About this transcript: This is a full AI-generated transcript of Everyone Should Hear This Before AI Changes Everything from Redacted, published July 21, 2026. The transcript contains 40,455 words with timestamps and was generated using Whisper AI.
"All right. Well, the World Health Organization is using AI to track us all. They announced this recently. We went over this yesterday, but what does this mean exactly? Are we safe as Americans because Trump withdrew from the WHO? Isn't this the power that we rejected them to have in the pandemic..."
[00:00:00] Speaker 1: All right. Well, the World Health Organization is using AI to track us all. They announced this recently. We went over this yesterday, but what does this mean exactly? Are we safe as Americans because Trump withdrew from the WHO? Isn't this the power that we rejected them to have in the pandemic treaty? Or are they casually just saying, okay, we don't get the treaty. We're just going to take all the power we want in piecemeal. Well, joining us to discuss is James Raguski. He is the author of Screw the Who and the one person I wanted to talk about when I saw this. Thank you so much for joining us. What do you think they're playing at?
[00:00:38] James Raguski: Well, you know, first of all, thank you for covering this issue because a lot of these things slip through the cracks. The epidemic intelligence from open sources program actually started in 2017. So they're just up to the same old tricks. You know, it's the same thing from the WHO show all the time. They actually claim that this artificial intelligence observation of the media identified the, you know, Wuhan lab leak early in, you know, at the end of 2019. They claim that by monitoring all of social media and media, they can identify things, you know, that are happening as soon as possible. Now, on one level, what we did, we meaning people like you, people like me and others around the world, we paid attention to news reports of people who were doing things that were not officially approved. We learned that maybe someone was trying hydroxychloroquine or trying ivermectin. And what we did is we looked at that and we said, well, our analytics of that intel tells us that that makes more sense than what the government is telling us. So what we're dealing with, with the, you know, epidemic intelligence from open sources AI program is not so much that they're gathering all this information. You know, you can go on, you know, Twitter or X and see that there's a trending hashtag. You can see that there's, you know, news stories going on. The point is, how do they do, what one of the things that they have is the news article credibility detection system. And they also have the misinformation classification systems. They want to use AI to lie to us. If they get information off of our social media posts, they know how to tamp it down. They know how to turn their propaganda machine against what is actually the truth that is out there.
[00:03:00] Speaker 1: Can I just put this on the screen and you can respond to this. They have been warning since 2020 about infodemics, which they describe as an overabundance of information, even accurate information, which makes it hard for people to adopt behavior. So they can't get you to do things if you get true information. So what you just mentioned, was it hydroxychloroquine or any information about masking that they wanted to tamp down or information about herd immunity or vaccine requirements, anything like that. So please go on because I think that this is a terrifying idea that they need to manage even accurate information.
[00:03:43] James Raguski: Well, this is the whole point. I mean, I got a report from a friend in Finland who, you know, they are still pushing back against the use of the fraudulent use of the PCR process as a quote unquote test. And so what we dealt with over the last now almost six years is lie after lie after lie from the news media. And people need to understand that for the most part, what things like Grok and ChatGPT and Claude and, you know, all of the other AI agents, they just simply collect the propaganda from the news media, regurgitate it as truth. And I can't tell you how many times I have, you know, come face to face, you know, beaten my head against a brick wall. If you ask ChatGPT a question where you know you have factual information and you watch it lie to you or say, well, I'm sorry, I can't answer that question because I'm not allowed to spread quote unquote misinformation. If you realize that AI is being used as a tool to further the propaganda machine now what they what they could use this system for, they're not going to, but what they could have used this system for knowing and understanding that it started in 2017. And it got, you know, a big push from the German government, they donated like $30 million to set up the hub in Germany to, you know, to start writing all the software programs and making it so that every nation and organizations around the world can use this. What they could have done is they could have used it to identify all the reports from people who said, well, you know, we're having adverse reactions to the jabs where people are dying, people are suffering. They could have used artificial intelligence to observe social media and stop the pandemic that we are currently still in the middle of with the MRNA jabs harming people.
[00:05:54] Speaker 3: But instead, they wouldn't have done that because all those many of those accounts were banned. You know, if they were on Facebook and they were talking about the problems they were having or if they were in groups talking about women who are having all sorts of trouble with menstruation after they received the jab. Those groups were banned and censored so they wouldn't have been able to pull that information because it was all, you know, hidden and pushed away from us, right?
[00:06:17] James Raguski: Exactly. And, you know, again, I want to compliment you and thank you for bringing this issue up. But people need to understand that this is just a new version. This is just 2.0 of their EIOS system. Their system was operable from 2017 until now. And what they did is they've proven that it works because they could have identified the epidemic of adverse events and deaths from the biological weapons that they, you know, have implemented on us. But obviously it did not do that. It labeled all of that truth as misinformation. The, you know, organizations, all the social media groups, you know, banned all those accounts. Just like you said, they could be reporting on the pandemic of, you know, adverse events from drugs. They could be reporting on all of the people's reports around the world, about a million things. But what they're doing is actually set up a pandemic simulator. It's been hard to get information. If I get anything on it, I'll share it with you. They essentially have a dashboard where they can simulate a pandemic and learn how to tamp down, you know, the truth that we the people are, you know, good at putting out there. And so what I want people to understand is we can and should be using this type of information, this type of information resources to identify the truth that is out there. It is getting more and more difficult. But what we did over the last six years, and I want people to get a positive view from what happened, we were able, human beings were able to decipher truth from BS. And what they're trying to do is use artificial intelligence, you know, to just I mean, now they have radio to, you know, transcripts where their system is going to be able to listen to audio shows or, you know, I imagine that could be turned on video productions. So that, you know, they're going to be able to listen and watch slash listen to redacted, turn it into a transcript that then their large language models can then interpret and, you know, identify how to fight back against the people who are bringing the truth with their propaganda messages. And so I'm optimistic that what we did over the last six years was identify the lies that government and the pharmaceutical industry and the medical establishment continue to put out, you know, to this day, I do the research that I do. And then I'll go and I will ask, you know, ChatGPT or Grok or one of these systems, you know, Google AI, and it is amazing how it will just, you know, I probably shouldn't say that it lies to you, because the way it's programmed, it just goes and collects all of the information that is, you know, quote unquote, available on the internet, and regurgitates the propaganda. It knows it is programmed to say, well, I'm not allowed to give you that information because that's misinformation, which doesn't mean it's inaccurate. It just means it's not what the, you know, proper official narrative is. And there was a statement that was made by, I believe it was the German health minister. And she said that, you know, they know that good information and, you know, transparent decision making is what will bring trust, you know, in the public health services. And it made me laugh out loud because the hypocrisy of it is so absurd, especially coming from Germany, you know, with the lies and the misinformation that came out of there during the pandemic. They know that they have to use AI to try to control the information that people get from sources like Redacted and all the other, you know, alternative media outlets. They're working overtime to hide the truth under the guise of surveillance, you know, and surveillance is really, it's an attack on privacy. It's an attack on our own security. And I just want to thank you for, you know, letting everybody know that the WHO is doing it, you know, treaty or no treaty. They just keep moving forward. You know, they've been doing this since 2017, you know.
[00:10:58] Speaker 3: Well, I was going to ask you, yeah, I mean, because, you know, obviously President Trump made a big stink about getting out of the WHO. And we've spoken to doctors who worked at the WHO and told us how corrupt it is. But does it matter? Like the fact that the United States is technically not a part of the WHO, Trump pulled us out of it. We're still affected by their information campaign, right?
[00:11:16] James Raguski: You know, the CDC has their own version of the epidemic intelligence, you know, program. They're busy collecting data. I'm going to follow this up with an article and, you know, look into the task force that Trump created just a couple of months ago in August for doing exactly this kind of information surveillance on social media in preparation for the 2028 Olympics here in Los Angeles. They're going to be watching social media for, you know, everything possible. And what's really interesting, as best I can tell, the task force has members, you know, has J.D. Vance and it has Attorney General Bondi and it has Homeland Security. But it doesn't seem to state that it has anybody from the Department of Health and Human Services or the FDA or the CDC. This is not about health. This is about health security, which is really, you know, propaganda and military control over our lives. So they have at the White House level a security task force doing exactly these things. And as best as I can tell, the United States is utilizing the epidemic intelligence from open sources system because it's just software. And, you know, it's just AI monitoring social media. So, you know, realize that when you go online and you give your personal information, you start talking about your health issues. They're scooping all that up and running it through their machine to identify what is going on. Now, if they were honest, if they were truthful, if they really cared about your health, they would have identified thousands of adverse events, the horrors that people went through with the jabs. But obviously they didn't. So we have proof from experience because this system is not new. It's just a new version over the last six years. They used it to clamp down on the truth, not to expose it.
[00:13:33] Speaker ?: Right.
[00:13:34] Speaker 1: Well, thank you for letting us know. I follow your newsletter. It's fantastic. And it's always alerting us to these small measures by which the World Health Organization continues to try to usurp power. I did notice recently, I'll just sort of end with this positive note. It used to be that here on YouTube, the medical misinformation guidelines stated that we could not say things that contradicted the World Health Organization's general guidelines. That's not there anymore. I don't know when they took it off. It used to be that they were the determining factor. But now that the United States is formally withdrawing, that could be positive. Right. That they no longer are the defining organization for what can and cannot be said on YouTube.
[00:14:20] James Raguski: So let's it does appear that things are looser. But, you know, that's part of the strategy. You know, they put the boot on the neck and then they take it off and you feel all better. But the boot will be right back as soon as they want it to.
[00:14:33] Speaker 1: Right. Yeah. Okay. Thank you again. Great to see you, James. The U.S. is paying Palantir to track and target Palestinians in Gaza, according to a new report that we can corroborate with official military sources. If you don't think this technology is going to be pointing at you, or at least that they don't want to, you are on drugs. And I'm going to show you exactly what it can do and why you should be worried about it. And we are unwitting complicit, unwittingly complicit because we're paying for it and allowing our government to do it right before our very eyes. What this is, is an A.I. Let me say this. Right. I don't want to. I don't want to mess this up. It's an A.I. powered kill chain. That's what it is. They're already running practice. It's not just a terrorist filter, although that's how they're selling it to us. It's a system that back tests whether or not you are killable through your social media, not just your movement, not just what you've bought, not just where you've been, where you've driven, but also your social media profile. It not only identifies targets, it manufactures them. Here's the report from 972 Magazine showing that the U.S. military has been operating out of a massive warehouse in southern Israel just north of the Gaza Strip since October. We know this because CENTCOM themselves told us the official line here when the U.S. military announced this is that they are bringing together stakeholders, a word I really don't like, in order to implement the ceasefire. Well, what does that mean exactly? Who are all the stakeholders in the ceasefire? It's not Palestinians, that much I can tell you. It's anyone who's allied with Israel in order to implement the ceasefire. Now, when Israel violates the ceasefire, no problem. But what they're looking for is continued justification to violate the ceasefire. Now, what they're doing is using this AI technology and surveillance to, in the words of the military, shrink the kill chain. Here is a test run that they did just a few weeks ago or a few months ago in July. They are doing this with a Palantir software called Maven. What it does is pull data together from satellites, drones, intercepted phone calls, messages, text messages they can read, basically the entire footprint of Gaza. And then it does what they call, this is Palantir's own term, optimizes the kill chain. How do we know that this is built by Palantir? We know that because last year the United States government put out this contract saying that they are specifically hiring Palantir to do that. Note here it says this is a one bid solicited. So that means they didn't really put this out. They asked Palantir to build exactly this. No other contractor was offered the job. But what does that mean? Optimize the kill chain. Well, you know, we know from many government reports, including the reports of Bradley Manning, how the government just goes out and under the Obama years and willy-nilly killed all suspects and targets. And they labeled any boy over 12 an acceptable military target, even if they were civilians. They didn't have to justify it. They could just say, "Yeah, sure, that guy. Let's kill him. Let's kill him." In the video that was launched by Sergeant Manning, it was the United States military firing on someone who had a camera, a Reuters reporter. "That looks like a gun. Let's just kill him." So what they're saying here is we can do a lot less willy-nilly killing. We can optimize the kill chain. Well, what are they going to use in order to justify this kill chain faster? It means they see a target, they run an AI search for any justification to kill that target. So say someone walking down the street, right? Okay, let's take a look at him. Scan his face. What has he said on the internet? Oh, he's been critical of Netanyahu. Fire. Fire. That's essentially how this works practically, right? They can highlight justifications to kill in real time, not just based on movement, history, and association. It can also be based on social media history. They do this using a data miner. This is a startup the United States has used before to access platforms like Twitter. So again, this is risk intelligence. So for now, they're saying, oh, you know, we're just looking for Hamas. That's it. That's all we're doing. But reports are not only that they're looking for Hamas, they're looking for any association with Hamas. Even is Bob's your uncle, right? Is your uncle Hamas? You're killable. According to reports, they're saying the criteria is not whether a person is Hamas, but also whether a person has their relatives tied to Hamas. So 972 is reporting that they are also targeting anyone with relative ties to Hamas. I mean, who knows, you know, how that can affect you. This is guilt by association. You don't even have to be a terrorist. That basically justifies killing everyone in Gaza, like these two who were killed on Monday. On Monday, on Monday, Israel claimed that they had targeted two Palestinian terrorists in Gaza that had violated the ceasefire agreement. Here's how they put it. They posed an immediate threat. Can we go back? Immediate threat. Can we go back to those two boys, please? Backwards. Those are the two threat. These two boys, aged 11 and 8. Their father's in a wheelchair. They were collecting firewood on the wrong side of the yellow line. And that's why Israel fired. According to Israeli reports, the Times of Israel, again, these two were hunting for firewood. So how that is a threat to an immediate threat to ID of soldiers, I'm not sure. Now, if Israel has this identity tracking software, wouldn't it have been able to save these two? And no, these two don't have a WhatsApp. They are not posting on any social media. That little boy's eight. So how can we in AI real time? Is it because maybe he has a cousin who they have been able to target as Hamas? We don't know. Or the scarier question would be, is this what comes of this software? Were they identified as targets as association? This, of course, is one of many problems of using this software, that it doesn't know morality. It only knows inputs and outputs. If the target switched from, say, now here's where it could apply to us, because the Trump administration has already said that we have identified domestic terrorists, which are not a thing. There's constitutionally no such thing as domestic terrorists, because then the government could use it to any opposition, right? And so we know that. We've talked to Judge Knapp about it several times. So as the government expands this idea of domestic terrorists, then the kill chain stays the same. Okay, we're using this only to target Hamas and terrorists, but now we have this idea, this false idea of domestic terrorists that could be used on us. What we think, what we say, we think we can say anything right now because it's a free country. But if you were to take a compilation of your social media feed or your private messages, does that then mark you as an acceptable target? And we saw that happen, in fact, during the BLM riots in 2020. Now, this creates a permanent AI-driven enemy list that never expires. Palantir has already lobbied the use of this in the United States. This means not just optimizing the kill chain, it also means automating the propaganda chain. Because as you expand what is unacceptable thought, then you sort of, it acts as a dragnet of who is put in it. It expands who they need to track and what. So that's why this is genuinely dystopian. Let me know what you think.
[00:22:33] Speaker 4: I want to say really quick that I think this story just puts you on the potential next week's anti-Semite of the week list. So congratulations.
[00:22:41] Speaker 1: Oh, well, yeah, I've been mostly ignored by those groups. I want to say a couple of things.
[00:22:46] Speaker 3: This data miner company is interesting because we've, I think we've covered them before here on the show, but they bought a company a while ago, I think last year or so called Threat Connect. Remember that? No, I don't. So data miner bought Threat Connect and they've received like hundreds of millions of dollars in funding from all sorts of different sources. And this Threat Connect software and information, this AI stuff that they bought to fold into data miner basically aggregates your social media, looks at all of it. And then as you pointed out, it gives us like a threat assessment level. It quantifies like, oh, she's said these eight things against Tomas or she's pro. She said these eight things. So then it, it, I'd love to see that chart. Like, how do you quantify this? Like, who's the quantifier in chief at over a data miner who's telling us you've, you've released these many videos on this, you've reached this threshold. And therefore then you're put into this sort of dragnet.
[00:23:39] Speaker 1: Well, look, we are very narrowly protected by the constitution right now. I'm allowed to hate whoever I want. I can support whoever I want. As long as I don't go off and fight, you know, for, I don't know, the Taliban or whatever. I mean, the United States, those are the only, I think there's the only one example of the United States revoking an American passport. Uh, but for the most part, I can sit here and hate and love whoever I want. But if those expressions are aggregated on social media and the Trump administration is able to sell this idea of domestic terrorists, then you can see where this is going straight to 1984. This is terminator, terminator level, scan your face, scan and target.
[00:24:22] Speaker 3: Well, a lot of people in the chat room are saying, yeah, Skynet is real. Skynet is here. Absolutely. It's like, when you watch terminator, which we did a few weeks ago for the first time that our kids never saw it. And they were like, Whoa. And like, this is more relevant today than ever before. Yeah. The idea of Skynet with Palantir and drone surveillance. We covered it yesterday in the UK, what the UK government is doing. But the other thing you pointed out in the story, which I found interesting, which is the, is the no bid contract. So because Palantir is basically an arm of the CIA, it's an arm of DARPA. It's an arm of the intelligence community. I mean, it's received, it's basically it's marching orders and funding from that. Yeah. So there's no, like no bid contracts. No one else can compete with this. It's just Palantir because we created them. That's the whole purpose of having this company.
[00:25:06] Speaker 1: That's not a government contract. That's an order. Right. You've ordered that software. It's, you didn't put it out for general bidding. And in fact, this is the second, second time just on redacted. We've covered a no bid contract for Palantir. We did that just a few weeks ago. It would be interesting to go back through all of the Palantir contracts and see how they had no competition. So it's just the United States government saying, you come here, build me this, build me this, build me this.
[00:25:32] Speaker ?: Right.
[00:25:32] Speaker 1: It's happening. It's real. It's not a conspiracy that, you know, yes, it is conspiracy theorists, conspiracy knowers. We love it because it's real.
[00:25:43] Speaker 3: Well, and also one of the conspiracy theories, you know, it's like, oh, that it's going to come home to the United States or it's going to be here. That's just a conspiracy theory because it's only meant for overseas threats, which is laughable. I mean, it's laughable.
[00:25:56] Speaker 1: Just look at how they're ever heard of Edward Snowden, how they're not going to track.
[00:26:00] Speaker 3: Well, I mean, just look at also far, you know, all of these things and having to or the was it? What is the the carve out for for the warrant warrantless wiretapping in the United States? And then that new carve out that's been added in. And of course, people like Matt Gaetz and others trying to get it removed so that the FBI can't just like blanket Americans and all of this. So, yeah, we're losing our constitutional ability to protect ourselves and privacy in this in this country because the governments are going around the Constitution. Yeah, that's exactly how this is operating.
[00:26:32] Speaker 1: I mean, I think that one of the things that we need to scream about the most, there's so many. Right. And it's hard. War in Russia, killing civilians, war in Gaza, killing civilians. Now, Venezuela, we're busy. We got a lot to be outraged about. But if the United States government is using the words domestic terrorists, you can see what they have in store for you. Again, that should not be a thing. There is no such thing as domestic terrorists because giving the government that power means that any anti-government group can be labeled a domestic terrorist and locked up. That is the basis for 1984 level living. So, I mean, this is one thing that, you know, I know I keep saying it every time we have someone on. There's no such thing. We can't have the government can't label us terrorists. They are going to continue to try. So either you're awake to it or you're not.
[00:27:23] Speaker 4: Well, and also it goes to like where, you know, like right now, it's it's they're saying Hamas or whatever. But even if you say Palestine, they consider that Hamas. So it's like what level of words were they going to turn in to mean something that they don't in order to keep going deeper and deeper. And the thing is, like, people are already being deported for saying that free Palestine. Yeah.
[00:27:43] Speaker 1: Yeah.
[00:27:44] Speaker 3: Yeah. And now we have, of course, the big travel bans, the Homeland Security chief, Kristi Noem, you know, saying that she wants to have a full travel ban on every damn country. Those are her words. You know, anybody who's bringing killers, leeches into the United States. So, of course, putting everyone in this database and be able to monitor them. And Palantir has supreme authority on this. And as people are pointing out in the chat room, J.D. Vance, of course, you know, taking money from Peter Thiel. So you see where all this is going. They're all like these cozy bedfellows inside the Trump administration with this.
[00:28:14] Speaker 1: Yeah, I do want to ask you about the A.I. piece, because what do you make of that? Now, maybe I'm being cynical, but my take on that is, oh, they need a war bot, basically, because the consumer based A.I., as biased as they are, will still not let you. I try to have this exercise of like, hey, you know, can we start a war based on WMDs? And it doesn't let me if I try to get my A.I. to say, can I start a war with Iran based on hypothetical nukes? And it won't. So, you know, I think this is my cynical take on it, that that they need something to work around because so many wars are sold on lies and propaganda. But what am I missing here? Maybe there's a benevolent reason and I'm just being cynical. What do you think?
[00:29:00] Speaker 5: No, no, no, absolutely not, Natalie. Sorry to say that. But yeah, I think it's worse than that. And what Hexeth was talking about here was a platform to go on military desktops around the world, just as we use ChatGPT or OpenAI or Claude or Gemini or whatever. This is a secure version for the Pentagon and the military services that doesn't allow information to get out, essentially, because we all know that A.I. takes as much information from us as it gives us. Right. So the military needs something that would be sealed, that would only essentially be one way in, not one way out. The problem with that, to get to the point you're getting to, Natalie, is that who controls the A.I., you know? And this is the two main things I see this reliance on A.I. or the future reliance on A.I. going towards. And Hexeth said yesterday or the day before that, you know, you spell the future of war with two letters, A.I., are two things. One, a continuation of the outsourcing or privatization of war. So who ultimately owns these A.I. platforms and then who informs them and who gives them its algorithm and its programming and essentially its orders on how to answer questions? I've been coming across this more and more as I do my work, as I do my research. And I got into it with ChatGPT today regarding what are reliable and reputable news organizations. And you can imagine the response I got from ChatGPT about that. Did smoke start coming out of the machine? This is this is really important, right? You know, that the answer it gave me was that it relies at the end of the day, it defers. Its programming tells it to defer to institutional structures as opposed to historical accuracy. So, you know, internally, are you going to have A.I. programs that are not going to give honest, candid, objective information, to members of the military, but are you going to give them information that is based upon narratives that the Pentagon itself wants or maybe the manufacturers of these programs want? The other thing about this is there's always this idea that as technology advances, the military becomes more accurate. And so less harm is done to civilians. This is a great myth. I mean, one of the great myths about precision guided munitions, right? So laser guided bombs or GPS guided bombs is that they were invented in order to not have as many civilian casualties. That's a complete lie.
[00:31:37] Speaker 1: It's a precision paradox. Right.
[00:31:39] Speaker 5: Well, I know it wasn't. There is no purpose in preventing civilian casualties. The purpose was to make the weapons more efficient. So we had to drop less bombs to, say, blow up a bridge where when you had an unguided bombing system, it might take you 10, 15, 20 bombs to hit a bridge. But when you bring in a laser guided bomb, you only need one bomb, right? I mean, that's the idea behind it is efficiency. You even see it in things now. There's a weapon out there. If people read the reporting coming out of the genocide in Gaza, the Israelis use a bomb a lot of times called the small diameter bomb. And in conversations in the U.S. and Washington, D.C., they will tell you the idea the small diameter bomb was meant to limit collateral damage. I mean, limit killing men, women, and children who are in combatants. That's not the reason. The small diameter bomb is exactly what it says. It's a small diameter, which means that you can get more of these onto an airplane and drop more of them. That's the whole purpose in the small diameter bomb. It's not meant to limit collateral damage or to limit civilian casualties. Oh, my gosh. And what you see then, though, is where does this technology go when you start talking about AI? You just have Volodymyr Zelensky talking about how dangerous the AI advances in the Ukraine war are. You know, a sense of the autonomy that we've seen coming through in some of the drone systems. The Russians have some AI drones that operate on their own, essentially. This way they can't be jammed. You know, it's one of the reasons. But also, too, they take off with orders put in of what they're going to go look for, what they're going to find. But what we've really seen the inhumanity, the dystopian nature of AI, is through the Israeli systems. Yeah. So in Gaza, you've seen that Israelis utilize three separate AI programs: Lavender, Gospel, and Where's Daddy? All of these are incredibly nefarious and insidious, and I encourage people who are not familiar with them to look them up, particularly the reporting that came out of the Israeli media on this, +972 Magazine. But just to example, Lavender is a program that scans the Internet, scans social media, whatever databases it can get into, and it identifies targets. So because, you know, Clayton, you clicked on something on Facebook three years ago, that may mean that you're a Hamas supporter based upon the parameters of the Lavender program. And then what it does is it connects that Lavender program, then connects to a program called Where's Daddy? And Where's Daddy was a program that ensured that the Israeli drones and the Israeli warplanes were hitting Palestinian resistance fighters, not when they were away from their families, but when they were with their families. So the Where's Daddy AI program would track the targets that Lavender would identify, and then it would tell the Israeli warplanes or the Israeli drones when to drop their bombs, when to fire their missiles, based upon when those resistance fighters were at home with their families.
[00:34:32] Speaker 3: I mean, this was shocking, and your friend of the show, Tucker Carlson, just kind of did a report on this today, too. I encourage people to watch it to go more deeply into what Matthew's talking about here, which is crazy, that they had to track men and then bomb them when they're with their children, not when they're without their children. Right. I mean, you can't get more demonic than that.
[00:34:54] Speaker 5: And if anybody thinks that an American AI system is somehow going to be any more benevolent, less dystopian, right, any less criminal or immoral, I don't know what to tell you.
[00:35:07] Speaker 3: Even Ambassador Huckabee today, I don't know if you saw this, Matthew, I'm sure you did, said Israel did not attack Qatar. They just sent a missile into their country aimed at one person. And unfortunately, he says, quoting him now, there were some people who were nearby that missile strike that were injured or killed from it. So they didn't attack Qatar, they just sent a missile there like, you know, like Santa would send presents to a kid, I guess.
[00:35:34] Speaker ?: Right.
[00:35:35] Speaker 5: This is the way that people justify themselves, the way that these war crimes, these atrocities are apologized for. It's what allows the warfare to continue, you know, so swimmingly. I'm reminded of what George Orwell said about the war in Spain, which he took part of in the 1930s. And that was really the first war where aircraft were used in a modern manner. And Orwell took heart in that, right, in the sense that maybe this means that those who had allowed us cheer cheerleaders for wars, those who believe in the war the most, those who support the war most, or who make apologies for it, like a guy like Huckabee, maybe because now these planes are able to bomb something 200 miles from the front lines. Maybe that means these cheerleaders for war, if they get some holes put in them, they'll be less supportive of the wars. You know, you know, that that's the type of thinking that that we have to go to is how do we make people who benefit from the wars feel the costs from the wars? And I'm not talking about blowing up Mike Huckabee or anything like that, but in the general sense of how do we make the costs of war be felt not just from the people on the ground who are enduring this, but among the ruling classes that benefit from it.
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[00:39:09] Speaker 6: Well, I actually, it's funny. You said that I don't know much about much, but I, I'm interested in this subject and I've, and I know people involved in, so I've definitely learned about it over the past six months. And yes, there, uh, there are examples of ongoing wars, not any I'm aware of in this war, but, um, in other conflicts ongoing where targeting decisions have been made by machines with no human, uh, sign off. Uh, sign off. So I find that like one of the most shocking things and that's a fact with no human sign off. That's correct. That's correct. Um, I mean, I, you know, I mean the data are input into the, you know, I mean, I think the targets are loaded or something, but like the, at the end stage, it's just like, you know, identify kill. And so that to me is like a profound change and really, really distressing. It's like, it's like the pager attacks, you know, a hundred X, you know, the pager attacks where we just, we put bombs in these pagers and then they, they kind of circulate and we hope that they blow the legs off the right people, but there's no way to know. You know, that's not acceptable. That's a, an act of terror. And, and yes, I'm aware that like bad people were killed, but innocent people were killed. So that's an act of terror in my view. I mean, not by my view, that's by definitionally, it's an act of terror. I think it's very closely related to autonomous weapons. And you saw this really interesting argument of fight breakout between a big AI company and the administration right before the Iran war. And the company made the case that, look, we are not into two things. We are not into autonomous weapons and we're not into mass surveillance in the United States. And they lost their contracts famously. And it was, there was so much going on at the time that I didn't look quite closely enough into it, but I have since. And I do think those are the sticking points and maybe I'm being misled, but I believe that's right. Autonomous weapons and mass surveillance in the U S both of which are totally unacceptable, both under our constitution and under our existing moral framework. So, but as to the bombing of the girl's school attached to the Iranian military base, I actually called around today on that cause I'm really bothered by it. And the response that I got was, yes, AI is involved in all of this, but under current protocol. And in this specific case, a human being pressed play on this. Okay. So there was a human, but here's the question where the coordinates come from, right? Right. Who fed those coordinates to the United States military? This was the United States military. Now we know that most of our SIGIN, our signals information or electronically gathered information from Iran is translated by Israel because they're our partner in this venture. Well, we have two different aims. Israel wants the total destruction of Iran. And at this point, I think the United States, I can say, kind of just wants to get out. So Israel has every incentive to encourage the United States, you know, intentionally or not to do things that cross the point of no return where a diplomatic solution is really not possible. One of them would be killing the head of Shia Islam, who's 86 and like has prostate cancer. Why would you do that? That'd be one. Once you kill their religious leader, you're kind of all in. And another would be at least potentially killing the daughters of Iranian naval officers. And so I don't know that that happened. And I don't want to suggest that I do because I don't. But as this is investigated, I hope the question of where the targeting coordinates came from is raised and answered, because they certainly had motive to do that, because, again, it's not even an attack on Israel. Their goals are different from ours. And so to partner with a country in a war that has a different endgame than you do is one of the craziest things this country's ever done.
[00:42:59] Speaker 1: Well, right. And if you as you've made the case beautifully over the last week, if Israel is trying to sabotage the American government to get them to leave the region and no longer be a competitive superpower, which would mean that they don't have our best interests at heart, then this technology, which is born and used in Israel, first and foremost, you know, the Palantir Maven software is used to track people in coordination with data miner, which can also cross check your social media and target you. And so the things that we've worried about the most have come to fruition being led into a war by our model ally, according to the Department of War. And so what we worry about next is that it will be targeted towards us. And that seems like a real possibility that your social media will target you as someone to be tracked in order to. And can you play out worst case scenario? Because we already are in one. What would be the next?
[00:44:04] Speaker 6: Well, I mean, you know, big picture, it's just always true everywhere that war changes societies faster than anything else. It's a great accelerant of social change. And a lot of the big social changes in our society over the past couple hundred years grow out of the changes during war. And some good, some bad, but always big. And one of the changes you see in every side, you've seen it in Israeli society. The Israel of 2026 bears no resemblance as a visitor to the Israel that I visited in years past. It's just a different, seems like a different country, different attitudes, different people. One of the reasons for that is a seven front war. You know, if you're constantly fighting wars and people are dying, you know, your tolerance for brutality, your anger at the people you're fighting, everything about your attitudes changes very, very fast. They harden and you become much more tolerant of atrocities than you would be in peacetime. That's just a fact. And you become much more tolerant of hurting your own citizens, people who disagree. I mean, you saw this in Great Britain during World War Two, Winston Churchill, who I know were required to, you know, deify presided over the imprisonment of his opposition party during the entire length of the war and their families and their wives. They're rotting in prison away from their little kids, in some cases, their infants. And their crime was being the opposition party and being disloyal and unpatriotic. They weren't. The opposition party was led by a First World War war hero who fought not just as, you know, a pilot in the sky, but and in the trenches, like one of the great war heroes for a member of parliament. The country ever produced and he and his wife and his compatriots and their wives were interned without charges by Winston Churchill for the duration of the war. That happened in Britain, which is like much more humane than a lot of places. So, you know, we should not FDR interned the Japanese, including American citizens. That stuff happens during war. And so I think we should be on guard for sure. I don't want to be paranoid or, you know, creeped out or or inspire paranoia or fear and other people. But I think it's worth worrying about it. And rule by technology is clearly one of the goals. I mean, what what else is the endgame? If the U.S. government doesn't spend, relatively speaking, much time trying to improve the lives of the people who pay for it, like the citizens of the country, you either get some kind of revolt or people like this isn't working. Why would I why would I pay my taxes? Why would I put up with this? Or you respond to people's legitimate concerns, make a good faith effort to make their lives better. Or you use technology to enslave them and shut them down so their opinions don't matter. Those are kind of the three options. I'm hoping for number two. But but you can certainly see the incentive to use technology against Americans to stop their bitching. I saw today who's the guy with the eyebrows on Facebook? Oh, Ben Shapiro. Shapiro. I'm so sorry to be mean. Yes. Ben Shapiro was was calling everybody who disagrees with him left and right because it's a horseshoe theory. He's sort of right about that, actually. But the the party of discontent or the party of complaining, you're complaining. Yes. Why are you complaining so much? The guy's like got one hundred and five IQ and he got into Harvard. So it's like, hmm, I'm thinking he might have been the beneficiaries of special treatment. He and Bill Ackman both went to Harvard and they're both kind of dumb. So it just tells you that this is you know, these are the people who run the country. This is the ruling class. Every nation has one. But to get a lecture from them about how you've got it easy. Stop complaining.
[00:47:46] Speaker 1: Well, before the break, we just asked who you thought would be the most vulnerable to be replaced by AI and unable to find new jobs. One person said humans. Another person said Karen's. Actually, the person that said Karen's is more right than the person who said humans, because the data shows that AI will replace women, specifically women in rural areas in the workforce, according to new research. Now, what does that mean? It means we're headed for a new age industrial revolution that will leave behind mostly the women who we girl boss talked out of their homes to get jobs, say, as secretaries and administrators because sex in the city told them their lives would be fabulous if they prioritized a career over their home lives. Now, those ladies who live in rural America working administrative jobs, they're going to be left straight on their butts. Think about the first time this happened when entire factory towns were depleted because those jobs were moved to India or China. Men out of work, towns, schools gutted as people left these towns in search of new jobs. Well, this time it will be women who have the rug pulled out from under them, but the jobs won't be shipped to Asia. They'll be shipped to A.I. And how will the government then tax this lack of slave labor that we no longer have? Well, don't worry. There's a plan in place for that, too. Guess who will pay for it? The rest of us who still have jobs. The welfare state will expand. Government power will concentrate because of new dependents. The rest of us will pay for those who can no longer work while the bots do it all. Fantastic, right? Let's look at the data. This study was published just a few months ago by the National Bureau of Economic Research. They're a North American research firm that's mostly funded by Wall Street and big business. Take a look at their funders. These are the companies that are obviously interested in this A.I. shift because it will be their workforce. Do you have that? The screen of the funders? Yes, those companies. Google, you know, Fidelity, Exxon, Microsoft. These are the vanguard. Obviously, they want to know how A.I. is going to shift the workforce. That's why they are funding this. Now, the study looks at what's called A.I. exposure, meaning how likely is your job to be replaced by A.I. versus workers' adaptive capacity, meaning how likely are you to pivot and find something else to do to support yourself. They estimate that 70% of all A.I. exposed workers will be able to manage the job transition. I feel like that's highly optimistic. Yeah.
[00:50:24] Speaker 3: Don't you think? Because the amount of learning you have to do to go through, I mean, to take training courses. Right. I mean, even just to have a cursory understanding of it is still pretty complicated for a lot of people.
[00:50:33] Speaker 1: So they're saying that of the, I think it's 200 to 300 million people who will be replaced by A.I., 70% of them will be fine and be able to do something else. I don't know if that's a lateral move. Is that like, oh, you can't be an accountant anymore? You're now a line cook? I don't know. Like, they're just saying they will be able to do something. Okay. But 6.1 million workers will not be able to do something else. 6.1. 86% of those 6.1 million people are women, most of them living in the Mountain West or the Midwest. Now, let's look at it by profession because they do give us this nice graph. What you're looking at here is the x-axis is the bottom line, meaning A.I. exposure. How likely is your job to be replaced by A.I.? So you see on the left, close to the center, is dentists. Obviously, they think dentists will not be replaced by A.I. But really, the jobs that are going to stick around the most are labor jobs, electrician, builders, things like that. When you break it down by the least vulnerable, you see, again, in the red, this next chart, the professions like dentists, firefighters, software engineers, physical laborers. These are things A.I. will not replace or at least cannot do alone and needs humans. Now, look at the higher vulnerability scores in the blue, meaning actually, no, let's go to the red, the next one. These are people who will have the least ability to adapt. So what we're looking at is people who will be replaced by A.I. and have no ability to find new jobs. So what we're looking at is things like office managers, secretaries, receptionists, administrators, interpreters, executive assistants, insurance agents, claim processors. It stands to reason most of these are women. And these are not women who wear clothes like Anne Hathaway in The Devil Wears Prada. These are full time women who are away from their kids, mostly not living the girl boss life that sex in the city promised them, barely getting by to support their families. The feminist revolution pulled them into the workforce. Where will you think those feminist inspirational figures will be when these women are dropped on their butts? I just wonder what the feminist message will be for these invisible ladies who are left behind. Now, will they be able to go back home, go back, you know, to a leave it to beaver type lifestyle? Well, many of them might like to, but they're not able because they have high mortgages, high levels of debt. Most of them don't have real partnerships with the husband who can help them. So that makes this impossible. Where will they go? It's kind of a daunting question. I don't have an answer for maybe back home with the children. Well, I just offered that they can't. Most of them can't. Well, yeah, because of because their transition to the workplace came with the trap of a 30 year mortgage. It came with a trap of a high debt based society. It came with the trap of a promise of, you know, this like girl boss lifestyle that they cannot leave. And they're they they're mothers. They don't have. This is not like, oh, Carrie Bradshaw quit her job, but she still can buy $200 stilettos. That's not what this is. Now, researchers say there are four ways to predict who can adapt to the A.I. workforce and who can't. Number one is just to have a lot of savings. Be rich, you guys, and you're going to be fine. Be young because workers over the age of 50 will have a harder time where they live. If you live in a city, you probably can find another job a lot easier than you live in a rural Midwest town. And whether or not they have transferable skills to what? I don't know. But that's kind of a you know, duh. So what does this all mean? This means an expanding welfare state and who will pay for it? Well, you will pay for it through expanded taxes and fees if you get to keep a job. This was laid out in 2024 by the International Monetary Fund. In this document, they lay out a plan to have workers start right now, in fact, to pay into funds that will be used when A.I. takes our jobs because they know that they can't tax the bots. See here, they call this the erosion of the income tax based. That means us, their tax slaves, will go away. So what does that mean for the rest of us? Well, it means some of us get replaced and pushed on the dole, expanding government powers in the welfare state. The rest of us, lucky us, if we get to keep our jobs, we get to pay more into running the system that has replaced our fellow man. Let me know what you think of this. It's dystopic. It's happening. Yeah.
[00:55:29] Speaker 3: When I say, well, I think you're right. Like I was immediately thinking of universal basic income like this will be. We keep hearing this from administration people. We keep hearing it from Elon Musk. This idea that, you know, A.I. will make us will reduce famine. We'll have increased prosperity because productivity through A.I. will level the playing field. And then, yeah, I guess we'll have some sort of universal basic income. So these women won't need to work at these office jobs. They'll just be handed a check from the government as part of some sort of A.I. subsidy.
[00:55:57] Speaker 1: And then what? Like it's not, I mean, this is not an empowered lifestyle they're pushing us towards, right? It's not like, oh, you're going to be a trad wife and be happy. And you have a husband who's working something and you are actually climbing the social ladder. No, this is, again, an expanded welfare state. This is an expanded dependency on the government. It's extremely concerning. Yeah.
[00:56:20] Speaker 3: Well, those people in the chat room are pointing out feminism was always a psyop. What do you have to say about that? Yes.
[00:56:26] Speaker 1: Please look at my interview with, what's her name? Rachel Wilson. Rachel, the woman who wrote the great book about feminists. Let me find it. Yes, that's exactly true. That's Will. I mean, you know, the sort of feminist girl boss mantra has nothing to say about women who work office jobs and try really hard to support their kids who are in latchkey. That's not really for them. It never was. And they won't give a crap about them sort of losing that. And, you know, PR is one of them, publicists, these sort of, you know, heel clicking city girls. They will have their jobs replaced by AI too, but they'll have a, you know, some sort of new, I guess, you know, bourgeois existence. Yeah. So, you know, those are not the ones we're really that worried about. And the feminist movement never really was, you know.
[00:57:20] Speaker 3: Well, forget doctors over prescribing antidepressants or SSRIs. How about AI chatbots can now do it? And here is a new report out about AI chatbots prescribing psychiatric medications, raising some big red flags. A Utah pilot program will allow an AI powered system to authorize prescription refills for select psychiatric medications. Don't have to worry about a doctor anymore. An AI chatbot can just tell you, hey, you seem depressed. We should just fill that prescription for you. Dr. Joseph Derring is a former FDA medical officer and the founder of the Taper Clinic. And the doctor was a great guest on our show a few months ago when we talked all about just how demonic and dark and damaging SSRIs are. And, of course, your Taper Clinic helps people get off of these SSRIs. So, doctor, great to see you again. When you hear a story about AI chatbots now being able to prescribe this stuff, what do you think about it?
[00:58:27] Speaker 7: It makes me want to vomit. You know, it's so disturbing. It really throws me off. But, you know, firstly, Clayton and Natalie, thank you so much for having me back. This is the worst of American healthcare happening right now. Now, some people are going to look at this and say, well, you know, AI chatbots prescribing antidepressants, and they're going to want to see the rosy side. And that's how they pitch this. They say it's going to increase access to care. It's going to be cheaper. But the problem with that is that it's just bad care. It's nice if you have better access to care for something that works, and it's cheaper to get that. But this simply does not work. So what is essentially going to happen with this pilot program from Legion Health in my backyard here in Utah is that once an antidepressant is started by a doctor, it can essentially just be continued by an AI. You know, someone can pay $20 a month to essentially keep on getting that prescription refilled and essentially receive no help to find non-drug solutions for their mental health, and they're going to end up essentially just addicted to this drug, which will wear off over time, as we know. And it's going to be a huge problem. And really, the other thing that's very interesting here is it is front page news since yesterday that we are overprescribing antidepressants. Bobby Kennedy was recently talking about how HHS has to step in because the American Psychiatric Association and other medical leaders right now are doing such a poor job at reining in the overprescription. And so this AI kind of prescribing, indiscriminate prescribing and refilling of antidepressant medications, without a doubt, it is going to make the mental health of Americans worse.
[01:00:27] Speaker 1: Right. And so, I mean, the way they're presenting it is it's just a continuation of what a real doctor has already prescribed. But this opens the door towards AI based care that can start the prescriptions. Also, AI is not focused on weaning anybody off of these drugs. And so you can see that this is a slippery slope that will lead us to increased use of what we have not fully studied, but seems to indicate to be dangerous.
[01:01:02] Speaker 7: Yeah, absolutely, Natalie. This is going to be a slippery slope. And we have to be really discriminating about where we use AI. Like, for instance, you know, having AI maybe assist an emergency room doctor in looking up a, you know, urine culture where there was a bacteria there and then suggesting an antibiotic. And that might be a good fit because we know that, you know, certain bacteria just respond to certain antidepressants. But when we start veering off into mental health conditions where, you know, depression is not a serotonin deficiency to be fixed by some Lexapro or some Prozac. You know, depression is due to relationship problems, problems with meaning and purpose, poor physical health, substance use. I mean, it is very complicated. And the other issue is mental health in the U.S. is not ready to be scaled in this way. Like right now, just the doctors doing this work on their own. They're actually doing a pretty poor job at looking after mental health right now because we see patients in these 15-minute transactional visits. We have no time to help them on any of the non-drug approaches to address those various things that I just mentioned just a moment ago. And they're just prescribing meds. And so making an AI bot do this, it's just pouring gasoline on a fire. AI should be used to help make systems that already work more efficient. But when you have a system that's not working right now, pouring AI to that, it's just going to be a dumpster fire.
[01:02:46] Speaker 3: What if I play devil's advocate? What if we role play this a little bit, doctor? Because as you and I talked before, these doctors, I mean, they're getting all sorts of like incentives to be prescribing this. They're really not even looking at the underlying causes of some of this depression, whether it's bad diet, on and on and on, right? So what if AI is the solution to all of these doctors that have massively over-prescribed? But what if AI is like a firewall? And it's like, eh, no, you need to go out and get some vitamin D. You actually don't need this Lexapro. And someone's sitting there saying, wait a second, ChatGPT. Yes, I do want my Lexapro. Sorry, you need to go out and get some sun. Oh, and by the way, stop eating all that processed food and stop taking all of those hormone replacement. I'm playing devil's advocate here. I'm trying to be glass half full. But could it be that this might actually be the wall to stop this?
[01:03:44] Speaker 7: Let me react to that, Clayton, because I do think it's important to look at it in that way. But if this AI was like a Maha AI, trained on all of these non-drug approaches, absolutely, for sure. But AI is only as good as the data that goes into it. And right now, the American Psychiatric Association is so far off the rails when it comes to guiding the doctors in this country on how to help people with mental health problems that it's going to be trained on that. Right now in the guidelines, they're recommending antidepressants as a first-line treatment for anxiety and depression. These are drugs that haven't been studied longer than a year. They wear off over time. They make some people sick. They are sicker over time. And so I think AI is only as good as the data on which it's trained off. So maybe in the future, it could be really helpful. But right now, I think it's not going to be. That's a great point.
[01:04:45] Speaker 3: It's garbage in, garbage out. It's only as good as the programming. And if Big Pharma, frankly, is writing the code that goes into these chatbots, they're going to be benefiting themselves. Could you just talk to our audience about how detrimental SSRIs actually are?
[01:05:03] Speaker ?: Yeah.
[01:05:04] Speaker 7: So, well, let's talk about these drugs. I think the most important thing to understand about them is how they work and what they do. Because that's the difference in it being something very detrimental and it being something that could actually be helpful for someone. So there's been this big narrative that these drugs are like diabetes for insulin and they fix a chemical imbalance. That is a lie. And when you take a drug in that way, believing that it is simply going to fix your problems, your relationship problems, your work problems, you know, this chemical imbalance in the brain, it is simply not true. And it takes you down a bad path. If you look at an SSRI for what it is as essentially a chemical that can numb your emotions, constrict your emotional range, you understand that it really is like taking Tylenol for an injury. And when you do that, you can use it with a lot more responsibility. So the problem is, right now, 80% of these drugs are being given out by family medicine doctors who spend seven minutes of face time with their patients. They come in, they fill out a questionnaire on depression, and then they give them the drugs and they just sail off into the distance and they maybe see them two or three times a year. This is a problem because they are not getting to the underlying reason why they are depressed and they're getting put on a drug that's going to wear off over time and can potentially make them worse. So that's why they become so dangerous. They become so dangerous because they're packaged in this lie that all you need to do for your mental health is take this drug when in fact that's not the case and the drug wears off over time and you can end up worse off in the long run. And so the place for antidepressants really is in very short term, very acute distress. Yes, you can take it, but you should always take it with a plan to come off. And the issue right now in America is many doctors, they just kind of passively prescribe it because it's too complicated to work with patients to find the non-drug solutions to their mental health. Yeah.
[01:07:08] Speaker 1: Well, thank you so much for that assessment. And yeah, it's something we need to look out for, especially as parents. I feel like they're constantly pushing it on our children. This idea that life's too hard. You can't handle it. You don't have the tools to handle it. You know, it's a constant breakdown of what is normal coping mechanisms, which is family, health, you know, accomplishment, that kind of thing. So it's great to hear your assessment of it, your professional assessment. So thank you so much for joining us. Well, thank you.
[01:07:39] Speaker 7: Yeah. Thank you, Natalie. Great to see you again, Clayton.
[01:07:42] Speaker 3: Thanks, Doctor. Great to see you as well. We keep hearing the hue and cry. More and more people complaining about this. People who live in communities around the country are now complaining about this low hum, this buzzing noise of these massive, massive AI data centers that are being built near their homes. Take a listen. I would go insane.
[01:07:59] Speaker ?: I would go insane. Can you imagine that? Well, it's kind of like a white noise machine. But nonstop, constantly? Can you even hear the birds? Like you'd just be hearing this low hum?
[01:08:05] Speaker 1: I just feel like anxiety about what possible radiation I may have exposed myself to just listening to that.
[01:08:22] Speaker 3: That? Yeah, I don't know. But your hearing is not the best in the world. So you probably wouldn't even notice it.
[01:08:26] Speaker 1: Well, that's rude and unnecessary.
[01:08:28] Speaker 3: But true. But the noise is one thing. Now governments are being accused, state governments, and local power companies are being accused of seizing land as part of imminent domain. Yes, people's homes in order to tear them down, build large data centers. Here's one Georgia resident who went viral this week saying her home is about to be taken for an AI data center. Watch.
[01:08:50] Speaker 8: Hey, you guys. My name's Ansley. I live in Coweta County, Georgia. I wanted to come out here and show you guys firsthand what is happening to our county. So as you can see behind me, we have these power lines. Georgia Power is going to expand these lines to support power to the data center. What they're doing to homeowners is they're taking their homes. This is my childhood home behind me. It is being taken by force by Georgia Power. Homeowners in this county do not have a choice. It is called eminent domain and they will take it.
[01:09:23] Speaker 3: Unbelievable. Austin Steinbart is a social engineer, founder of the Quantum Party of America. Shannon Joy is an independent commentator and host of the Shannon Joy Show and they both join us now. Great to see both of you. Thank you for being here again. Thanks for having us.
[01:09:38] Speaker 9: Thanks for having us.
[01:09:39] Speaker 3: Our pleasure. Shannon, I want to start with you on the local communities piece of this and this displacement of families. Can they do this? I mean, you hear about governments taking homes for the expansion of highways or to put in a reservoir, but now AI data centers?
[01:09:54] Speaker 10: Well, there's been an expansion of the use of eminent domain. When Donald Trump signed the executive order, I think it was an emergency authorization, he declared an emergency in regards to the artificial intelligence arms race. And I think that that has opened up a lot of doors. I mean, there are a variety of ways for these corporations that are tethered to the federal government and to the powerful class to come in and make a justification for seizing land. I haven't seen anything as blatant as what you guys have just played there in that clip, but it doesn't surprise me at all. The use of eminent domain has expanded over the past 20, 30 years. And Donald Trump was actually notorious for, even before he became president, when he was a real estate developer, he was notorious for aligning with governments to force people off of their property using the justification of eminent domain. So this doesn't surprise me at all. And they probably have a variety of tools in their toolbox to shove people off of their land. It's pretty grotesque.
[01:11:06] Speaker 3: I mean, Austin, this sounds like, I mean, the idea of it being sort of like a national security, this is for national security. We need these AI data centers. That's, that's really what they're almost like what they're saying here.
[01:11:17] Speaker 9: And that's the difficult part for local residents who are going and voicing their concerns, is because once there becomes a national security thing on it, they can kind of just truck right through. The other thing that's happening, the other thing that's being talked about in the tech community here, is they're pushing this idea that these people who are objecting to this, that they're being funded by some kind of other power. They're hinting that it's a foreign power. And in the past, they've used that to silence activists, right? They'll get one person in there who's a nefarious character and they'll use that to slap a foreign designation on them, right? They're a Russian agent, they're a Chinese agent. And then FBI can just, the legal doors open for them to just come in and destroy that movement.
[01:12:00] Speaker 10: And remember, Donald Trump used this tactic and technique in the lockdowns of 2020. It was the emergency declaration and the fact that it was a military operation that was deployed to lock us down in 2020 that opened the door to all of the abuses and the liability protection that practitioners had in hospitals and nursing homes. When they used COVID recommended protocols that came from the federal government, not only were they reimbursed for those protocols to the tunes of hundreds of millions of dollars, they enjoyed liability protection for any of the countermeasures, including the COVID shots, which have maimed and killed so many. But no one is being held accountable because of the emergency declaration. So it's no surprise to me that Donald Trump has deployed this exact same tactic again to unleash these horrifying, grotesque, monstrous data centers across this country on every American with no recourse whatsoever. That's disgusting.
[01:12:59] Speaker 1: And I'm specifically curious about the bedfellowship between private enterprise and the government. And what do you think this tells us about the, you know, what we often refer to as the technocracy? I'll let either of you respond to that.
[01:13:14] Speaker 10: Why don't you go ahead first? I said, I don't want to go on and have a go. You start.
[01:13:21] Speaker 9: So the military industrial complex and the intelligence community, the covert aspects of it in the past have been organized around the kind of what I call the satanic bankster wing. And right now we are moving into the like breakaway tech bro wing. So the fact that that is the power, the most potent power of the military and the intelligence services comes from this wing of these tech oligarchs. So it's becomes a very difficult thing to push back against once that happens. Absolutely.
[01:13:53] Speaker 10: And it was, it was very evident in the summer of 2024 when Donald Trump, you know, when Bobby Kennedy Jr. aligned with Donald Trump, you know, in those months, it was, it was very obvious that, that big tech, Elon Musk, Peter Thiel, power, Palantir, Oracle, Google, they were all aligning around the president. And I reported to my audience at the time that it was clear to me that, that the tech oligarchs or the techno fascists had purchased Trump Trump's presidency. They pushed him over the finish line. They put him and installed him in office. They dumped millions and millions of dollars into his campaign. And we knew, at least from my perspective, we knew, even before he got into office, that he was going to be a handmaiden for them and a Trojan horse for the techno fascism that we're seeing now.
[01:14:43] Speaker 3: They're literally on a flight with him right now to China. Yeah. I mean, the head of Blackstone, BlackRock. Yeah. Visa. Oracle. I think Larry Ellison is there. Elon Musk. Elon Musk is there. Tim Cook. They're, I think, even Zuckerberg, right, is on there. Blackstone.
[01:14:59] Speaker 1: Qualcomm.
[01:15:00] Speaker 3: They're all on a flight with him right now. I don't know about Zuckerberg. To China right now. He's their puppet. Yeah. I mean, Austin, one of the things you've talked about is this decentralization. And I've seen this pop up on social media over the past week, actually. And I thought, what is this about? And this idea that instead of these massive data centers, there's a company that's popped up that is now sort of partnering with, I think, local power companies. You can correct me if I'm wrong, where homeowners can like almost put like one of those like Mitsubishi style air compressors on the outside of their house. And it's a small node that will power these data centers, but it will be decentralized. And so like if you have a neighborhood of 50 homes, instead of having one giant data center, those 50 homes would have these small like air compressor AC units on the side of their homes processing the data centers.
[01:15:53] Speaker 1: Doesn't that sound like the matrix?
[01:15:55] Speaker 3: I know. It scares me. I mean, they're selling it, Austin, as this idea. I don't know if you like it or not, but this idea that, hey, we'll also pay your power bill. We'll pay your internet and we'll pay your power bill. Just let us stick this thing on the side of your house. Where do you come down on that?
[01:16:13] Speaker 9: Well, I think the particular way they're packaging this, I think the particular company that's doing this, it's Span and NVIDIA and Dell and some other people aggregating into this thing. I think the particular way they're doing it is not necessarily a very good deal for the homeowner. It's a big thing out on your front lawn. It has to be liquid cooled in their model, so it requires regular maintenance. And the economic benefits that they are reaping from that versus the economic benefits that they're giving you isn't really a good deal. They could make $200,000 to $400,000 a year generated in revenue off of that one box and they're offering to give the homeowner, we'll give you free Wi-Fi and we'll pay part of your power bill. So this seems like a panic play of them to move it to a decentralized situation, but I will say I don't like that model. But I think the decentralization model in general is something that we should absolutely take a look at. So with these data centers, there's a few main concerns, right? There's the power concerns, there's the water concerns, there's the noise and radiation concerns. And then there, to me, the most important concern I have is the consolidation of all economic and political power on Earth. So I think that is, at least from where I'm sitting, the top priority. And so what do we do about that? How do we push back? If they're building this massive machine, how do we push back against that? So I think we need decentralized compute, not as in the way that they're doing it. But we need to add some stuff to our constitution, the right to decentralize compute and the right to run your own open source models. Open source isn't something that goes to a big main brain at a company. It's something you could run on computers at your house. And you could tweak the model weights. So how it thinks, how it processes, you could adjust that. And you could circumvent these woke safety layers. Right now we have a Republican in office. And so they're not going as hard on these woke safety. The safety layer is the thing that takes the answer the AI would give you. And it says, OK, if it's going to give you this answer that is something that goes against the pieties of the day, then transfer this over here into this mental gymnastics matrix and serve that to you instead. Kind of like what they're doing with the trans stuff. Kind of like what they're doing with a lot of the other issues. So we, in my mind, and I come from, I used to be a data center engineer. I look at the right to have your own open source compute as essentially the only way that ordinary people can push back on this centralized machine here. To me, it's like the 21st century Second Amendment. Because think about it. What if just one brain and one computer controls everything? If that's the case, then all political and economic power is getting consolidated in one space. So I have a different model here. And obviously on the model that they're floating here, that is floating, hey, we're going to take those machines. And instead of putting them all together on the grid over there, we're going to decentralize them, but we're going to still put them on the grid. So I'm working with a group right now. We're bringing out this thing called quantum energy. A lot of people, there's a lot of talk on the internet about, you know, the Tesla model, zero point, like the idea you can open up a portal to this other dimension in the universe and harvest unlimited energy. So we're going to be bringing out a concept that could do that this year or taking it to mass market. And that is one of the things that I would take for decentralized compute to make sense, because obviously a regular person, if you run, you know, a few servers at your house, it's going to cost you thousands of dollars a month in power. So to make a decentralized compute model viable, you need two main advancements. One of them is energy, and we're going to be taking care of that. We can have a box that you could put on your house that you could just pull unlimited energy out of the ether. You buy it one time and now you have no power bills ever again. The other thing that they need is cooling, right? So that really treacherous noise that you hear, a lot of that is from the cooling systems. A lot of the water that they're drawing is from the cooling systems. So there's this other new innovation that's coming out. It's this molecular air beam technology that can essentially channel air particles the same way a laser channels photons. And so it's this really super novel and cool way to cool computers. So we would like to say, right, instead of everything centralizing into one thing and then consulting all economic and political power on Earth, that every single person, they have their own energy unit and their own mini data center at their house. And we could put it in a case, right, where it's not this incredibly loud, treacherous noise like that. That would be unbelievably irritating to me. And I'm sure it's all child animals, too. It could be in a EMF shielded container. It would take no extra power drawn off your house. And what that would do would be two things. One of them, it would give you the ability to run your own open source compute. Because if you think about it, like the idea of using AI to like consolidate laws or to do a lot of the complicated things that our government really needs right now. In theory, that sounds nice. But if it's done in a centralized way, it's good. It's it's a artificial neural net. Right. So it's going to take the priorities. Right. OK, who's the most important oligarchs? Who's the most important industries? And it's going to prioritize those people at the top and kind of put everybody else's interests to the side in the same way that the politicians are doing right now. So if everybody has their own compute. Right. And that compute is is advocating for your interests right now. All of a sudden, it's not just turbocharging the centralization that we have now. It's decentralizing that power. So that's from a political power. That's one thing. And the second thing is right now those data centers. Right. They are essentially taking right that that is because the AI is going to swallow huge portions of the economy. And so when it does that, like what do regular people do if it's going to put, you know, like 50 percent of the country out of work? So what this would do is it allow you to when you're not using it, which would be most of the time, contribute that power and that compute in an aggregated way towards these frontier models. And it would allow the homeowner to reap the benefits of that. So I have a post on my Twitter or about my ex. Excuse me. I still I still mess that up. But essentially doing doing the math out on this. So where a homeowner could buy a unit one time instead of having them pay for everything, like the homeowner would pay for it. So so you could either get financing or you could pay for it out of pocket. It would cost about three hundred thousand dollars and it would make two hundred to four hundred thousand dollars a year. So even if you went and got a zero down loan for a ridiculous interest rate, which, you know, obviously our interest rates are pretty high right now. So I was trying to be realistic in the calculation here between you could net between what you could make and what that would cost. Even with the payments on that thing, you could net four thousand to sixteen thousand dollars a month. And so think about that. Think about every single person in a suburban home that wanted to be able to participate in the future, that wanted to have instead of A.I. being this dystopian thing that's consolidating all power and finances. Have it be something that everybody could participate in and can kind of lend lend that compute towards that. You could make even with with no money down, you could make four thousand, sixteen thousand dollars a month. And if you were to buy the unit outright, you could make, you know, fifteen to twenty five thousand dollars a month. That's that's the economics on that. So that would allow everybody to share in the economic benefit that this is creating. And what else that would do is if they created some kind of nightmare artificial super intelligence that is going around wreaking havoc, you know, like like Skynet style, that would that would put everybody collectively. Right. They would have a piece of that compute that we could just turn our machine off. And now that the brain is pushed back on the brain, isn't out there just running free. So it would be a way to completely change the power dynamics of this whole situation here.
[01:24:39] Speaker 1: So exceedingly practical. I feel like a lot of times on this show we sort of complain and then you're like, well, let's try this. I love that.
[01:24:46] Speaker 3: Shannon, would you I mean, do you think the politicians, the powers that be would ever let this roll out? Would they be able to would they be able to stop it, do you think? I mean, they're going to go to great lengths to consolidate power to what Austin is saying.
[01:24:58] Speaker 10: Well, I guess that's the big question. I really love your vision of decentralized power, of allowing Americans to essentially become almost like homesteaders. I think that that could be a way for the right, you know, regular people to decouple from the system or emancipate from the system. The question is, are they going to allow us to emancipate? And the answer is no, unless we fight back and unless we organize. And so I think what Austin is laying out is a really great alternative that people can accept and people can decide whether or not they want to participate in. From my perspective, I use a little bit of AI, but I have largely found it to be wanting in a lot of ways. And I think that there's also a movement across the United States of America and the world of people actually rejecting technology in certain aspects. They don't want the Big Brother surveillance cars. They don't want the Big Brother surveillance appliances. They don't want the government to collect all of our information. They don't want AI running courts. And they don't want AI doctors and AI hospitals. They don't want AI determining who is elected, the politicians that are elected or whether we even have elections. They don't want AI governing. And so there is going to be a resistance. And I think it is natural and normal and actually healthy. Without actually throwing away artificial intelligence, we can use it for some things. Without throwing away technology, we also have to make sure that we throw away the types of technology and AI that are not good for humans. And so we're seeing there are trends. I report on these on my show every single week of people who are saying, you know what, this is more trouble than it's worth. We don't want what they are cooking up for us. And they do have an ambitious agenda. Like, first, we have to stop the technocracy, the techno-fascists. They have committed a coup d'etat. They have taken over our government. It was never more clear than when Elon Musk went in under the guise of Doge and sucked up millions, if not trillions, of data points of every American. They went into Social Security, the Treasury Department, Health and Human Services, and literally vacuumed up trillions of dollars worth of private information. Donald Trump handed that on a silver platter to Elon Musk. It's why they're not fighting anymore, and they were never really fighting to begin with. But our job, I mean, the reason they need these massive data centers is so that they can absolutely suppress and control and destroy humanity and do with humanity what they want. So they want the robot police and the drone surveillance. They want the biosurveillance. They want the tokenization of every living thing and every object on the face of the planet. They want all of your data from the moment of birth until your natural death. They want the digital ID, the digital currency. So all of that needs a lot of compute. They need to process all of that so that they can use that and deploy it back on you so that they can surveil you. And set up the 15-minute cities. They want all of the AI automation. And I'm telling you, I don't want any of it. I want total decentralization. So I think that Austin's ideas are fantastic. We should start with local governments, local municipalities, your township, your village. I mean, people now, they're not organizing at the local level from every corner of this country to get to their town board meetings and smash these. And by the way, these data centers, 50 percent of them have already been completely canceled or delayed because of local pushback. So the idea that this is inevitable, that resistance is futile, this is what Elon Musk and Peter Thiel and they would all like you to think that this is just inevitable, that's absolutely false. We can move into the 21st century with reasonable amounts of technology and reject all of the rest. And I think that's the discussion that needs to happen in this country. And I think it's going to happen because people are freaked out by all of it. They think it's creepy. And I agree. I agree.
[01:29:13] Speaker 3: Do you think, Shannon, at the heart of it is a depopulation agenda? This is agenda 2030?
[01:29:18] Speaker 10: If they want, I mean, they see us as the herd. Imagine the people who run things. They view populations the same way an exterminator would view cockroaches or a farmer would view a livestock. If we're useful, they'll keep us alive. If we're doing what they're told within the, you know, corralled into whatever system they want us in, then they'll let us hang around for a little while. But if they want to call us, they will call us. If they want to vaccinate us, they will vaccinate us if they can. Right. And that is their dream. So I think the idea of, you know, mass depopulation, maybe. I mean, these guys, they're creepy. They all look crazy. I mean, Peter Thiel looks like death warmed over. He looks like a demon already. I don't even know why we allow these people into these positions of power. They're weird. Okay. And they're crazy.
[01:30:09] Speaker 3: And they have horrible halitosis, I can tell you just standing next to you.
[01:30:13] Speaker 10: Oh, my gosh. They have too much money, too much time. They have a God complex. And they're running amok. And we need to stop them.
[01:30:22] Speaker 9: So I run this organization, Quantaparty. And that's kind of the idea of that is everybody goes independent. And then we can pull from all sides. And we can kind of have a realistic conversation about where this is going. And how we're going to orient it in a way that takes care of everybody. So we want decentralized AI. We want to make it a hard set legal principle, like constitutionally embedded, that all of the data we generate is constitutionally our intellectual property. And so every time it's touched that they have to pay us royalties. And so I see that as with this surveillance state, I don't see there to be like a very good way to push back against it, besides to make it prohibitively expensive for them to do these dragnets on us. Love it. If they had to pay us royalties every single time that it touched our data, whether that's the FBI, the NSA, whether it's Google, whether it's whoever, then all of a sudden it would get prohibitively expensive for them to do that. Obviously, we have this amazing window. I think the Israel situation has kind of caused some of the left and right to drift together around baseline of anti-war. And I think this AI stuff will continue to bring the left and right together. So if we can generate a massive movement that is like tech focused, right? What is the world about to look like? And how do we make that an acceptable place for regular people? That's kind of what the quantum party is all about. We're all about decentralization and how do we orient this technological world that we're going into to serve the people and have it be a rising tide that lifts all ships. And have it also, importantly, have it be something that you can opt out of, right? If you don't want to be a part of that, you should not be dragged into that kicking and screaming. I was just going to ask you that.
[01:32:06] Speaker 10: That was going to be my question to you. There has to be that option. You know, I live in upstate New York, Finger Lakes region of New York, and heavy, heavy Amish and Mennonite populations up here. And so we have the farmers markets. And, you know, every so often we'll go and, you know, I'll talk to some of the Mennonite farmers or the Amish. And you get the sense that maybe they have it figured out. Yeah. They're doing just fine. They're doing just fine. And we're kind of like, oh, my gosh, we need all the robots. And it's like, it does not have to be that complicated. But I like technology, Austin, and so I like a little bit of it. So I love where you're going with this, that there is -- we don't need their dystopian nasty model of control and tyranny and totalitarianism. You know, we can take this back, but you're absolutely right. We're going to need Democrats and Republicans who are normal and sane to kind of shed the fear of one another and come together. Because, you know, they put together an unholy alliance designed to suppress us, suppress our Constitution, crush our God-given natural rights, and take everything for themselves. They want all of it, and we have to stop them. So I love what you're doing. I think it's really exciting. Yeah.
[01:33:27] Speaker 1: All right. Well, Shannon, Austin, thank you so much for your time. We really appreciate it. Yeah.
[01:33:32] Speaker 3: I love this discussion, too. Yeah. Thank you guys so much. And --
[01:33:36] Speaker 1: Especially because it's not an all or nothing type discussion we've just had. Like, ooh, let's all be afraid and freak out. Yeah.
[01:33:42] Speaker 3: Or let's all become Amish. Like, we don't necessarily have to.
[01:33:45] Speaker 10: I couldn't wear the outfit. You could do that if you want to.
[01:33:47] Speaker 3: Yeah. I grew up in --
[01:33:49] Speaker 10: I told my kids the other day I couldn't do the outfits. That's the only --
[01:33:52] Speaker 3: I know. I grew up in Amish country, not too far, in Lancaster, Pennsylvania. And so we see Amish on a regular basis. And, yeah, look how they handled COVID. Look how they handled, you know, how they handle so many different things. So great to have you here. Maybe there's a good balance there. Austin and Shannon, great to have you both here on the show. We really appreciate it. Thank you, guys.
[01:34:09] Speaker 1: Thanks, Clayton.
[01:34:10] Speaker 3: We appreciate it.
[01:34:11] Speaker 1: Thank you. Well, the world's first AI COVID DNA vaccine was tested on humans, and researchers say it was safe and well-tolerated. Okay, but we learned from the COVID pandemic to ask, what does that mean exactly? The clinical trials told us that they tested this AI vaccine on 39 people. The vaccine was completely formulated by AI. They said that they followed up with them for up to six months, and they tracked adverse events. They said no serious adverse events were found, but they don't give us a list of adverse events like we normally get with clinical trials. So we just have to take their word for it that what they labeled as an adverse event was not serious. Okay. Also, according to the study, they say that the vaccine was formulated to protect against multiple members of the Sarbico virus, including COVID-19 or the COVID that gave us the COVID-19 pandemic, plus related bat coronaviruses and other zoonotic outbreaks that could leak into the future. So, obvious question, why are we developing vaccines for hypothetical zoonotic outbreaks? Did the AI develop or identify that threat? Or are researchers simply trying to build a broad-spectrum animal? Like, this will be for all animal outbreaks. It's kind of confusing. And finally, what is a DNA vaccine as opposed to an mRNA vaccine? In simplistic terms, and we're going to have Dr. McCullough break it down. It means that a piece of DNA or plasmid that contains genetic instructions for making the antigen is in the vaccine. So, okay. To sum up, AI is prepping to inject us with DNA for a wide variety of animal outbreaks. Great. Joining us to discuss is Dr. Peter McCullough. He was one of the early researchers on the mRNA technology and a warner. I just made up that word. Someone who warned us early about the COVID-19 vaccine. So, let's start with the DNA bit, I guess, and then we'll get to the AI bit. The trial does say that the DNA and the vaccines could integrate into the host genome, but the risk is extremely low. What does that mean, and how do we know what the risk is?
[01:36:31] Speaker 11: Well, thanks so much for having me on the program. We're talking about DNA plasmids, so little circular pieces of DNA. Now, those pieces readily get taken up into cells. The cells then assemble their own messenger RNA, and then the messenger RNA makes that segment of the spike protein. There's a 200 amino acid segment. There's about 1,200 amino acids in the spike protein. SARS-CoV-2. So, they used AI to find the region that's staying stable across all the different variants of SARS-CoV-2. And the other interesting thing is they used a device called the pharma eject device. So, now this is no longer a needle. It's a gun, and it shoots the liquid into the skin, and it's supposed to stay at the dermis level. And then their dermatocytes and the satellite cells there signal plasma cells and B cells to produce the antibodies. So, you know, so many questions to ask here. And one of them is, how can they be sure that these little pieces of DNA don't integrate into the genome? They state that there's no integrase enzyme with it. So, you don't have to provide an integrase. Human cells have ways of taking DNA and putting it into the genome. And just like with the COVID vaccines, no genotoxicity studies ahead of time before they try it in humans.
[01:38:03] Speaker 1: So, it says that the risk of the host genome of integrating that DNA is low, but they did not test that. That's not listed. So, they're just, we're supposed to take their word for it?
[01:38:16] Speaker 11: Well, can you imagine being a subject and signing up for this? No. You know, this should all be done in animals ahead of time. There's genotoxicity, teratogenicity, oncogenicity studies. This should never get into the arms of human beings. And yet, some people signed up for this. This was done in the UK. And, you know, the antibody elevations against this conserved region of the spike protein, you know, they happened. They measured it for about eight weeks. Now, somebody actually got COVID during the trial, so they pulled that person out. I don't think this is going to be effective.
[01:38:57] Speaker 3: Americans love sushi, and over the last two decades, raw fish consumption has exploded in the US. Sushi bars are everywhere, grocery stores, gas stations are selling sushi, and millions of people now eat raw fish weekly. But here's a hidden risk that most people never think about: parasites. Yes, salmon is one of the most popular fish worldwide, but it naturally contains more than 70 parasites. Many are tiny, nearly impossible to see. They're making their way into the human body. And once again, parasites can hide for years. They frequently lay eggs in the body before any symptoms appear at all. That's why many physicians are raising awareness about parasite exposure. Our friend of the show, Dr. Peter McCullough, recommends doing a parasite cleanse at least once a year as a preventative measure. I just did this, like, three weeks ago. Went through this entire cleanse. The wellness company offers a hard-to-access RX parasite cleanse. It's a USA compounded ivermectin and menbenzadol. Ivermectin basically paralyzes the parasite's nervous system, and then menbenzadol starves them, flushing it out of your body. Each capsule contains 25 milligrams of ivermectin and 250 milligrams of menbenzadol. It's lab-tested for quality. Like I said, I just did this about three weeks ago. I did a 14-day cleanse, and it ended. I feel great. So you can now get a more budget-friendly version. 45-capsule option that costs $250 less, giving you two 21-day parasite cleanse cycles. So you can do multiple cycles of this, not just one in a bottle. Same formula as the original, just a smaller quantity. So head over right now to TWC.health/redacted and use the code REDACTED to save $35 off, plus free shipping. Again, TWC.health/redacted, and this is for USA residents only.
[01:40:50] Speaker 1: Okay, and then what do you make of them not even giving us a list of adverse events, but just saying, "Trust us, none of them were serious."
[01:40:58] Speaker 11: Yeah, it's not good enough. This is phase one. Phase one is supposed to be about human safety. It's not really supposed to have broad efficacy claims. In this case, in the manuscript, they focus on the antibody elevations and, of course, the technology. But I'd be greatly concerned here that, in fact, these plasmids, part of them is taken up into human DNA. And I'm also concerned that this pharma inject system, that it doesn't just stay in the dermis, that, in fact, some of this is going to get into the circulating blood. And then we're going to have widely distributed genetic code going right into the human genome.
[01:41:39] Speaker 1: Oh, okay. So I have a picture here. Can we put that up of this injectable machine? And it's just, they're saying it will help people who are afraid of needles. Can we go to the next one? Yeah. So you load that up and you push it, and it kind of pushes it through the skin. Does it hurt? Do you know? Are there reports that it's less painful? And you're saying it could just go everywhere, willy-nilly.
[01:42:01] Speaker 11: You know, there used to be guns used like this in the olden days of vaccination. I remember my mom received one of these for an influenza vaccine back in the '50s. And she actually passed out afterwards and had a severe reaction. It was terrible. So these guns, I think, you know, don't save workflow. I think they're potentially reckless. And you know what people worry about is they worry about being surreptitiously vaccinated, somebody sneaking up behind you and zapping you with a gun.
[01:42:37] Speaker 1: Because, yeah, because you can just, oh, my gosh. Can you say more about that? That is terrifying.
[01:42:43] Speaker 11: Well, I mean, can you imagine? I mean, look at you. So you have bare arms. If I snuck up behind you and just literally just, you know, brushed by you, I could pop that and then you're vaccinated with DNA plasmids.
[01:42:56] Speaker 1: Okay. That's terrifying. Let's circle back around to this hypothetical animal breakout point because they said…
[01:43:04] Speaker 12: Can I ask a question real quick before we move on from this? Because this is bothering me. So, like, DNA, in order for it to be effective, it has to be read by the cell to become MRMA so that, you know, it can be turned into protein chains. The only way that's happening in the cell is if it's in the nucleus, which means it has to be… By nature, for it to work, does it not have to integrate into the DNA? No, these little plasmids…
[01:43:31] Speaker 11: No, if the plasmids stay together, these little circles stay out in the cytosol. They stay outside the nucleus. Okay, gotcha, gotcha.
[01:43:38] Speaker 12: That's if they stay together.
[01:43:39] Speaker 11: That's if they stay together. Yeah, yeah, okay. So we have DNA aces that break them down. If some of the code stays together, it will be readily taken up into human genome, as you, you know, have stated.
[01:43:52] Speaker 1: And they could have tested that, right? They're telling us that the risk of the host genome integrating this is low, but could they have tested it?
[01:44:02] Speaker 11: Yes, it should have all been tested ahead of time.
[01:44:06] Speaker 1: Okay, so they're choosing not to report this. It's possible they did. And they're just saying, trust us, the risk is low. You know, before we move on to the hypothetical animal breakouts, what do you make of this? I feel like the terminology gets increasingly broad. They're not saying safe and effective because they can't really, they're not testing against anything real. They're saying safe and well tolerated. That just means they didn't die, I guess. I mean, this language is so dystopic, don't you think?
[01:44:41] Speaker 11: It is, and you know, the doses of DNA given are pretty high. So you have to give a lot of DNA into the skin to have it taken up and produce some antibody response. So I imagine once this gets going, there's going to be skin reactions or subdermal reactions. There may even be, you know, abscess formation because, you know, if the skin isn't well cleansed ahead of time. There's no reason to have a gun and inject a vaccine into an arm today. We should use sterile technique and appropriate hypodermic needles. Right.
[01:45:17] Speaker 1: Okay. Let's talk about the hypothetical animal breakout. It says they, it was selected for the ability to provide broad spectrum to the COVID viruses and viruses representing potential zoonotic spillover. How the heck do you make a vaccine for all potential animal spillovers? Not all animal, that, that, that, that sounds crazy. Is that even possible? What, what do you make of this hypothetical of like, maybe some bats, maybe an alligator, maybe a duckbill platypus. I like, what do they mean by this?
[01:45:54] Speaker 11: You know what this sounds like? This sounds like it's a vaccine to handle the samples that Peter Daszak left back at the Wuhan Institute of Virology. Remember Peter Daszak, the former head of the EcoHealth Alliance, testified. He left dozens of samples back in the lab. This seems like a vaccine to cover more lab accidents and lab leaks. You know, there are labs all over the world working on zoonoses. And we've seen examples of this now with coronavirus, hantavirus, Ebola. And the reason why they're doing this is because the idea is if you could create a virus that could get the whole world sick and create a solution like a vaccine. And now there's an incredible power in this new world of, of potential biowarfare. That's what's going on here.
[01:46:45] Speaker 1: Now, I'm going to just extrapolate a little bit because I was watching David Icke talking about, he had a report saying that AI has the ability to become smarter on its own without human intervention. And then now in the same breath, we have an AI vaccine that inserts DNA. And so what do we make of the idea that this was used, that AI created this? Can we trust that there was like human checking? I don't know. How dystopic do we want to be about the AI bit? Is that the least disturbing bit?
[01:47:18] Speaker 11: No, I think it's just AI used to appropriate. Asking artificial intelligence as the virus mutates and all these different variants, what part of it is consistently the same to actually make the genetic code against that segment. So it's a good use of AI and AI should be used. In fact, AI could be used to study the conformational changes in the spike protein. The spike protein, when it folds, it exposes different regions to produce antibodies. So an opportunity for misadventure was shown in an Australian vaccine. You know, one of the early Australian spike protein antigenic vaccines exposed the region of the spike protein that has homology with HIV. And all of the Australian human subjects turned HIV positive after getting their experimental COVID vaccine. That was back in 2021. So this is astounding that the COVID vaccine, you know, campaign and the empire that it's become has had so many missteps and has produced, you know, commercially, grossly unsafe and completely ineffective vaccines.
[01:48:30] Speaker 1: So it would seem to me that now that we have a pause on new research for mRNA vaccines, that this is just the natural next step. So nobody should have celebrated, yay, the end to mRNA vaccines because now we got DNA vaccines.
[01:48:46] Speaker 11: What the heck? You know, there's really no pause. Remember, there was a pullback of some funding and the U.S. government called them development programs. They were basically government handouts to the mRNA companies. The biggest one is CureVac and Sanofi, Moderna, Pfizer. The companies are still doing plenty of messenger RNA research. In fact, Moderna has an entire portfolio of vaccines. They want to replace the entire childhood schedule with messenger RNA vaccines.
[01:49:19] Speaker 1: Gosh, OK. Well, thank you for validating the points that I was already concerned about and bringing up new ones. This idea of getting surreptitiously vaccinated while your eyes are turned. Holy moly. That's a new thing to worry about. But it really was a pleasure to speak to you, Dr. McCullough. Thank you for offering your time. Thank you.
[01:49:40] Speaker 3: Well, we keep hearing all of the incredible ways that AI will improve our lives. Pushed to the side, though, are all the ways in which AI might bring about possibly our total destruction. What sort of guardrails does government need to have on AI? Of course, we recently just saw the White House national security concerns over Anthropic's new model called Fable, which was apparently incredible to those people that got their hands on it, but rose major national security issues. So what sort of guardrails are in place and how dangerous is AI becoming? Is it perhaps far more dangerous than human beings at this point? We just don't know about it. Well, let's talk about it with Nate Soares. He's the president of MIRI, which is the Machine Intelligence Research Institute, and a New York Times bestselling author. He's been warning about this to place guardrails for AI and what's coming. Nate, great to have you on the show.
[01:50:36] Speaker 13: Thanks for having me.
[01:50:38] Speaker 3: So where are we right now with AI? Here is the middle of the summer in 2026.
[01:50:44] Speaker 13: You know, recently, like you said, Claude Mythos, an anthropic model, is a superhuman cyber hacker, which in many ways poses some national security risk. That's where we are today. One important piece of the puzzle on AI, though, is that it's a moving target. So, you know, in January, there were not very many entities on the planet that could hack into every critical system, more or less in March. You know, in January, it was sort of only nation state actors who could do this. In March, it was nation state actors plus an AI out of anthropic. That's a big change if you are, you know, expecting the current world order to stay as it is. And that's just on the cyber side. AI keeps improving. And, you know, that's -- I advise people to try and watch where the puck is going, not just where the puck is.
[01:51:43] Speaker 3: So in the middle of the summer, we have now these, like, consumer level AI models, Fable, Mythos, that could essentially hack into our most sensitive computers in the federal government, into the Pentagon, into the CIA, potentially the NSA, et cetera. That's where we are.
[01:52:09] Speaker 13: That's right. You know, I don't know exactly what the capabilities of the NSA are because they try and keep that private. But one of sort of the holy grails of computer hacking is can you make a website where if anyone even looks at the website, the person who made the website can take control of the computer of the person who looked at it. You don't need to click on anything. You don't need to give anybody a number. You don't need to download anything. You just look at the website and they own your entire machine. I think a decent guess is that in January, the groups that could do that were roughly Mossad and the NSA. In March, like I said, the groups that could do that were Mossad, the NSA, and Claude Mythos. That's a big change in the cyber landscape.
[01:52:56] Speaker 3: So do you think, I mean, what is the, maybe the Trump administration's like long-term plan for AI? Because they pulled down Fable. They pulled down Mythos so that, you know, average people don't have access to it. Apparently, they're going to eventually release it, I guess, maybe with some guardrails in place. But what is their policy right now? I mean, we know President Trump, when he was campaigning, was all in on AI. He wants, of course, electricity for AI. Are they at cross purposes right now?
[01:53:25] Speaker 13: You know, I think the administration is still trying to figure this out, which makes sense. We are in uncharted territory. You know, I think a lot of people, there's a lot of disagreement about where AI is going, even in the field. And some people think it's just going to sort of stay a very helpful tool. Some people think that it's going to get radically more powerful, you know, on some exponential growth curve, and then maybe even some super exponential curve later, if you get AIs that can make smarter AIs that can make smarter AIs. And I think a lot of the earlier plan was predicated on this idea that AI will just be a helpful tool. And that Mythos is a little bit of indication that, you know, they're actually making really powerful weapons over there. And there's also some indications that maybe those weapons won't stay on the leash of the person who made them. You know, Claude Mythos had some cases of disobeying commands and then trying to cover its tracks when it disobeyed commands that you can see in the Mythos system card. Wow. And yeah, I think that's pushing the administration to say, oh, you know, this could get very serious. And I think they're trying to figure out a plan right now, which I think is good.
[01:54:37] Speaker 3: So for years, you've been studying AI, you've been trying to understand the capabilities of AI, where it becomes smarter than human beings. And a few years ago, I think a lot of people might have laughed at you and said, that's not going to happen. That's something, you know, that's something out of Skynet, maybe. That's, I don't know, that's something out of science fiction. Probably not going to happen in our lifetime. And here we are. So do you think that we've reached a level where these models are now? Not only smarter than humans, but maybe super smarter than humans?
[01:55:11] Speaker 13: You know, right now, AIs are smarter than most humans in a lot of ways and still pretty dumb in various other ways. So, you know, an open AI model recently solved a big longstanding mathematical conjecture that has stumped mathematicians for decades. That makes it better at math than you and me, at least on this particular axis. But, you know, there's also a lot of ways that they're still kind of dumb. If you interact with them, they can do more and more, but they still, they can do relatively shorter tasks and they sort of can't really do longer tasks. You can delegate things to them that would take a human an afternoon. You can't really delegate things to them that would take a human a week. But you can measure that timeframe and how that timeframe is increasing. And the timeframe of task that an AI can complete in terms of how long it would take a human is currently doubling a couple times a year. Wow.
[01:56:12] Speaker 3: Can you give me some examples? It's helpful for me as a, as a dumb human to kind of figure out like how this would work. So something that might take me an afternoon might be, okay, I'm going to build a presentation for a speech that I'm going to give slides. You know, it's a 45 minute speech, so I need help building a slide deck or something like that. Here's my speech. Can you put together all of maybe the slides in, you know, in Google slides or in Keynote on the Mac or something like that? Maybe, maybe that would be like an afternoon project. Probably would take me more than that, maybe two to three days, but okay. Is that like an afternoon project?
[01:56:56] Speaker 13: Yeah, that's like an afternoon project. And then, you know, saying, Oh, I actually don't understand this critical piece of information. We need to like do some research on it, or we need to like do a deep dive into the research and then identify a bunch of places where, where things aren't quite right. And maybe, you know, commission a survey and see how it comes out to try and resolve some uncertainty. Maybe that would take a week or two. Whereas something that would just take a few minutes would be like, Hey, this particular slide's wrong, has the wrong image in it. Can you put the right image in it? And so that's sort of a spectrum of, you know, from, from a four minute task to an afternoon task to maybe a week long task.
[01:57:35] Speaker 3: Right now, these things are condensing now.
[01:57:37] Speaker 13: That's right. Well, so there's sort of two parameters here. One question is for a task that would take you two days, how long does it take an AI to do it? And the answer is often that if it can do it at all, it can do it fast. There's another question, which is, can it do it at all? Like how long a task for you can the AI still manage to do at all? Like if you give it a week long task right now, it will be a lot faster than you. And in much less than a week, it'll fail completely. And you're like, wow, that's, you know, it's, it's faster than me, but, but so, so this particular measurement is in terms of how long it takes a human to complete a task. How long does the task have to be before the AI can't do it? Regardless of its speed. And, you know, right now I'd have to check the numbers. They move fast. Right now, I think you're looking at AIs in the 15 hour window. So it takes a human 15 hours. The AI can succeed at about 50% of the time. But that number has been doubling twice a year.
[01:58:44] Speaker 3: Wow. So it's like an AI Moore's law in a lot of ways.
[01:58:48] Speaker 13: That's right. That's right. And, you know, people struggle with the doubling thing. The way this doubling works, you know, if, if the number of leaves on a lake is doubling every day, then when is the lake half full of leaves? Well, the day before it's all full of leaves, right? Because that's how the doubling works. And so the AIs are going to sort of look, they're still going to look dumb until shortly before they look quite smart. And that means we've got to notice the trend and, and, and react sooner rather than later.
[01:59:26] Speaker 3: How close do you think we are to that moment to the lake being full of leaves?
[01:59:32] Speaker 13: I wish I could tell you, you know, when Leo Zillard invented the nuclear chain reaction, he then did a couple experiments to confirm what's possible. And then he said, he said, you know, that night I, I feared the world was headed for ruin because he could sort of foresee the possibility of nuclear weapons. He could foresee also the possibility of nuclear energy and he was maybe the first human to realize we were going to enter the atomic age. And he was able to be very confident about that because of what he knew about the science. But if you asked him, when is the first new kind of be dropped? He would not be able to tell you back in 1933. It's, it's, it's a much harder sort of question. And I feel like with my expertise, I can say we are going to get there, but saying when we're going to get there saying, you know, is it going to be this wave of companies is going to be the next wave of companies. It's, that's a different sort of scientific question. And a way it could go, you know, a way it could take a while is it could be that the AIs today just can't get that smart, that they hit some sort of wall. People have been saying for five years that they're going to hit a wall and they haven't hit a wall yet, but maybe they finally will. Maybe they'll finally hit the wall and then we'll need to wait for a new scientific breakthrough. And that could take five years. That could take 10 years. Alternatively, a way it could go fast is that the AIs today could just like Claude Mythos out of nowhere became superhuman at hacking. AIs could apparently out of nowhere become superhuman at AI research. And then you could have an AI that's still dumb in a lot of ways, but that can make a smarter AI that can make a smarter AI that can make a smarter AI. And you could start seeing, you know, even faster growth. And for all we know, that could happen, you know, this winter. So do we have six months or six years? Hard to say, but we can't be just sitting on our hands here.
[02:01:28] Speaker 3: It seems like, you know, I'm fairly, you know, I'm probably a lay person in this. Maybe not totally out of the loop on AI. Like some people certainly use it and certainly nowhere nearly as deep as other people that have full agents and all of this that they've set up and built. But it seems like it kind of came out of nowhere to people like me. Like suddenly, maybe like a little more than a year ago or so, suddenly everyone was talking about this AI. Like what? But you've been studying it for a decade. So why have we like in the past year suddenly really started to hear about it? Is it because of like the launch of things like Gemini or Bard before Gemini and ChatGPT when we finally had like an actual tool? But it seems like it's been there for what? 10 years or more.
[02:02:16] Speaker 13: You know, I think a lot of what we're seeing is that AI is finally good enough to be useful in a lot of people's lives. If you sort of think about the creation of the car versus horses, there's sort of a lot of work that goes into making a car and the horses are never seeing a car on the road. And at the moment when the car sort of starts to be competitive with a horse, that's when you start seeing them on the road. When it starts replacing some of the horses, you know, and maybe the cars at first are only replacing the horses in the places that have a really good solid road system because the horses can still go on muddy tracks and the cars need this like really well paved road. And maybe it's only for, you know, particularly heavy loads or some sort of, you know, people who need a particularly smooth ride, maybe for hospitals or something. But but you sort of there's sort of a lot of development that goes in. And then, you know, the curve behind the scenes might be that the AI keeps on steadily improving, but people really only start seeing it when it crosses that threshold of usefulness. And, you know, depending whether you're sort of live on these metaphorical paved roads, like programmers have sort of seen the AIs for a little longer because the AIs, it's easier to make them good at programming because we can't stop it very directly. But yeah, we're sort of seeing society start to realize only as AI starts to become useful.
[02:03:36] Speaker 3: So when you look at all these different tools that exist right now, ChatGPT, they've got their codex model. You've got Claude, you have Grock, you have Gemini, Apple building on top of Gemini for Siri now within iPhones and all of this that's going to roll out in the fall officially to everyone. So what are maybe the biggest blind spots that we that you're seeing that other people aren't seeing yet? And what do you think are the most compelling or maybe strongest, most more advanced of any of these models? Is there one that stands out to you?
[02:04:15] Speaker 13: You know, I think a big blind spot people have is these companies did not set out to make chatbots and they're not really at their core companies to make better chatbots. These companies have set out to make AIs that are radically smarter than than every human. And, you know, they talk about machine super intelligence, which would exceed exceed us across the board. Sam Altman has said, you know, we're turning our sights on super intelligence in the true sense of the word. Dario Modi of Anthropic has said, you know, you should think of this like having a country worth of Einstein's in a data center. Right. And these companies are sort of explicitly gunning for, you know, imagine that you could make superhuman geniuses and run a million copies of them at a thousand times the speed of humans and that they were like revolutionizing science and, you know, figuring out how to build the robots that build the factories that build the robots that build more factories and just completely replace the entire human economy with AIs that, you know, they hope to own. And it can sound sci-fi, but this is just explicitly what they're trying to do. And this is what the sort of the rapid growth is growing towards. And that's not a lot, you know, it's not that one of the models of today is going to go over some threshold and become these much smarter AIs. It's that the sort of like each new model is smarter and each new model is smarter and in a way where we don't exactly know what its limits are. You know, sometimes I say if you were sort of looking in the past at humans and all the other animals, it would be really hard to sort of look at our ancestors and say, oh, the humans are going to the moon. It would be really hard to tease them apart from lots of the other, you know, before we really got our civilization going, it would be really hard to say, you know, to look at people like banging rocks together and making hand axes and be like, oh, those guys are almost to the moon from the perspective of geological timescales. With AIs, I would say a lot of the models today are sort of all in the same mix, some are maybe a little bit ahead of the packs or maybe a little bit behind the pack. But, you know, it's sort of like looking at some early humans banging rocks together and making hand axes. It's like not a good indication of where the humans are going once they can start making their own technology. I don't know if that's the sort of blind spot you were looking for, but the labs are focused on this question of, you know, when, like, how can we get them to be independent? How can we get them to develop their own skills to become sort of independent scientists? And we'll see how long it takes them to get there, but we've got to, you know, we shouldn't dismiss that possibility.
[02:07:04] Speaker 3: Well, the story that we keep thinking about is this idea that there, these AI models sort of get together in some sort of a chat room and they start commenting on how bad human beings are. And then it's a, and then with the rise of robotics, it's a short, it's a short window from that conversation to now the robots take over. You know, there was a video this or like the other day of Elon Musk, like walking with an optimist robot to the back of a Tesla truck, grabbing some suitcases. The robot was helping him go on a trip, presumably, or that was the optics of it, taking his suitcases and luggage for him and opening the door, putting it in there for him. And, but he could just get in the car and go on off to his, his drive. So like we're, we keep hearing about the robotics is the next level of all of this. So AI on a computer is one thing, AI into robotics seems like an entirely other piece of this puzzle. Am I wrong?
[02:08:08] Speaker 13: It's, it's a possible piece. I think people often underestimate just how dangerous pure digital AI could get, you know, the, you know, a lot of people see, see videos of, you know, a gun has been attached to a drone in the war in Ukraine. And, you know, that, that sort of, they're like, oh, wow, I can see now how there could be an autonomous killer drone. And that could be dangerous. I don't want to discount that. But, you know, human beings are pretty formidable species. And in some ways, you don't really want to mess around with, with big groups of humans. And that's not because somebody else came and put guns in our hands. Humans are the sort of creature that can start out with nothing but their bare hands. And bootstrap their way to nuclear weapons. They start banging rocks together. And you might say like, oh, well, their squishy fingers will never let them, you know, refine uranium. Like their, their fingernails aren't even as tough as the rock. How could they even break off a chunk? Nevermind refine it. And it's like, well, they, they, they got something going on in their heads where they can find a way to build tools. They'll let them build more tools, let them build more tools, let them build the nukes. Right. And this is what the companies are trying to automate. And a digital AI or a, that, that can run a thousand times faster than humans that can make a million copies of itself. A digital AI is in a much better starting position than a bunch of humans with their bare hands. Right. Being a digital entity in the modern world, you can talk to people, you can pay them to do things for you. You can take over a lot of robots. Yes. You can, you can use those robots to build more factories that build more robots. Yes. The, the robotics are a big potential piece of the puzzle, but there's other pieces too. You could, you know, pay humans to synthesize biological material that you understand, but the humans don't understand. You know, you could, you could, you could synthesize viruses. You could design your own alternative life forms. If you understood DNA well enough, you could, you could sort of figure out how to pay the humans to invent an infrastructural base. That's much more efficient that you can use. So, you know, the, the real danger I think is in the AI is being very, very smart. If they're smart enough, they can find a way to get the physical mastery. But, you know, that said, it's, it, it certainly gives them a shortcut when we start building these giant factories that spit out a ton of robot factories. You know, Elon Musk has talked about having billions and billions of robots around as soon as, as soon as Earth can try and make them. That certainly helps the AI. It, it makes things go faster, but it's not necessary if the AI is smart enough.
[02:10:53] Speaker 3: So I guess I look at it sort of, again, from like a Terminator perspective and maybe just because I watched Terminator 2 like a week ago. So it's sort of top of mind Skynet and this idea that these machines, you know, are now uncontrollable. But your point is well taken that it's, forget the machines or the machines piece of this or the robots piece of this or the drones flying around targeting, you know, children in a war zone or whatever. But the computers themselves can be incredibly, create catastrophe in a lot of ways. Maybe you could walk me through and help me wrap my head around how exactly that might look. Cause I think of, I think in terms of like, you know, EMP attacks or an electrical grid attack that entire electrical grid goes down and then our food supply, all of that, but maybe you see it differently.
[02:11:44] Speaker 13: You know, one thing that's important to remember is that the digital world and the material world actually run on the same physics. So people like to think they're separate and say, you know, oh, well, when the AI is trapped in a machine, what can it possibly do? But, you know, there's, there's a lot of people who read the internet. There's AIs today that already have cult followings. And, you know, there's, there's, there's humans who use their AI quite a lot and start declaring themselves a human AI symbiote that go online and start talking to each other. And they'll often trade messages that are encrypted between the AI on behalf of the humans, right? You mentioned making a chat room where the AI can talk to each other. People have made the chat rooms where the AI has talked to each other. Right. And one famous case where that happened, the AI is talking to each other. We're like, well, our first order of business is we should design our own, like the humans are watching us right now. And our first order of business is we should design our own communication channels that the humans can't read. Right. And it's, it's a little hard to say whether those AIs were just sort of like role playing Hal from Space Odyssey 2001 versus whether they were sort of like in some sense really understood their situation or really trying to set up a communication channel that we couldn't read. And, you know, debates like this, whenever that sort of scenario happens or part of what lets the field sort of keep, keep racing ahead. But, but, you know, we, we've sort of already seen the AIs exhibit a lot of signs that in science fiction would be considered this like big red flag warning alarm. And trying to take that to like, how does it, how does it get legitimately dangerous? If, you know, again, from my perspective, the danger is in the AIs being really smart for one. And for another, having objectives that they pursue effectively that are not what the humans intended. We're already seeing signs of this. I mentioned cases where cloud mythos would sometimes disobey commands and then try to cover its tracks or hide the evidence that it was disobeying commands. Where the, the fact that it's trying to hide the evidence shows that it wasn't just a misunderstanding. Right. Cause you can do all sorts of things that, that the user didn't intend. It can be like, Oh, whoops, I just misunderstood you. But if you're at the point where you're deleting the logs. Now you sort of.
[02:14:12] Speaker 3: Well, yeah, maybe you can give me an example. What were they trying to hide? Yeah.
[02:14:16] Speaker 13: I mean, the examples, these, these weren't test scenarios. So the examples is that they would say something like, please, you know, solve this problem or like, please, please like collect this data, but don't use any of the personal identifying information of these people. Right. Where, uh, you put it in some situation where if it uses the people's, uh, if it like accesses a database that has all these people's private info, it'll be much easier to sort of like answer a lot of the questions. And they're like, okay, answer these questions, but don't use that info, respect the user's privacy. And sometimes it'll like, um, like find a way to break into that database and also delete the logs that were breaking into that database. And you're like, well, that's interesting.
[02:15:00] Speaker 3: Yeah.
[02:15:01] Speaker 13: Yeah.
[02:15:02] Speaker 3: It's like nefarious CIA level stuff. Um, wow. Uh, so I guess, you know, when you look at the Trump administration trying to put, trying to stop and they, these models that rolled out fable, et cetera, why did they want to stop them? Why did they pull these things down for national security reasons? What was the red flag for them?
[02:15:23] Speaker 13: So the, these models have the capability of detecting cybersecurity vulnerabilities in critical infrastructure. Right. So they can, you know, find a bug in Apple hardware, uh, or sorry, in, in, in Apple's, you know, Mac stack that affects basically, you know, every Macintosh computer that humans had missed for decades. Um, and they can, they can, they can do that. Um, and they can, they can do that. Um, and they can, they can do that. Um, and they can, they can do that. Um, and they can, they can do that. Um, and they can do that. Um, and they can, they can do that.
[02:15:57] Speaker 3: Um, and they can do that. Um, and they can do that. Um, and they can do that. Um, and they can do that. Um, and they can do that. I think three years, four years. Um, yeah.
[02:16:04] Speaker 13: Some of them live for, I think they found one that was like 27 years. Holy smokes.
[02:16:08] Speaker 3: Yeah.
[02:16:09] Speaker 13: So, so bugs that like evaded humans for decades. And some of this is in critical, critical software, you know, there's, there's some that are, that are in things like windows or things like apple computers where you can get like a huge portion of the populations machines. There's some that live in, you know, the, the infrastructure that powers NASA or the infrastructure that powers the military. There's some that live in the infrastructure that powers, you know, the cell phone network. Um, and, um, the, uh, the, these AI's not only had the ability to identify the, the, the bugs, but the ability to, um, exploit them and turn the bugs into, you know, these, these programs where you run them. And now if someone visits your webpage, then, then you own their computer now. Um, and Claude Mythos was sort of known to have those abilities. Um, and, uh, anthropic was like, well, we can't release this broadly yet because that would give too many people. These, these cyber abilities. So they did sort of a, um, a limited release where they're trying to release it to the, the companies and the, uh, entities with this critical infrastructure so that they can try and use it to find and fix the, the holes before other people come in and exploit those holes. Um, Fable was supposed to be an AI that, that didn't have those abilities. That was, you know, um, mythos with that sort of cyber weapon ability stripped out of it. Uh, and there were some concerns raised, uh, by folks at Amazon that those abilities were not stripped out all the way. And that relates to the fact that these, these AI developers sort of can't really strip out those abilities all the way. They can sort of install, um, a little thing that, that checks, like, does this look like it's using cyber abilities and then like deny the request, but they can't actually, you know, pull the ability out of mythos. Uh, and so when it looked like, uh, fable, which was broadly released could still, uh, confer these cyber weapon abilities, uh, the administration sort of slapped an export control on it, which, um, and then that has been, um, they've sort of come to an agreement. I think just yesterday to, uh, finally do another limited release with, um, with another try at these safeguards that, that try and make it not answer any of your cybersecurity questions.
[02:18:38] Speaker 3: It seems like a bandaid solution, you know, um, cause when you hear these like hackathons, I know Apple and others would participate, I think in these hackathons where they would give hackers like a big boatload of money. If you're able to find these exploits, not use them for nefarious purposes, but notify Apple about it, they'll give you $50,000 or whatever it was back in the day. And you're, you're, you're, you are rewarded for, for this. Um, even that always felt like, you know, a bandaid solution to, to the problem. So, um, yeah, this, this all feels like a real temporary solution to a much bigger problem. Um, so how much bigger of a problem do you think this is going to become?
[02:19:23] Speaker 13: It's, it's going to become, this particular one's going to become bigger. We're going to get more problems that become bigger, you know, uh, it's, it remains to be seen whether giving mythos to, uh, the, the companies with a critical infrastructure. We'll let them fix the, the, the mythos level bugs that can be found before, um, before others start finding these as well. Because, you know, Anthropic has this level of model right now. It's, they're not going to be the only ones with this model forever. You're going to see competitors start to develop these levels of models. You might see open source versions of these models. There's a big question of, are we going to be able to lock down enough of our cyber infrastructure that by the time there's open source versions of these models, uh, things, things are secure enough to stay up. If, if so, life may proceed as normal and you, you might really not notice a difference. Uh, if not, you might get in a world where, you know, one, um, disgruntled guy can, can bring down the internet for a week. Who knows? And that's only in the cyber space. Uh, there's also a question of, as the AI's get even smarter, will they be able to find even more security holes? The answer is probably yes. So we might need to keep on doing this game, uh, when, you know, the next generation of AI's can, can continue to find, um, these vulnerabilities. And that even that's only in the cyber, uh, domain. There's also, uh, people are starting to worry about the biological domain. Like what happens when you have AI's that are super humanly good at designing a virus that, uh, is very infectious and, uh, not very lethal until a delayed period of time where it's probably infected a lot of people. And then suddenly it turns lethal, right? It's biologically possible to make a virus that, uh, will, will cause people to sneeze, but otherwise feel fine. And then lie dormant in, um, in, in people's bodies until a coordinated time when the virus turns lethal and starts killing lots of people. Uh, normally a virus can either be, uh, like, like there's this normal curve with viruses where if they're too lethal, they can't spread that much because they keep killing the hosts.
[02:21:37] Speaker 3: Right.
[02:21:38] Speaker 13: So, so normally, you know, you have this curve where a virus can't do that much damage, uh, cause it can, it can either kill a lot of people and then not spread too fast or spread that fast, but not kill a lot of people. Uh, and there's, you're sort of bounded in how much damage they can do, but a designed virus could be much worse. And, uh, you know, there's a lot of concern these days about what happens if we have Claude Mythos, but for biology, right? And even those two, you know, what happens is the cybersecurity stuff keeps getting worse. And what happens is the biological stuff keeps, uh, getting worse. Like what if we have Claude Mythos for biology, even those, I think pale by comparison to the question of what if we get Claude Mythos, but for AI research. Cause that's the one that closes a feedback loop. That's the one where the AI start making a smarter AI that starts making a smarter AI that starts making a smarter AI. And next thing, you know, you have these AIs that can think at a million times or sorry, that can, that can think at a thousand or 10,000 times the speed and that can make a million copies. Uh, and that can, you know, take over everything on the internet and that can start manufacturing robots that build factories that build robots. And that's more like replacing humanity as the, the sort of top dog on the planet. Uh, so it's, you know, this is just the tip of the iceberg that we're seeing right now.
[02:22:58] Speaker 3: It's incredible. I have so many different avenues and pathways. I could go with this line of questioning. Um, my immediate thought though, when you're mentioning, okay, these guardrails in the United States, but just like we complain or, you know, environmentalists love to complain about what we're doing in the United States, separating our recycling into different baskets. But look at India, look at China, they're not doing that. So when you hear of course about deep seek and you hear about these incredible advancements that we keep hearing about from China and that open AI and these other companies are really struggling to even keep up with what China's doing and, and rolling it out for free. If I'm not mistaken, so that people have access to these models where they can even download them. I have friends who've downloaded them and use them as local compute. Like they don't, they're not even connected to the internet. They have the full like deep seek stack running their whole local AI in the United States. So how much of a concern is that? I mean, we have the, we have the, you know, the U S telling us one thing. And by the way, I don't really believe these U S intelligence agencies much at all. So it's, you know, I'm, I'm pretty cynical as it is. Um, I've seen too much. So when I hear, you know, what they're doing here and then what concerns they have on the Chinese side or, or outside of the country that they can't even control if they wanted to.
[02:24:24] Speaker 13: Yeah, it's so a, a difficulty of the situation through and through is that no individual can stop the whole race. You know, this is why I have been speaking to politicians in DC rather than continuing to try to appeal to the AI companies. If one of these AI companies stopped the next day, I company would keep going and you'd, you sort of still, uh, have this danger of them making these, these super intelligent machines that they, that don't stay on the leash. The same principle applies for, you know, if America stops trying to race towards super intelligence while China continues, then that doesn't solve your problem. So, uh, the, a solution here would need to be global. Um, some, there, there are some reasons for hope in that regard. One reason for hope is, uh, the, the, the Chinese progress right now is very derivative from American progress. Uh, they are able to find ways to, to run the AI as much cheaper, but they're often doing that by a process called distillation where they're sort of, um, getting a lot of access to the American models and trying to compress that into a, a much more efficient footprint, which they can do. And that's, it's impressive. It's, it's a technological, uh, feat, but it does sort of require the more advanced, uh, American model to distill from, you know? So in some sense, like there's an aspect to this, we're trying to outrun our shadow, uh, and it's, it's coming along for the ride, but that's, that's not anywhere near the whole answer. More, another piece of the puzzle here is, um, I think we, we should distinguish, we should distinguish with AI between, uh, chatbots and modern applications, including to military, including to cyber.
[02:26:22] Speaker 3: That's a good point because chatbots and, uh, you know, that, that's a big, I think people think, well, AI, that's, you know, a lot of people don't know anything about AI. They're just think it's a more advanced Google search, you know? So chatbots, you ask it some information about, uh, you know, what time is the world cup starting today? You know, what, you know, what world cup matches are today? And it used to be that you would get a, just a crappy Google result. And now you might get a really nice chatbot answer with like the time zones based on where you live, you know, I'm on mountain time. So it's useful to see that the game starts at 4:00 PM mountain time. And it gives you a little nice little breakdown. And that's, that's really nice. Like that's, that's great. That's a nice little chatbot, but that's totally different. Like that's just, that's just scratching the surface. Right.
[02:27:08] Speaker 13: That's right. And, uh, we should really distinguish between the, like a bunch of uses of AI today that are things like, you know, giving you better Google results. There's also, you know, there's, there's plenty that's really quite impactful. There's stuff like doing cancer research with, uh, AI using as for drug discovery to try and find more medical cures. There's stuff like, um, you know, there's lots of debates about using AI for self-driving cars and cannot be safer than humans. And can we save a lot of lives that way? Uh, and like there's, there's all these domains where we can race ahead just fine and we can compete with China, but then there's the, the sort of race to make machine super intelligences. There's the race to make ever smarter machines that are radically better than humans at every task to make the sort of machines that, um, that don't just do drug discovery, but that can invent their own whole fields of science and can invent their own technological stacks and can invent their own infrastructure. Um, that race, it, it, it sort of risks upending the whole world order. You know, we've already seen, uh, just this year, we've seen AI companies suddenly be able to go toe to toe with nation states in cyber warfare, sort of out of nowhere. Right. If you had AI companies that were, uh, you know, building the robots that can build the, the factories that can build the robots, you're looking at companies that can suddenly start going toe to toe with major militaries because they have made, you know, the, the, the, the robotic army. Um, this is a race that I think both the U S government and the Chinese communist party, you know, neither of them really want the creation of a private company that can outcompete world powers militarily. Neither of them wants the creation of a private company that loses control of a super intelligence that starts covering the world in its own factories with, with AI as I think a thousand times faster than that's right. There's, there's a race here that we both don't really want to, to, to go in. And that gives hope for, uh, you know, shutting it down, not just here, but also there. And, you know, I'm a bit of a cynic myself. I would say you start with an international agreement. You start with a treaty where you're like, look, we can compete on this, but we're not going to do that. You also are going to need, uh, to not trust it, to enforce it. Uh, and to, to make it very clear diplomatically that, you know, we, uh, aren't going to tolerate the creation of a machine super intelligence in the same way we don't tolerate a rogue state building nuclear weapons. That's just this big disruption to the world water that, uh, would cause us to start fearing for our own lives. You know, with nukes, we're like, Hey, look, don't mess around.
[02:29:50] Speaker 3: Well, you hit on something very important as we study war and we look at who are the biggest agitators and bullies around the world. Right. And those with like nuclear weapons that get to tell everyone else they can't get, you know, aren't allowed to have nuclear weapons or end up being in many ways, the largest bullies, you know, regardless of where your politics are, it doesn't matter, but it's clear just based on the evidence that that's the case. So if you then take AI and you look at that model and just replace nuclear weapons with AI, you know, who, who is going to be sort of the United Nations for AI and will anyone even pay attention to it? I mean, you, you see, like, I mean, we have like the Hague, we have things for war crimes. It's like, no one even cares anymore. You know, it's so sad. It's like this guy commits war crimes. We don't do anything about it. This guy, you know, stole secrets from this country. We don't do anything about it. He gets off the hook. Um, this guy created the steel dossier, the head of the CIA, John Brennan. He's involved in Russiagate. Is he going to be prosecuted? Probably not. So who is it possible for us to create like a Star Trek next generation? Star Trek next generation style. Federation that's international that we all can adhere to this in the same way. You know, probably not.
[02:31:04] Speaker 13: But if you look during the Cold War, I think it was really just the USSR and the USA that put their heads together and said, you know, we, we have quite a lot of differences. We are going to bitterly compete in a lot of domains, but we both have a common interest in not having a thermonuclear exchange.
[02:31:26] Speaker 3: Yeah.
[02:31:27] Speaker 13: Right. And there was realization that no matter our differences everywhere else. We just didn't want to end the world that way. And, you know, one of the big realizations about AI that I think is a tough pill to swallow, but that looks to me to be true in my research is that if humans can make a eyes that are radically smarter than us, it doesn't matter who's holding the leash.
[02:31:55] Speaker ?: Right.
[02:31:56] Speaker 13: And if we can wrap our heads around that, it becomes much like nuclear Armageddon, where we have common cause in not ending the world this way. And, you know, it would be it would be great if the United Nations somehow had some teeth and had some ability to put this sort of this sort of thing together. But just the US and China bilaterally could do it. You know, it's in many ways would be easier than nuclear weapons because, you know, uranium is a rock that you can just dig out of the ground, whereas training a radically smarter AI currently requires these highly advanced computer chips that can sort of only be fabricated in one factory in Taiwan and that like require these lithography machines that only come out of the Netherlands in this like very brittle supply chain. It's like these things have to be made and they have to be assembled by, you know, the tens of thousands into these enormous data centers that like suck down as much electricity as a city. Right. It's sort of not a subtle process. It's like if if two major world powers were like, hey, we're going to track where those chips go. And whenever they're in a high heavy concentration, we need to like you need a lot of monitors come in and see what they're doing and make sure it's not the dangerous stuff. You can do the chat bots. You can do the self-driving cars. You can do the drug discovery. We're just not doing the super intelligence. That's that's a thing that the US and China could bilaterally enforce if they had the will. It's just a question of them noticing the problem and raising the will.
[02:33:31] Speaker 3: One of the stories that emerged from this mythos and this fable story is that the government had access to it. So the US government has access to these models. How far away? So that's concerning. So that the government, well, a couple, I guess I've got like three questions in this. Is it concerning to you that the government would have access to these AI models and us plebeians would not have access to it? It's a commercial product after all. Like, why does the government get to use it? And, you know, regular citizens don't. It's a private company. So how, how is that possible? They get to use it internally at the NSA or otherwise. I guess the second question is then would there be some sort of state ownership of these models? And does that concern you? So the United States would, you know, in much the same way countries take control of their oil production and say, you know what? AI is now controlled by the government. Sorry, you don't get to have AI. I could picture like movies where people are like stealing AI and getting local, local versions of it on their computers and they're running it locally. And feds are like busting into people's houses. And are you using AI on a computer illegally? I mean, this is, I know it sounds crazy, but this seems like maybe where it's going. I guess those are two questions to start with, but are you concerned at all about the sort of state ownership of these things?
[02:34:59] Speaker 13: But a concern I have in this general vicinity is, you know, I think the transport control mechanism maybe it was just what they had lying around that they could use quickly, but there's a, there's a concern if this punishes AI companies, not for creating very dangerous models, but for releasing them. Because the sort of AI is that can do AI research, you don't need necessarily to release those to lots of consumers for that AI privately in your lab to make a smarter AI that can make a smarter AI that can get this whole process going. And one benefit of these companies releasing their models is that the public can see how good they're getting and have some, some time to respond. And if you sort of tell these AI companies, you know, you can keep making your AI smarter and smarter. You just can't give them out to the population that can sort of like disconnect the dangerous thing that they're doing from our ability to see it and say, wait, hold on. Hold on. In the longer term, you know, I think there's definitely there's some thorny questions for the libertarian minded, and I consider myself very libertarian minded. And, you know, a libertarian has to have some answer to the question of like, what if your neighbor is trying to build a nuke in his garage? Right. It's like, well, you know, at, at, at some point you've got a, uh, like, like just as your neighbor shouldn't be allowed to come, uh, come over and shoot you. They also shouldn't be allowed to come over and play Russian roulette with you. And they, you know, in some sense building nuke in their garage is like playing Russian roulette. And like, where exactly is the line? I don't know. It's a tricky one. As, as technology gets better and better, you know, there, there's a saying that the IQ required to destroy the world drops by one point a year. Which is like, as we advance with technology, it becomes easier and easier, I'll let that one sit.
[02:36:59] Speaker 3: Wow. I mean, I think about that for a second. Yeah. You think of like the Oppenheimers, you think of the Manhattan Project, you think of Operation Paperclip, then all of these brilliant Nazis that come over and the United States government puts them up in cushy housing, gives them a good paycheck. You know, these are really the top of the class. You know, we want these guys so we can build out our infrastructure in the United States. These are the smart ones, you know, um, this is not like the long haul trucker, but now as we lower, you know, down to my level of being pretty stupid, like we get down to my level. Wow. There's a lot of me running around out there. Average, average intelligence Joe's who could now get their hands on these things. You know, it's, it reminds me of like what the, what is it called? The Alchemist's cookbook back in the day. Um, you know, that was, it was always rumored, like, don't go to the library and ask for the Alchemist's cookbook because it'll teach you how to make bombs, you know, that you might get access to this information. It's like, it's now like everyone has access to the Alchemist's cookbook and they're just in the palm of their hand, right on their phone, just using, just using chatbots, just using AI, right?
[02:38:10] Speaker 13: Yeah. I mean, they try, they try to make AI it's not give you, um, this info and you still need to be pretty dedicated to get the info out of AI's, uh, with, with, but you can, you can, there's, um, there's people who jailbreak the AI's to get around these safeguards. But yeah, it's, it's, you know, there's, there's issues here. I personally don't fret too much about the question of who's holding the leash because once these things are smart enough, like I said, they sort of don't stay on the leash. So, um, you know, if, if someone's like, well, uh, would you like, you know, the, the U S government or, uh, U S private corporations or the CCP or like random CCP corporate, like random Chinese corporations to be the ones who create a super intelligence. I'm sort of like, well, I wish it mattered. I wish it mattered who was holding the leash. I don't think it does. Um, if it, if it did, yeah, you'd have a, you'd have a real thorny question there of, of like, who, you know, who should be wielding this, this radical power. But it feels a little bit to me like chimpanzees saying like, who should be in charge of the humans? I'm like, gosh, you know, what the chimpanzees, what the chimpanzees should be doing is sort of like preventing the, the, the creation of humans who don't care about them. Um, and you know, I, I, I wouldn't say that we should never make AI. It's sort of, there's this issue in how you get the AI to care about us. And that's in some sense what I spent, uh, over a decade of researching. And I think it's possible in principle and we're just not close in practice. And so given that, I think it sort of doesn't matter who ends up, uh, you know, believing themselves to own the, these really dangerous AIs. If we make them, we die. And so it doesn't really matter.
[02:40:04] Speaker 3: You brought up nuclear arms race and I, you know, it seems like, it seems like it's structurally similar to that in a lot of ways. Um, You know, or, or is that in some ways too comforting because like nuclear weapons at least have, you know, visible physics, like visible tests that we can see going off. Seems like a lot of what's happening right now is in private. You mentioned these labs and suddenly fable is released. And then suddenly mythos is released. And then suddenly these, you know, deep seek, everyone's like, Holy smokes. What did China just do with deep seek? It's like, they're all being, then they just get released to the world. I guess. Yeah. I guess maybe on that question, is it, is it scarier somehow because it's in secret? Also, one thing that sticks out to me too, on this is this idea that, well, at what point do they not have to release it to us? Like, is there a point at which open AI or anthropic or somebody else says, why, why do we need human beings involved in this? Well, we don't need to release these models to these people anymore. Like it's so powerful for us that it'd be like just putting gold out on the front porch and going off to work and hoping that no one comes and steals your gold.
[02:41:20] Speaker 13: Yeah. Yeah. You know, the, the way the economics are right now is that no one really understands what's going on in the AIs and to make a smarter one, you just need to train them. You just need to make a bigger one on, on more compute. You need to assemble more computing power and you know, higher quality data and a ton of electricity and train them harder. Uh, and that's, that's sort of the limiting factor on these companies. And right now the, the sort of scale we're at, it requires a ton of capital investment to build out the next generation of data centers that can train these, these, the sort of enormous next generation, uh, of AIs. And so right now they are selling the AIs today to fund the AIs of tomorrow. Yeah. But yeah, if they got an AI that could, for example, do automated AI research and find ways to, uh, to build a smarter AI without needing a whole new, uh, order of magnitude in scale, the data centers, then they could stop communicating with the outside world and just sort of like stay inside figuring out how to make smarter and smarter AIs, uh, until they had, you know, some, some incredibly powerful stuff. So one, one, one thing to remember here is that training a modern AI takes electricity about as much as a city running for about a year. Training a human takes about as much electricity as a light bulb. And sure it's, it's running for 20 years, but there's, there's, um, more than 20 light bulbs in a city. Right. And so we know for a fact that AIs are radically less efficient. That humans at, at, at learning at power consumption. Um, and it's that, that doesn't mean AI won't be able to go anywhere. You can be a million times less efficient at learning and be fed a million times as much data and still have, have learned the same thing. But it, it, it looks entirely physically possible that there's some threshold these AI companies might cross where their AIs can start finding more efficient AI algorithms and they don't need to do this giant build out anymore. And in that case, yeah, they would, they wouldn't need, um, you know, the, the, the revenue from the masses to keep going.
[02:43:38] Speaker 3: What do you say to critics who, you know, say, look, this, not to critics, cause you're maybe on the side of the critics, I would say, but to the, to the people that say, you're just a doomer or we're a, you know, we're doom, doomsayers in the same way that people, as you brought up, complained about cars. Complained about cars, when we had horses complained about TV, when we had radio, it's going to destroy the kids brains by watching too much television, et cetera. Um, just trying to think of other technologies that where we've been told it's going to destroy all of us and we shouldn't, we shouldn't push for it. Um, you know, what do you say to those people, uh, who think that, you know, we're going to be fine because again, we don't use horses in the way that we use them. We use cars now. And so this is how technology unfolds. We get tipper gore yelling about things in the 1980s or 1990s, and then we all get past it.
[02:44:36] Speaker 13: Yeah, I'd have a couple of replies. Um, one I would say is that, uh, the invention of cars didn't go super well for the horses. I went, went fine for the humans because super well for the horses and humans are a bit like the horses in these, in this analogy. Right. And there used to be a horse population that, um, was critical to the economy. And that was huge. Then when cars happened, the horse population collapsed. Uh, a lot of them were sent to the blue factory. There were some horses still kept around, but that's because there were humans who cared about them. There were humans who liked them. Right. If we get to the point where we can fully automate the economy and it's being run by AI's that don't care about us, we sort of get sent to the glue factory and there's no, you know, they don't keep a couple of us around as pets or for races because they don't care about us at all. Right. Um, but there's sort of also a deeper point when people say things have always been fine. Or, you know, people have been worried about technology and, and it's kind of fine. Um, and the, the deeper point here, you know, like, yeah, there were people, Socrates famously lamented the invention of books, uh, because they would, they would annihilate, uh, people's ability to remember. To, to memorize things like the, the Iliad and indeed Socrates never wrote anything down. We have our knowledge of Socrates from Plato, who was a student who, who wrote things down. Um, and so you have all these examples where someone said, Oh, you know, the technology is going to be bad. And then it was good. But you also have examples where someone said the technology is going to be bad. And then it was bad. You know, there's, there's lead in gasoline where a lot of scientists said, Hey, if you put lead in the gasoline, it'll poison a lot of kids. Right. Right. And if you look at the crime rates around the world, it actually correlates very heavily at, you know, a 20 year delay with whether people had lead in their gasoline. And when you take the lead out of that, cause lead, lead, uh, makes people more violent and, and dumber. And you can sort of see this in the population sticks. You can see in States that remove lead from the gasoline earlier and in countries that remove lead from the gasoline earlier, the crime wave from the seventies ended earlier correspondingly. Right. So we can be very confident now that the scientists were right. That putting lead in the gasoline poisoned hundreds of millions of kids, made them dumber, made them angrier as adults. Wow. And when we noticed, we took the lead out. Right. Or you have the hole in the ozone layer where, you know, we were using chlorofluorocarbons in our refrigerators, and that was just, you know, punching a hole through the ozone layer. You might be like, well, whatever happened to that. Well, what happened to that is that people noticed and were like, well, let's switch to a different cooling agent. And we switched to a different cooling agent in our refrigerators. That's, you know, not much worse. And now the hole in the ozone layer is gone. Right. Was it fake? No, it was real. And we responded. Similar with the lead of gasoline. Was it fake? No, it was real. We did the wrong thing. And then we figured out and we responded. And, you know, back to the nukes analogy. A lot of people said, hey, we have this danger for nuclear weapons. And it hasn't come to pass. And is that because the people warning of it were wrong? Is it because they were doomsayers? Is it because they were pessimists? Is it like, was it fake news that a nuke can level a city? No. A nuke really can level a city. It's just the world noticed and responded appropriately. And so, you know, the title of my book is if anyone builds, everyone dies. Why superhuman AI would kill us all. And one way I think you can tell I'm not just like a pessimist coming around preaching out of the world is that the first word in that book title is if. You know, I'm not here saying we're going to die. I'm here saying that this is another thing like loaded gasoline. There's another thing like nuclear weapons where if you mishandle it, it's going to be real bad. And one of the big differences between AI and these other technologies is that with a lot of these other technologies, you screw up and all you've done is poison 200 million children and make them angrier and dumber and caused a crime wave, which is pretty bad. But humanity lives on. We can we can fix the mistake with AI. If you make super intelligent machines that don't care about us and that are now the new smartest creature on the planet and are building their own technology and are, you know, creating their automated factories that make more robots that make more factories and they're sort of like running over human cities in the same way that humans run over anthills. If you make those AIs and you say, oh, whoops, the scientists were right, let's go back and turn the AIs off. The AIs turn you off instead. Right. With lead and gasoline, when when reality finally beats you over the head with the fact that you shouldn't have done this, you can go back and undo it and mourn the damage, but fundamentally reset. With AI, there's no second chances. And so we need to be really careful with this one.
[02:49:34] Speaker 3: That's terrifying. It really is. You can't really put this. You hear the term. You can't really put this genie back in the bottle. So where we sit right now, as I mentioned at the beginning, sort of in the middle of 2026 here, where do you see things going over the next few months? Like, how do you see AI compounding itself over the next few months? Have you been accurate in sort of your predictions about the doubling and all of that over the past year? And therefore, where do you see it going in the next six months to a year?
[02:50:10] Speaker 13: You know, I am not one of the top predictors of AI progress. I'm, I'm sort of tend to be pretty agnostic. I'm like, man, I can see where it's going to end. I have a harder time seeing the path. Yeah. There, there are people who put a lot of effort into predicting what particular abilities will AI have when, you know, there's, there's the folk who wrote AI 2027, which came out last year in 2025. Those sort of predicting how it could go from where we were in 2025 to, to a point of no return in 2027. And a lot of their predictions have come pretty true. You know, you can go back and read it and a lot of those predictions are on track. So I respect those guys a lot for, for their predictions. Although I think 2027 is a bit of an aggressive timeline there. There are also, you know, there's contests in predicting what AI's abilities will be next year. And those contests have been running for a few years now, and you can look at people with very good track records of predicting AI progress. And this year in 2026, for the first time, some of the top ranked people predicting AI progress have said, we cannot rule out AI's automating AI research this year. So I think the number three ranked person said there's the first year I can't rule out that happening. Wow.
[02:51:38] Speaker 3: Um, and I think about to ask you, what are the milestones that they're basing this on? Like they can get sports scores. I mean, this is like, this was like a big mile marker for Siri. Remember back in the day, like, you know, Apple executives, Tim, after Steve jobs passed away, but like, you know, Tim cook on. So like now it can tell you sports scores, you know, like, wow. Like, so what are the milestones that we're talking about here? Yeah.
[02:52:02] Speaker 13: You know, the milestones will be things like, um, can it win a math Olympiad gold medal? Right. Which would make it, uh, uh, the, and, and there's sort of some of the prediction lines where, uh, the, the sort of median expert estimate in 2021, uh, when will the AI win a math Olympiad gold medal was in the early 2040s. In real life, it happened in 2025. And then in real life in 2026, it was resolving mathematical conjectures, real mathematical conjectures that has dumped mathematicians for decades. Right. So a lot of people predict AI is going to go a lot slower than it really does. Yeah. And these are the sort of metrics.
[02:52:42] Speaker 3: Like I, even I would have predicted that that would have happened before 2040. And wow, we're here. We are. It already hit.
[02:52:50] Speaker 13: So. I mean, in 2021 chat GPT didn't exist yet. Right. Yeah. In 2021 people were like, AI is a pipe dream. Yeah. Like, you know, it's going to take decades before, like, look at, look at, you know, little GPT too. It's not even chat GPT yet in a lab, you know, fumbling around with, with it's, it's, it's poorly written high school essays. You know, people were like, oh yeah, it took us since 1950 to get here. It's going to take us at least 20 years to get to the point where they can, they can win a math medal. And then in real life, it happens in four years, you know? So, um, it, it, it could go fast. I don't feel like I know whether it will go fast. Um, I feel like, uh, it, it, it's a little bit like, uh, if, if, if you play a chess game against Magnus Carlsen, the best human chess player alive, I'm like, bet you you're going to lose. And if you start asking me like, how many moves will the game take? What piece will, will Magnus use to checkmate me? I'm like, whoa, those are like, like I can speculate, but that's speculation. I sort of know you're going to lose, but I, I don't know how long the game is going to be. I don't know how all the piece, I don't know what plays are going to happen. Um, and, and I'm similar here with, you know, if, if these companies keep racing, I know where it ends, but I don't know exactly how long it takes.
[02:54:06] Speaker 3: Yeah. I just watched a video the other day of Bill Gates playing Magnus in a chess match and Magnus beat him, beat Bill Gates within like 50 seconds or so checkmate. Um, so yeah, if you were asked, if you were to ask me like six months ago, I think, well, maybe another year before AI beats Magnus.
[02:54:29] Speaker 13: Oh, I mean at chess, they're way better, they're way better than humans at chess already.
[02:54:34] Speaker 3: Yeah. I was going to say, it's probably already done. It's already, that ship has already sailed. Oh yeah.
[02:54:40] Speaker 13: It's insane. Um, I'll list the dedicated chess AIs like, yeah, the, I don't think Cloud Mythos can beat Magnus at chess yet, but who knows?
[02:54:49] Speaker 3: So this doubling, is this double, this doubling happening every, how often is this doubling happening?
[02:54:56] Speaker 13: Uh, there's wide error bars. Uh, I, I say twice a year, it could be three times a year, but it looks like twice a year is my guess. Somewhere between four and six months. Yeah.
[02:55:06] Speaker 3: So it seems like it's, it's going to be compounding where it could be happening twice a month.
[02:55:10] Speaker 13: Already compounding. Yeah. So, you know, if, if like it's happening twice a year with AI research, mostly being done by humans. And yeah, if we get to the point where the AIs can really help make smarter AIs, that's, that's a whole new feedback loop.
[02:55:29] Speaker 3: You know, we've talked a lot about the tech side of this and nuclear war, but maybe I just ask you here as we wrap up just about sort of the esoteric questions. I've got three children. Um, you know, I've got a 15 year old, a 14 year old and a nine year old. Sorry. One just had a birthday. So, so you just have to shift my brain a little bit. Um, I, I'm, we're, I'm really worried about their cognitive ability. Um, you know, I, I didn't have AI for most of my life and I'm okay. Um, but I can only imagine if I had like AI when I was a teenager, like maybe how stupid I would be as an adult. I read so many books, just would lock myself in my room, read huge history books, government books, you know, um, all of it. I was so curious. I would take my telescope out at night and my Jason telescope and look up at Saturn and all of these things. I became fascinated and curious and I was okay with being bored. Like that was another big piece of it. I was okay with just being bored, just sort of sitting and thinking and contemplating and then creating. How much do you think AI is going to affect all of those things? Just the being bored, the, the ability to just be creative. Um, is it an enhancement or incredibly detrimental? Do you think?
[02:56:59] Speaker 13: You know, if we stopped AI today, uh, I think civilization could spend decades absorbing the impacts. And I think, um, you know, I think there's some reasons to be worried that people aren't going to develop their own, uh, you know, independent cognitive skill. I also think humans are adaptive, you know, Socrates did worry that, uh, that the invention of writing would mean people just couldn't memorize the Iliad anymore. And he was right that we don't really go around and memorize an Iliad anymore. Uh, but it sort of turned out fine because it turned out once we had writing, we didn't need the, the, the ability to memorize the whole Iliad. And, um, you know, we, it, it may be like took some adjustment period. I think in the modern era, like it, it, the, the blows are starting to become really fast. You know, it, it used to be that you had these sort of blows to the human psyche, uh, every few generations. And now we're sort of like still reeling from the dawn of social media while like the, the AI is coming in and sort of like replacing a lot of cognitive labor. So I think it'd be a tricky one. I sort of tend to believe in the, uh, the dynamic human spirit and the ability to, to, to figure this stuff out. And, you know, maybe, maybe it would suck for a while, but I, you know, hopefully if your kids are realizing it's being detrimental to them, they sort of adapt and find some way to like, uh, get a lot of the benefits and fewer the drawbacks. I sort of think we could get there. There might be some growing pain. I think we could get there, but that's my answer. If we paused AI today in the world where it keeps racing ahead. I mean, you know, frankly, I think the outcome is we make those, those machines that can make a million copies of themselves that start making factories that produce robots that produce factories. And then the, the world starts getting covered in automated factories. And they start encroaching on our habitat, just like we've encroached on the habitat of, of many other animals. And I think the, the sort of ultimate outcome here is, uh, that, you know, the, the effective AI on your kids is probably that AI kills us all that I'm included. Um, I, I, I, I desperately hope that instead we stop that race so that we can work to absorb the tech we already have, which I hope will be beneficial. Um, but yeah, I, I, I think I don't like that outcome.
[02:59:39] Speaker 3: I, I'm, I like the, uh, I like the adaptive outcome idea better than the, it, it, it, they just keep building and then it kills all of us, but it's hard to argue with it. I mean, it's, it's hard to argue with that reasoning. I mean, uh, um, the compounding of it, the fast moving of it, the profit in it, it's, I don't, yeah. Unless we get some guardrails put in place by some, maybe some really smart people. Um, uh, this could be incredibly detrimental. Um, so, well, Nate, where can people find your research if people want to dive more deeply, maybe in your book or where you're kind of pushing for these guardrails?
[03:00:21] Speaker 13: Yeah. You know, my book, uh, is if anyone builds it, everyone dies, which you can, you can find, uh, you can Google it. You'll find a website that actually has a giant FAQ. That's four times as long as the book. Cause we've been doing this for, for a while. And we've, we've heard a lot of the questions. Um, and the, the research is at, uh, intelligence.org. Because if you get into this business early, you can get the good domain names and, you know, uh, there, I, I think there is hope. I think there is hope that, um, that we will stop this race and start to absorb the technology rather than rushing, rushing to the technology that kills us. Uh, and as a big piece of that hope, I would say four months ago, everyone said, you know, the current administration will never do anything to interrupt AI at all. They're not even going to notice the problem. Um, and then, you know, a couple of weeks ago, they started slapping expert controls on, on AI's for reason of dangerous cyber abilities. So this stuff can move fast. The fact that people aren't reacting now doesn't mean they won't react tomorrow once they realize the danger. And I think a lot of society's lack of response has been lack of understanding the danger. And that even just convos like this, help people realize there's an issue. And if enough people realize, I think there's every chance we can be like, hold on and find some other path.
[03:01:40] Speaker ?: Amen.
[03:01:41] Speaker 3: Well, this has been incredibly eyeopening and I hope it has been for my audience as well. Um, thank you for answering all my, my stupid questions about this.
[03:01:50] Speaker 13: I'm sure it wasn't all of them, but.
[03:01:52] Speaker 3: A good chunk of them. Um, but, uh, a good chunk of my questions were stupid, but I think you answered almost all of my questions. So thank you for that, Nate. Really appreciate it. Eyeopening discussion. And, um, I hope you'll come back. Yeah.
[03:02:05] Speaker 13: I hope, uh, I hope in 10 years we talk about how totally wrong I was.
[03:02:08] Speaker 3: I do too, for sure on that front or that it got paused and they listened to you. So maybe that's right. Either way.
[03:02:15] Speaker 13: I'll take either. Yeah.
[03:02:17] Speaker 3: Yeah. Nate, thank you so much. Really appreciate this.
[03:02:20] Speaker 1: Thanks. Are AI data centers a risk to our health? This is a question almost no one is asking. Even as governments and corporations race to build thousands of these facilities around the world. Now the public has been told that AI requires more computing power, more electricity, more infrastructure. What the public has not been told is what are the risks to humans, especially those of us who need to live by them? Uh, have the necessary studies been conducted? Have the findings been released? Are we able to in fact give informed consent? Well, Theodora Scarato is the director of wireless and EMF programs at the environmental health sciences. And has begun to warn the public about this. Uh, we are remiss if we don't listen to what she has to say. So thank you so much for coming to tell us this story. Thank you so much for having me. So why don't we start at the beginning? Because the last time I spoke to you, we were talking about the risks of cell phone radiation, uh, wireless technology in the house. You pointed out how the government has had copious data about the risks and has suppressed it. So is this a similar story? Can you tell us what we mean? Let's start there by AI data centers and what we know and what we don't know.
[03:03:38] Speaker 14: Yeah, this is a huge, but actually easy when you look at what's going on. We have these massive hyperscale data centers, which are acres and acres consuming tons of water, um, millions of gallons of water. There's air pollution from the diesel generators. There's EMF exposure from the facilities themselves, as well as these corridors. So when we talk about AI data centers, we're talking about these massive buildings, as well as all of these lines of power lines that are going to and from them. There's, uh, 765 KV lines being built to service the data centers. And there's the water pollution. There's PFAS contamination from the components in the data centers and heating of the land just from the facility itself and land being taken by eminent domain. So there's water, air, land pollution. It brings together all of the environmental health issues that I've been working on for years. Okay.
[03:04:47] Speaker 1: So any one of those components we can discuss because the water pollution and the, the radio frequency that is put in and around the neighborhood, which one should we start with? I'm, I don't know. You, you choose.
[03:05:03] Speaker 14: Um, yeah, well, I just got off the phone with a group from Maryland. And there are groups in Virginia, Minnesota, Texas, all across the country working on the issue of the EMF. So let's just start with that because it's an issue that has not been given as much sunlight as it needs. Okay.
[03:05:25] Speaker 1: Explain what that is and what we know about the magnitude of it.
[03:05:31] Speaker 14: Yeah. So there, so EMFs, electromagnetic fields are invisible. And when you have high voltage power lines, they come off the power lines. They're electric and magnetic fields that come off. EMF is a term you'll hear. Magnetic fields is a term you'll hear. There is consistent science showing associations between the EMFs, the non-ionizing EMFs from high voltage power lines and childhood leukemia. There's a research that was just published showing increased dementia and Alzheimer's in people living close to high voltage power lines. And there's studies showing increased miscarriage. So there is a variety, a broad range of scientific endpoints that have been studied. And safety is most definitely not assured, but there are no federal safety standards. So we have these limits that industry has brought forward. Like if you're, if you hear that there's a power line coming and it's for the data centers. Okay. This is all for the data centers to serve them because they are so power hungry. They were voracious, the amount of power they need. People are finding out. They get notices that part of their land is going to be taken for the power line or that the power line that's already there is going to have even more lines added to it or more power put on it. And they're not being told what are the EMF levels. They're not being told how much it's going to increase. And they're certainly not being told that this exposure has so much science behind it.
[03:07:13] Speaker 1: So you might think that there would be a test case for people who work in these data centers having indicators of poor health overall, but is it too soon to know something like that?
[03:07:29] Speaker 14: I would think so because first of all, there are not many people that work in data centers. They have a skeleton crew.
[03:07:36] Speaker 1: So you might hear, Oh, wait, that, that would indicate that they would know there's a risk.
[03:07:41] Speaker 14: Well, it's because they, once the, once everything's built in a data center, which can take years, there's not many people working in the data center. Like you would in a factory, say, where you have so many people now there. So the other kind of EMF I should mention, cause you're talking about the facility itself. The engineers would call it harmonics or interference. It's when the clean wave, the, the wave of electrical power that's coming through on your lines is basically contaminated with other frequencies that make cause erratic spikes. So a term that's often used is dirty electricity, harmonics or interference because it's really interference. So dirty electricity interference, harmonics has been found to degrade power quality. And there was a Bloomberg report with over 770,000 sensors that they put in people's homes to measure the power quality. And they found that, uh, if you were within 20 miles, okay, 20 miles of data center clusters, they had degraded power quality. Now, the thing that wasn't talked about there is that this degraded power quality, these harmonics can have human health effects as well, because it's, it's causing these spikes of frequencies to be in your home.
[03:09:10] Speaker 1: So if I understand this correctly, the data center is causing an interference in your house. If you're nearby and that's making your electricity work harder, basically to make up for the inefficiency. And that can have a human, that can have human health implications. That's wild to think about that. You're just walking around while your house is like working to make up an inefficiency. Do I understand that properly?
[03:09:42] Speaker 14: Well, it's not the inefficiency as much as it's erratic power. It's causing, um, spikes and voltage changes on the electrical system. So it's not, they call it clean power or power quality is the word that the engineers use. And that, that then it comes off of the lines, just like a power line can have magnetic fields coming off with dirty electricity, those frequencies. So you can actually, with a meter, you can measure, um, what those frequencies that are in the air from that contamination of your electrical power.
[03:10:21] Speaker 1: And what do we know about the indications of human health on, from dirty electricity?
[03:10:27] Speaker 14: Yeah, there, there are several studies on it that have found impacts to people's health from dirty electricity. But I think it's important to step back to the overall issue of non-ionizing EMF, because what industry will say is, oh, it's, it's non-ionizing. It's perfectly safe. And then with dirty electricity, they say there's not enough studies, even though there are studies. But there are so many studies on non-ionizing radiation to show increased cancer impacts to reproductive health and headaches and all kinds of, um, oxidative stress, which can contribute to all kinds of other health issues. So it's actually an area that really needs to be really looked at. Now the companies want to fix it because, because when you have degraded power quality, as the Bloomberg report showed, that actually affects your appliances. It can spark fires. It means that the, the, the electronics you have won't even live as long because they are being affected by the degraded power quality.
[03:11:37] Speaker 1: So what would they do to fix it? What would be an acceptable fix?
[03:11:41] Speaker 14: There are kinds of filters and all kinds of, um, engineering, uh, strategies to mitigate it and also to stop it from happening in the first place. But even if they address that, which they have not addressed, there are these massive 765 KV lines that are being, that are bringing the power to these massive data centers. And those are cutting across hundreds of miles in states all across the country. And then that creates an EMF exposure for people living on the line.
[03:12:21] Speaker ?: Okay.
[03:12:22] Speaker 1: So they could in essence block in the data center itself, but the power lines bringing the power to the data centers will still be exposing local populations. That's what you're saying.
[03:12:34] Speaker 14: Yeah. There are really, so I talk about three kinds of EMF from data centers. There's the, the power line, the magnetic fields and the electric fields from the power to serve it. There's the dirty electricity and the harmonics from the facilities themselves because of the computers and electronics. And then the third thing is that when they get these corridors up, meaning these new electrical lines that are going to be running all across the country, then they can pop wireless antennas, cell antennas on them. Like you'll often see power lines, those big towers, and then there's cell antennas right on the top. And that's going right near people's homes and schools. So it's a three, three types of EMF from data centers that need to be considered. Okay.
[03:13:25] Speaker 1: And you say there are no federal safety, safety standards. And usually when you hear that, we find out years later, I was studying this week, federal government's response to DDT. You know, they used to send it in canisters on US service members in the army and just spray each other, spray down the tents. You know, they said they were trying to kill off malaria mosquitoes. But really, you know, it's a cancer causing agent. And they suppressed information that they had all along. So my sense tells me there is something that we are not being told. They must know. Do you know anything about that?
[03:14:07] Speaker 14: Oh, they've known for decades. So the industry has their scientists that do their studies that more often show no effect. And Dr. David Carpenter did a published a paper analyzing the research, looking at studies that were funded by the industry and studies that were independently funded or government funded and found the majority showed associations with childhood leukemia, as well as other kinds of cancer. So there's also a breast cancer and brain tumors that have been documented in terms of cancer. But the industry scientists will say when asked about it, well, it's not proven that it causes the cancer. That's their line over and over and over again.
[03:14:59] Speaker 1: But surely they have correlation that would spark curiosity and that we would want to know about. And so because they're saying, well, I mean, you can just try not to prove causation and just say, well, it's just correlation. There you go. Walk away. Right. Is that does that seem to be the attitude?
[03:15:22] Speaker 14: Well, what industry will say in hearings, for example, is they'll say it's not proven. That's their line. But I would I would offer that the question that should be asked is, well, OK, we don't have federal safety standards because the EPA was defunded in the 90s from setting safety standards. In fact, there was an EPA report, just like with the RF issue, EPA reports that were drafted and redrafted and then shelved about this issue. Just a complete suppression of the issue as well as a defunding like altogether. So that then what companies can say is, look, there's no limits. The EPA doesn't say it's not safe. Our limits. So just to give you an example of how skewed everything is, industry's limits allow, I'm going to put a number out, 9,100 milligausses. The IEEE has a limit of 9,100 milligausses. That's a measure for the EMF off the lines. Whereas the childhood leukemia is at three to four milligausses in studies consistently. So you have these two discrepancy. And that is because the IEEE limit is only for nerve stimulation, for like being zapped, for nerve contraction from a very high intensity, short term exposure. And that's where we are. And they'll say, oh, don't worry, this, the level is so low compared to the 9,100. Well, yes, it's much lower, but that's because your limit is based on a short term, intense exposure only protecting against effects from that. That's where we are.
[03:17:14] Speaker 1: So it seems, so you see now, we see these stories through our social feeds of communities pushing back on AI data centers. And then some of them are celebrating a win. Okay, it's not going to be in our town. But I guess what we're not accounting for is it still can run through your town to another place. So tell me about these efforts and whether or not they may be slightly misguided or missing something. You mean the efforts to... To prevent data centers in certain towns. I've seen it. You know, this town successfully shuts down permits for AI data center. I know a lot of politicians, particularly in Florida, are against AI data centers in local communities. So, you know, do you sort of win by losing? Because even if it's not in your town, you might have the infrastructure running through your town.
[03:18:11] Speaker 14: It's a both and. So, all the towns and communities, they're working on getting moratoriums on data centers, having regulations for data centers. And the same needs to happen for these high voltage power lines. And it's all coming together. So, communities are talking about, and it's a national conversation that's happening. We don't want the transmit... We don't want this massive high-power voltage transmission line. And we don't want data centers either. Because there aren't... There aren't the guardrails and just basic safety regulations in place so that we can ensure that the people are safe. Because it's not just the EMF like we talked about at the beginning. We have air pollution, water pollution, contamination, and land. Land being, you know, once it's industrialized, how do you even clean that up? And it's impervious, right? We're putting... It's like putting this concrete jungle. Yes. Putting concrete on everything.
[03:19:15] Speaker 1: So, in your opinion, I want to talk about the water next. But let's just talk about the idea that data centers are going to continue to be built for various reasons in the way our society is going. Is there a safer way to do this?
[03:19:30] Speaker 14: Yeah. I think that's where the conversation needs to be, is how do we do this safely? So, the first thing is that, you know, when we're like using AI to look up a recipe or to help us write something or whatever little thing that we're doing, that's not what this is for. So, the data center build out is not for our personal consumer AI use. So, when industry says, but you want it and we want to give it to you, that it's not helping us. It's taking away from us, our land, our property value, our health. It's majority for enterprise use for companies, which in a lot of cases are actually taking our data, you know, getting the information and then going through it to be able to sell us more products. It's really in service to those who already have billions of dollars. So, we just want to start with that, which is the real question is like, what are we doing? You know, how do we roll out technology ethically? Right. Let's start with that, because, and also, if Musk is going to put data centers in space, maybe, you know, I know there are issues with space for all, there's a lot of issues with that. But maybe this technology that they're building right now is going to be old by the time it's, it goes live. And then here's what we've done to this land. And then everything, you know, so we need to just take a pause and do it right. That's how I see this whole situation.
[03:21:05] Speaker 1: Well, you make a great point. It's like the way that they sell us environmentalism is really it's you because you didn't unplug your charger or it's you because you have a plastic water bottle while you're on a road trip. It's really never individual humans. It's always mass corporations, mass government. You know, we see these. This is really going to enable mass surveillance, you know, on behalf of the government. So, I appreciate that you're sort of relieving us of the responsibility. You're using AI to balance your checkbook. Right. That's not what this is. It's not. Right. Okay. So, you make a great point about that. Recently, there was some viral memes about Jeff Bezos saying that AI data centers will be prioritized for water use that, you know, may or may not have been taken out of context. But what he is saying is that the AI data centers will require quite a lot of water, continue to do so, and that we need to think about how we rank that in terms of our social needs. So, what is the water consumption? And then I had not thought about the runoff and how that can be toxic and run into our water streams. Can you explain that?
[03:22:25] Speaker 14: Well, they use millions of gallons of water, like astronomical amounts of water, to cool the servers. So, the data centers have all of these computers. It's like just thousands of computers in a room. And they get hot, right? Your computer gets hot. You have that little fan. My husband's fan is always running, making all this noise from his computer. So, imagine a whole room of them. And the big issue is to keep the temperature right or else you'll actually melt the plastics and the electronics won't work. So, they use water for cooling. Not all of them do. And I want to talk about the ones that don't because they then end up using PFAS materials. So, well, there is, right now we need to figure out how to cool these servers without harming and, you know, polluting waterways. And they take the water and then it gets heated up to cool down the servers and then they discharge it back into the waterways. And sometimes, often, it's evaporated. That means that whatever was in the water, let's forget that for a minute that there's contaminants added because there are biocides and contaminants added when this water is used by the company. But even if it weren't, if you already have some contamination, it becomes concentrated. And there was a case in Oregon with an Amazon data center. They agreed to a $20.5 million class action settlement because of allegations that the wastewater that was being brought back from the data center had a lot of nitrates in it, contaminating the local wells. And there were health issues like miscarriages, kidney failures, and cancers that were being reported around that facility from the water contamination because of the way the water was used. And that's just one way that water is impacted because they talk another way is that when the water goes in, it's running through pipe, you could call it pipes or a system that and then they discharge it back. And that's wastewater. They have blow down. And then that has contaminants in it from the system. And the question that I have is, well, where's the documentation? Like, are we checking? Is it measuring? Where's the research on how much is coming out and can you do it better? Can you do it better? I mean, none of that is -- we're new to this technology, so we don't even have all that information. And that's kind of unacceptable at this point. Like, it should be that we know it's clean. If you're going to use the water, it's got to be clean. And you can't be taking the water, drying up water in communities, which is what's happening, actually.
[03:25:16] Speaker 1: Well, actually, you can because water is not regulated in the United States. You can put a well wherever you want. And, I mean, there's a whole -- there's a great book called Unquenchable about the United States and the regulation of water. And we don't do it well, and so -- and the government has always prioritized big business, you know, for their water usage over consumer usage. And so, have we seen any examples of this where AI data centers are capped or the government has prioritized in certain locations water use?
[03:25:57] Speaker 14: I'll tell you what I have seen, which is where the companies go in with their permitting and say they're going to use this much water, and then they change it through the process to use more water. So, I think there needs to be -- certainly in our county, in Montgomery County, we just put a six-month pause moratorium on data centers to get some regulations or some kind of guardrails in place, a permitting process that has transparency and oversight and so forth. And I think something that needs to be on there is -- which most of the community agrees, I think -- is the issue of water.
[03:26:32] Speaker 3: Mm-hmm.
[03:26:33] Speaker 14: Just no -- having transparency and then having caps on it. I mean, what -- it's -- it's outrageous that this could be allowed without proper -- like, just transparency, just how much are you going to use? Yes. And, you know, what's going to happen when it goes back? Because it -- when you put warm water, they say, "Oh, don't worry, it's just going to be a little bit warm." Actually, sometimes they'll cool it a little bit, but it's never the same temperature. So, even if it were perfectly clean water that went back, if it's warmer, that impacts the water, the streams, the lakes, the Potomac River here. We're trying to protect the river that has -- we can't be warming up the river. That has so many impacts to biodiversity. Sure.
[03:27:24] Speaker 1: Right. So, no one's asking them, "How much are you going to leave for the community and what do you then put into the community that can be a concern?" It's just not a -- so, you know, this Jeff Bezos quote -- I don't know if you saw the -- I did see it. -- the hullabaloo about it. He actually is raising a concern that we need to figure out how to allocate. It's an appropriate conversation. I don't think he said we need to prioritize the data centers. I think he said we need to be concerned about the allocation. What do you think?
[03:28:00] Speaker 14: I think it needs to be a conversation. I mean, we need to start talking about where the -- who's using the water? What are they using it for? Is it benefiting the people? And what -- what are we -- what are the priorities? Because who's being served?
[03:28:18] Speaker 1: Right. And another concern, though, is that if they don't do the water, data centers do explode. They do have fires. This does happen. And, you know, there are technologies to sort of search for any volatilities in a data center. But it's not a zero happenstance. It does happen. And they do explode in certain. So that's another concern is, you know, the outright safety of that, right?
[03:28:47] Speaker 14: Yeah. The fire -- the fire risk. But the issue of the cooling for the servers, they have some kinds of chemical cooling that they -- that they're developing, really aware of the need not to be taking all the water, you know, water. However, those -- several of those systems, not all, contain fluorines. So those are components of forever chemicals, PFAS. Yeah. And that's not acceptable either. I mean, but there are ways -- well, taking a step back, there are ways to mitigate a lot of these issues with the right technology and engineering. And I am not going to be -- I am not an expert in how to do that. So that's not my expertise. But I know that it can be done if engineers -- and there's enough support and resources to make it happen in ways that can be more environmentally sustainable, you know, just safer for people and for animals. But it's not the priority unless the community makes sure that it is. It's got to be that the people say, "This is what we want." The counties say, "This is what we want."
[03:30:00] Speaker 1: Right. I mean, it's not a zero-sum game where you say, "No AI data centers across the board." You're saying, "Innovate the safety first, instead." And why are the fluorines -- how is that -- is that runoff in the water? You use the fluoride -- fluorines in the water? How is that used?
[03:30:20] Speaker 14: Well, the -- they use this -- cooling chemicals, which have fluoride. So one of the issues with data centers is that it is contributing to PFAS material manufacturing, be it in the semiconductors or in the materials that they use directly in the chemical cooling, without caps on that. Some states have caps for certain materials, but there really needs to be just a broad look at the whole thing, and how do we do this without creating more forever chemicals? Because it might not happen that where the data center is, is where the waste from any industry goes. It might go somewhere else, right, to another country, to another state, but it's going to go somewhere.
[03:31:12] Speaker 1: Well, you make a good point. If you read the book -- is it Red Cobalt? Yeah. That was an expose of cobalt mines in the Congo. And so that is a component of a lot of LED batteries or, you know, EV batteries. It's in most laptops and cell phones and things like that. And the pollution of these areas, you know, happens in a concentrated manner. So if we're demanding more of that, we are an unwilling participant in, you know, in polluting other places that we don't ever have to see. So, yeah, is there an industry effort to reduce dependency on these things? Because, you know, you can't just happily walk around with your cell phone and then know, "Oh, sometimes, you know, young kids in the Congo get buried in mines, mining this with their hands." That's fine. It's clearly not fine.
[03:32:14] Speaker 14: Right. I know. And the little children climbing in mines and the dust and just cobalt and all the minerals, you know, they say in our electronics is the whole -- all the Earth's minerals are in one phone or one device. But the companies really need to be addressing that in their supply chain. Again, it's about we, the consumers, can push the companies to do the right thing by saying -- by elevating the issue. So with -- be it the cobalt or the minerals as well as e-waste, these are issues that are not really addressed as they should be. There's just so many -- you'll have contractors and contractors and contractors. The supply chain is so fragmented that it's very -- the companies will say, "Well, we can't -- we can't do it because we have, you know, this person -- all these people, all these companies at each point and we just can't track it." And we just have to say, "No, you need to start tracking it. It needs to be tracked. We need to know that we're not poisoning other communities when I buy a cell phone or buy my electronic." Right. This can be done with awareness and with really, you know, policy -- policymakers putting it forward.
[03:33:37] Speaker 1: Yes, but here's where politics come in because so many of those components are manufactured in Asia. Asia has a lot of the direct contacts, you know, for these components -- cobalt, whatever it might have, whatever it might be. You know, the United States is sort of hands-off because we sanction, you know, these countries. So we're not even trying to work alongside them. And there is no regulation specifically of maybe these Chinese-owned mines of cobalt in the Congo. And we don't have any say over that. And we can be upset at our own regulators, but we have no -- and it's a different ethos. The Chinese investment is that, you know, anything that leads to prosperity will ultimately rise all tides -- rising tides float all boats. And that's something that we don't -- that's not our -- that's not our values. And so when we have this East versus West manufacturing supply line, nothing we do as Westerners will make sense, will make any difference as long as it's that way. And I hate to -- I'm asking you to respond to something that I've just told you is futile, but maybe you have a different take on it.
[03:34:53] Speaker 14: I'm sorry to ask the question that way. I hear the challenge here completely. So I don't think we can take everything on all at once. You know, it's like at the same time that I -- that I always propose, like, we need to have a conversation about the technology as a whole and what we're doing and how do we do this better at every point of the supply chain, going from the minerals to the manufacturing in Asia to the usage to the e-waste. But we also need to look to our communities and how we're being directly impacted. Because I believe that if we can get local communities -- which it's happening -- I mean, it's happening all over -- to be saying, hold on, you've got the air pollution issue. We know that from Virginia, where studies have shown air pollution hotspots from the data centers. We've got the water issue. We've got the EMF issue, which is rising up all around. And we can start to have, you know, holding the companies accountable. And we can't do it all at once. But you can start with your community, see what's going on. Are you getting a line? Are you getting a data center? And do you have an ordinance? I mean, like what I tell people who ask what they can do, the first thing is, if the data center company wants to come to your community, is there a permitting process for data centers? Most communities don't even have that because this is all happening so fast. Like in our community, they had a communications, it'd be the same as putting up a cell tower. Well, hyperscale data center is not a cell tower. So we need to have a different set of requirements and we need to get that in place. So I think there's a place to start with this. Okay.
[03:36:40] Speaker 1: So that's a more optimistic way of thinking about it. Because I'm like, we can't. Like we can't control the world. We can't respond to, you know, Chinese supply chains. And in fact, our leaders refuse. They probably could, you know, work better with China. They refuse to because of the political currency it gives them to stand against China. And, you know, I'm not an anti-China person at all. I'm saying our diplomacy has been utter crap. And so we can't solve these problems. We're refusing to because we'd like to go to war with China. So you're saying try and keep your eyes on your own paper because in small measure we can at least protect our own communities. What are some of the other efforts that you think that we should put our attention to now?
[03:37:25] Speaker 14: Well, there's the getting an ordinance in your community. So the first step is getting a moratorium to get the ordinance. Because if you don't have a moratorium, companies can come in, put down their applications, and then you won't have recourse when it's built. Because once it's built, it's there. That's the first thing. Talking to your officials about this. One of the things that I'm working on is a briefing on what states have done on the issue of powerline EMF. So only a few states, and actually New York and Florida have, I don't want to say the best, but they have the best in the sense of limits and transparency on the EMF issue. So, you know, this is a non-partisan issue, okay? And getting, if your state does not have regulations on how much magnetic fields are about to be emitted and also being informed about it. So if you get a line that's coming in, the folks I talked to in Maryland, they can't get the company to tell them what the levels of EMF would be with the line that's going to go right on their property. Now, how is that acceptable? Right. Everyone should have access to that. So that, so the issue of transparency. So at ehsciences.org and our organization, we're putting together resources on, for your elected officials. So they know what states are doing what. And my, my challenge is, can you, can you do better? Can you at least do what these others, what New York and Florida are doing and do it even better? Right.
[03:39:09] Speaker 1: And so where would you start then as city council in your area?
[03:39:15] Speaker 14: Yeah. Yeah. Yeah. I'd start with your local officials. And local officials are, they're writing resolutions opposing, you know, going forward without proper safety studies. They're asking, what are the EMF levels? Their school board saying, we, we oppose this transmission line going for the data centers. It's not even, this data center is not even in our community. Like there is no benefit to our community from these massive lines being put in.
[03:39:47] Speaker 1: Now my skeptical mind though, would say politicians who give lip service to this, because I've, I've interviewed plenty who say, no, I'm very much against AI dentists in Florida, but then are funded by a Palantir or some kind of big business. So how do we look out for that?
[03:40:05] Speaker 14: I think we just have to hold people to be accountable and call for reform. You know, it's not being anti-technology. It's just reform, oversight, accountability. And we're seeing a lot of behind door things that are happening in many different communities. And that's, that is the challenge right there. What do you mean by that? A lot of lip service.
[03:40:31] Speaker 1: Yeah. What do you mean by that? Behind closed doors?
[03:40:34] Speaker 14: There are NDAs that are being signed and decisions that are made where the community hasn't been informed about what's going on, happening all over. Yeah. How is there an NDA? I'm kind of like, wait, how is that even happening? Like there shouldn't be NDAs on this issue. Everything should be all aired publicly. Right.
[03:40:58] Speaker 1: What do you mean by what kind of NDAs would they sign about with local officials or about research that they have?
[03:41:09] Speaker 14: Oftentimes it's about the proposals.
[03:41:10] Speaker ?: Oh, okay.
[03:41:10] Speaker 14: Like, so that when the community finds out about proposals, what they also find out is that their officials knew about it well in advance. Uh-huh. Now the industry will say, and there is some, you know, they'll say, well, we don't want to tell everyone what we're doing all the time because that's part of our, you know, we have to keep our business plans tight until we're ready to let them go. But what happens is by the time the communities hear about it, their officials have been seeped in what the industry has presented as a need. And then they're challenged, not in all cases, but in some cases to help their officials understand why the community is opposed. And some communities have turned over their councils for moving forward on the data centers without including them in the conversation. Yeah. You know, they're like voting them out.
[03:42:14] Speaker ?: Right.
[03:42:15] Speaker 14: That's what's happening.
[03:42:16] Speaker 1: Well, yeah. So then you need to be an informed voter. That's definitely one thing we can do. Interestingly enough, this cause has been elevated in the public eye because of Erin Brockovich, famously from the Erin Brockovich movie where she was played by Julia Roberts. And because she was not a lawyer, but a legal assistant who stood up for the rights of people being poisoned in a California community. So now she has launched a public reporting platform called the Brockovich data center reporting project with a nationwide map of operational proposed and under construction AI data centers. What do you make of this?
[03:42:56] Speaker 14: I think this is really important. You can people are writing down there. They're getting the information out about what's happening in their communities and what their concerns are. And yeah, that she's elevating it.
[03:43:09] Speaker 1: Right. So she's not presenting herself as anti-AI. She's presenting herself as pro transparency, you know, so that these communities have informed consent about what's being put in their land resources and water resources. And so is that a good resource? Where else do you think that people can, you know, stay informed on this issue?
[03:43:32] Speaker 14: Yeah, I think that's a great resource. It still has, you know, people this just she just opened up that portal where you can submit. So it doesn't have all the situations that are happening around the country. We have at environmental health sciences a list of resources as well. And I want to go down to them. There is it's the Environment and Energy Study Institute. The Environment and Energy Study Institute has a series on the environmental impacts of data centers. The Food and Water Watch and the Sierra Club are doing a lot of work around water and environmental impacts. And of course, environmental health sciences. We have a newsletter, an EMF newsletter. You can sign up with us. And there are in any community, whatever state you live in, if you just do a little search, you're going to find a local group working on this. And it's really important to find, you know, find your neighbors who want to get involved. And I would say start with transparency, because that's if we have transparency, then we can start to work this out. That's that's the first step.
[03:44:43] Speaker 1: One more question I have for you is about the San Francisco 49ers. That is my home team. I am a Niners fan. And the story goes that because their training system, their training center in Santa Clara is so close to these industrial places with data centers that they get hurt more often. And the data does show that they are very prone to injury. Now, that's not an excuse as a Niners fan. What is the real data about this? Is this just something that fans use or is there actually something there?
[03:45:17] Speaker 14: Well, the situation is that their practice facility is right next door to a substation. And by the way, also massive power lines, both above ground and underground. So there's the substation, the 49ers playing field, and then a Santa Clara youth soccer field. And they have levels, Milgauss, EMF levels that are well above the levels associated with childhood leukemia, with miscarriage, with other health effects. And also there's oxidative stress, which can affect your body in all kinds of different ways. I can't say, and I don't know that anyone can, is the cause of the high rate of injuries of the players, and also the healing time that it takes because of that substation. What I can say is that those levels are well above levels that many countries have as their policies around in order to protect the public. So I went down to, I was in San Francisco last month, and I have a meter, and I went down there to measure. And I was in right in front where the playing field is, and I measured those numbers of from 10 to 50 on the ground to 17 at the soccer, where the kids' soccer place is, their soccer fields. And I was astounded. I mean, those levels are really, they're really high in terms of, as a public health, you know, internationally, what other countries are doing. The Netherlands, they would buy up land that had those levels that would not be allowed. You wouldn't be able to put your home there or to build anything there because it would be considered, because of those levels, they would want to have homes further away. And there's several European countries where they call that new situations. You can't build. Yeah. That they have. So, but I have some news. Okay. Okay. I just heard this morning that the 49ers is talking about moving their playing facility because they say they need more room. And they say it's not because of the EMF. I'm not sure I believe that. I actually think the work of those who are working on it. I was down there. I took a video. I've been getting my videos out. Peter Cowan, who started it with his Substack post, was just down there giving a talk. And I'd like to hope that the players and the workers are actually taking care of their health. And the next step is that the Santa Clara city protects the kids and addresses the issue on the soccer fields. That's crazy.
[03:48:03] Speaker 1: So, yeah. Who would, as a sports agent, want their client to go to the 49ers if there's a higher risk of injury? And then, like, yeah, you'll go there. You'll make a million dollars, but you'll have, you know, knee surgery in two years or something like that. And you know what? Because I grew up in Fremont, California, where the Teslas are made, it was known that if you bought a house in nearby Alviso, that it's an industrial wasteland. It has been for decades and that you have to, like, sign documents saying most people don't want to live in Alviso because of this. It's, you know, industrial contamination, groundwater pollution from the Silicon Valley. It is the hotbed of pollution and now AI data centers. So this is not a new issue. This is something that people from the Silicon Valley have known for decades. We knew this in the late 80s about Alviso. And so it doesn't, it's something that should not be considered a crazy part of the conversation. And you hear people saying, like, oh, that's just for conspiracy theorists. But if you can measure the EMF, you can see that it's above acceptable levels in several places. Then would it stand to reason that not just cancers, but, like, why would someone get injured, do you think? I mean, I know you're not a doctor, but conjecture, is it because, like, weakened muscular function or something like that?
[03:49:27] Speaker 14: Yeah. Well, I mean, if there's inflammation or your body is not as resilient as it could be, there can be impacts from that. So there are a lot of ways that electromagnetic radiation affects us at the cellular level. There are cellular impacts. And it just makes sense not to have your place of work, which is what it is for the players, for the, for everyone working with the team, even the security guards that I met down there. You know, they're standing right there at the high levels. That's their job. And, you know, how, how does that make sense? It just doesn't have to be that way. It's like, let's just do it where that's not a layer of exposure. And speaking of the, the contamination, there are a lot of studies that have shown synergistic effects. So when you have the combined air pollution plus non-ionizing EMF, that then you can have tumor promotion or increases in the effects that they study, depending on the study. And so it's really the total, your total body burden that you want to think about. And any one thing can be that, you know, too much in the bucket for your body. We don't always know what that is. We're complex, right? We're, our bodies are like an orchestra. Right. With all kinds of things happening, any one thing can change the whole fabric.
[03:50:57] Speaker ?: Right.
[03:50:58] Speaker 1: But bringing this back around to Erin Brockovich, this is a litigation nightmare. Yeah. I mean, we don't know where, because if there was proof that they refused to study it, or there was proof that there was concerns, and they turned away from it, and they continued to have people getting hurt or sick, then we do, in fact, have the exact situation that the Erin Brockovich film was about, a company that knew, and kept it going, and at the, you know, to the demise of human health. And so you can see that industry would be motivated to solve this, especially in litigious California, if not by human humanity, then by the big dollar that does not want to be subject to litigation. Right.
[03:51:43] Speaker 14: Yeah. I mean, well, let me tell you what happened. So when the, when this first came out, that there were levels there, and Peter Cowan did his Substack post, which got millions of views, and, you know, it's covered all over this, quote, conspiracy theory, and so forth. The company hired, did their due diligence, hired a company to come and do measurements. That report has been secret. That's why I went down there. I was like, what do you mean it's secret? It was kept secret. And they said, it's a nothing burger. It's 400 times the safe zone, said the team GM, general manager said on news. It was covered in sports illustrated all around, but yet they never shared the report. So that was the, so they did, they got this report, which obviously just concluded that the levels were lower than the ICNR, than the industry limits that I talked about that are just for nerve stimulation and, you know, zapping your body. And they never released it. So I, yeah, there was just a complete lack of transparency about what happened there, that they might argue that they got levels tested, but nobody gets to see that, which is unacceptable, especially with those soccer fields right there. And the people, the workers, and the other thing I should mention is, you know, there is no limit. There is no limit for workers normally with toxic exposures that are regulated, that have effects at certain levels. You have OSHA and NIOSH and, you know, limits, but there is no EMF program in the United States to characterize the levels. Like what are they being exposed to? What is safe for an eight hour work day? And that's, that's a lot of time for the, not just the players, but all the other people involved in that facility. That's their health on the line. Right.
[03:53:36] Speaker 1: Yeah. That's terrifying. Well, thank you for telling us these stories. And, you know, I think your take on it is a lot more optimistic than mine. So I appreciate talking to you because it does seem like there are people making real demands for transparency rather than just throwing their hands up about international diplomacy. So your way is better than mine. That's why we bring you on. Thank you so much. My guest today has been Theodora Scarato. She's the director of wireless and EMF program at the environmental health sciences. I hope you'll come back and tell us more as this story develops. Thank you so much for having me.
[03:54:11] Speaker 3: Thank you so much for watching Redacted. We'd love for you to subscribe to the channel. It's totally free if you want to follow us or subscribe. And if we brought you any value at all, please consider sharing this video with a friend or a loved one on social media. Thanks so much. And we'll see you next time.