This is On the Media. I'm Brooke Gladstone. Toward the end of my conversation with Geoff Hinton, he touched on a couple of things that need a little more explaining. One of them is AlphaFold.

Geoffrey Hinton: Which predicts the 3D shape of protein molecules from the sequence of bases that define the molecule.

Brooke Gladstone: An important development because protein misfolding is known to contribute to the pathogenesis of diseases like Alzheimer's. AlphaFold is an AI system developed by DeepMind, a subsidiary of Alphabet.

Speaker 1: Now a couple of days ago, DeepMind has announced that its second iteration of the AlphaFold system has "solved the 50-year-old grand challenge problem of protein folding."

Brooke Gladstone: There are other labs working on this software too. This is University of Washington, Seattle Biochemist, David Baker.

David Baker: We've also designed new proteins to break down gluten in your stomach for celiac disease and other proteins to stimulate your immune system to fight cancer. These advances are the beginning of the protein design revolution.

Brooke Gladstone: Hinton also described his fear of autonomous lethal weapons powered by AI. I followed up on that with Matt Devost, an international cybersecurity expert who started his career hacking into systems for the US Department of Defense back in the 1990s. When I first spoke to him in January, he gave me the beginner's class on autonomous lethality.

Matt Devost: Where once a target has been designated by a human decision-maker, the weapon will have autonomy to operate and get there. It'll navigate the terrain properly, make decisions based on how it achieves the impact of that target, for example.

Brooke Gladstone: There isn't a kid back in Oklahoma running it on a board. It can make a decision and change its path based on its own information.

Matt Devost: And probably much more quickly than a human drone operator would be able to achieve. Now that doesn't mean that we're going to take humans out of the decision-making equation with regards to what gets targeted.

Brooke Gladstone: Not yet, anyway. [chuckles]

Matt Devost: Not yet, but in how it achieves the mission and the ability to basically act in a swarm capacity and make decisions amongst themselves, adjusting their mission profile based on the swarm intelligence.

Brooke Gladstone: Yes. That's when multiple weapons are simultaneously operating and communicating with each other-

Matt Devost: With each other.

Brooke Gladstone: -making decisions based on each other's behavior. That's drone technology, but how would the next generation of swarming weapons behave?

Matt Devost: What gets really interesting is if they start to demonstrate an ability to operate in a way that is more humane or cognizant of the human impact than a human decision-maker would be able to do. In which case, now you start to have some autonomy with regards to the targeting itself.

Brooke Gladstone: Can you give me an example of that?

Matt Devost: Trying to target this facility, but we're trying to minimize the potential for collateral damage, and the drone is aware enough to know that a bus just pulled up next to the facility, where there is an autonomy that is built into the weapons that allows them to make a decision or abort a decision or delay a decision based on a situation that even a human being doesn't have the capacity to make that decision because it's changing so rapidly.

Brooke Gladstone: Right now, we wouldn't allow weapons to autonomously target, but that could happen one day, and it brings up images of Dr. Strangelove and Fail Safe.

Matt Devost: That is going to be a concern. I think we've articulated pretty clearly, at least at the US government level, that humans will remain in the loop as it relates to targeting other humans. It's different if you're targeting drones, or you're targeting the communications tower, et cetera. We could reach a point in which the drones are more efficient and more humane decision-makers based on the AI capabilities and analytics that they're able to achieve, the same way that we might someday decide that we should allow only self-driving cars. Humans do a really good job of killing a lot of ourselves in motor vehicles every year. There may be a point in time in which the AI is a more sensible and objective decision-maker.

Brooke Gladstone: Obviously, these new AI tools will have an impact on intelligence gathering and collection, and you say that for you, ChatGPT was a wow moment.

Matt Devost: It was for a couple of reasons. One is, it interacts with you based on questions, and you're able to refine it like the same way that you could refine your conversation with a human being. "Tell me more," or make a counterargument. It also does a great job of understanding nuanced concepts.

I gave an example. A friend of mine, Bill Kroll, who used to be Deputy Director of the National Security Agency, had a quote a few years ago where he said, "The cybersecurity industry has a thousand points of light but no illumination." I asked ChatGPT, "What do you think Bill meant when he said that?" It gave an incredible answer. It said, "When someone says that the cybersecurity industry has a thousand points of light and no illumination, they are expressing frustration with the fragmented and disorganized nature of the industry. The term 'a thousand points of light' refers to many different players and stakeholders, including government agencies, private companies and individual security experts. Each of these players brings their own unique perspective and expertise to the field, but the lack of coordination and collaboration among them make it difficult to develop a comprehensive and effective approach to cybersecurity."

Brooke Gladstone: Holy cow.

Matt Devost: That is an incredible response, right? You can tell ChatGPT, "I want you to give a ranking or rating about how confident you are in your analysis. I also want you to provide a counterpoint. Plus, I want you to provide recommendations as to what we can do about this." If you go in and ask it, "What is the probability that Iran will attack a US bank with a cyber weapon?" It gives you a response that flows almost exactly like you would see in an intelligence briefing that might be delivered all the way up to the president's daily briefing.

It's fascinating that it is able to not only query all this knowledge and come up with these great responses, but it can also frame the response from the perspective of the audience expectations.

Brooke Gladstone: But it has been shown over and over again that ChatGPT is fundamentally a people-pleaser.

Matt Devost: Yes.

Brooke Gladstone: It doesn't care if it's true or not.

Matt Devost: Yes.

Brooke Gladstone: It will invent sources in order to give you something that has the exact format you're asking for. You can't trust anything that ChatGPT says, so how can it be helpful in intelligence gathering?

Matt Devost: Yes. The Intelligence community won't use ChatGPT based on ChatGPT's existing training dataset. It'll use it based on data sets that are proprietary to the Intelligence community. What we're about to see in the next year and in the coming years is these domain-specific versions of ChatGPT where I control the training data, or I tell it that it doesn't have to be the human-pleaser. It doesn't have to be conversational. It should use the same heuristics that it's using to derive these answers, but if you don't have a source, you don't invent it. You can't make judgments that aren't based on a particular source. It's a very quick shift to move away from that inherent bias to using the capability in a way that's very meaningful.

Brooke Gladstone: Give me an example. Would it interrogate a prisoner of war?

Matt Devost: I don't know that it would interrogate a prisoner of war. Although, you could certainly envision where it might be used to augment a human's questions that they're asking. I think it'll probably get really good at threat assessment, making recommendations for remediating vulnerabilities. I think analysts might also use it to help them through their thinking. They might come up with an assessment and say, "Tell me how I'm wrong," and the AI serves as almost the Tenth Man Rule, if you will, where they're by design taking the counterargument. I think there'll be a lot of unique ways in which the technology is used in the Intelligence community.

Brooke Gladstone: How imminent is this kind of technology?

Matt Devost: It's incredibly imminent. The technology clearly exists. We're going to see, with version 4.0, a version that is much more constrained with regards to not making things up and is much more current. One of the existing flaws right now with ChatGPT is the training data ends in 2021. If you now start to have it where there's training data current as of whatever it found in the models this morning, that starts to get very, very interesting and means that this technology can be applied around real-time issues in the next year or two years.

Brooke Gladstone: Another wow moment you had was a challenge several years ago by DARPA, that is the government agency that drives a lot of amazing technology. It gave us the internet, for one thing, and GPS. Tell me about what happened at that DARPA conference.

Matt Devost: Yes, so that was fascinating for me. In cybersecurity, we have these contests that we call Capture the Flag contests, and they really are ways for people to compete to demonstrate who's the top hacker, who's the top person at attacking systems. You hack systems and you take control of them, and then you have to defend the flag. You have to make sure that you patch it and you fix it and you prevent other people from taking over that system and booting you off.

Brooke Gladstone: This is a cyber war game, essentially.

Matt Devost: This is a cyber war game, yes. In 2016, they brought the finalists out to DEFCON, which is the largest hacker conference in the world, in Las Vegas, and they had the six finalists compete. That was another aha moment for me, where I felt like I was living in the future, similar to the way I felt when I encountered ChatGPT at the beginning of December.

I started my career in 1995. It was my job for the Department of Defense to break into systems and show how they were vulnerable and help system owners patch those systems, and here I was being completely replaced by a machine, and the machines were very creative and fast. That's an uncomfortable feeling [chuckles] for somebody in the cybersecurity industry, not because of the displacement, but because of the lack of explainability or the lack of understanding with regards to how resilient the patching is, or making sure that the AI doesn't lose control of its objectives and do something that ends up being malicious behavior. It's definitely a Brave New World in that regard.

Brooke Gladstone: How do we ensure that these weapons are safe to deploy? How do we ensure that they don't commit war crimes?

Matt Devost: Yes. I think we'll have clearly defined ethics around the use of artificial intelligence as it relates to things that could impact human lives or human safety. What's going to be disconcerting is when we encounter adversaries that don't have the same ethics, and do we end up having to unleash some sort of autonomy in our weapons because our adversaries have launched autonomous weapons against us? Put in a position of having to violate some of our principles because it's the only way to appropriately defend ourselves.

If we dig a little deeper though, there are some other core risks. These technologies all run on systems that are vulnerable, so we have an underlying responsibility to make sure that the infrastructure is robust and is secure. You also need to make sure where the training data has an open collection model, ChatGPT draws intelligence from the internet itself, that you are aware of adversaries that might try and pollute that environment. What if I decide that putting blog posts up, writing websites, taking out advertisements, going on Twitter to pursue a particular narrative that will influence the decision-making of a particular AI?

Then the third area is going to be around the robustness of the algorithms and making sure that we have removed bias. I think that will drive, in the Department of Defense, a requirement for what we call explainable AI. The AI has to describe to us in understandable terms how it arrived at that decision.

Brooke Gladstone: The debate over the drones was that Americans wouldn't be killed if we used them. Critics say, we've overused them because the cost to us is so low. We've already been able to destroy the world many times over for 70 years, but the ability to be more surgical in our destruction and even to hand off our own autonomy to machines that may well be smarter than we are is a terrifying prospect.

Matt Devost: It is, right? We need to figure out what levels of agency we want to retain. As it relates to warfighting, we've said, well, we want to maintain the decision-making as it relates to other human beings, but what if, over and over again, AI makes better decisions, safer decisions than human beings? Do we abdicate that responsibility? Do I lose the agency of being able to interpret what is misinformation with my own brain, or do I abdicate it to an AI system that does it for me? That is definitely going to be one of the fundamental questions that we face over the next decade; where do we retain agency, and where do we decide that the machines can do it better?

Brooke Gladstone: You seem to be suggesting that it may turn out that humans are far more dangerous.

Matt Devost: In some domains, the humans might be more dangerous.

Brooke Gladstone: I'm thinking of the Cuban Missile Crisis, and how the tape suggests that John Kennedy was pretty much alone in wanting to make that deal to take American missiles out of Turkey so that Khrushchev would take them out of Cuba. I'm just wondering if there had been an advanced chatbot advisor in the room, whether he would've stood with Kennedy or not.

Matt Devost: Yes, it makes you definitely consider what does the training data look like for a decision like that. I don't want us to think that I'm a fan of abdicating control to the machines. I'm certainly not. We have to figure out which are fundamentally human decisions and which are the ones that can be automated or augmented.

Brooke Gladstone: It depends what you think of human nature, right? If there is a machine that is developed to help us fight the best war, is there a possibility that that machine may say, best not go to war?

Matt Devost: As long as we get it to understand our objectives and our constraints. You could sit and say, "Would the world be a better place right now if Russia were run by some sort of autonomous AI?" Possibly, but if the AI has been programmed with the same biases, the same tendencies, the same ambitions, it might be more efficient than Putin in perpetrating these atrocities.

Brooke Gladstone: Matt, thank you very much.

Matt Devost: Yes, of course. It was my pleasure. I enjoyed the conversation.

Brooke Gladstone: Matt Devost is the CEO and Co-Founder of the global strategy advisory firm, OODA, spelled O-O-D-A, LLC.