I've Got Questions with Sinead Bovell - AI Is Moving Faster Than Governments Can Think | Anna Makanju (OpenAI's VP of Global Affairs)

Episode Date: October 30, 2025

In this episode of I’ve Got Questions, I sit down with Anna Makanju, Vice President of Global Affairs at OpenAI, to explore how governments around the world are racing to understand AI’s implications, the geopolitical tensions shaping its regulation, and what it will take to ensure this technology benefits every nation. We discuss how AI could be immensely beneficial to humanity, but why Anna believes it won’t happen by default; the urgent challenge of unequal AI access and the risk of leaving communities and entire countries behind. 00:00 – Introduction 01:10 – Will AI Be a Benefit to Humanity? 02:00 – Can the World Cooperate on AI? 03:30 – AI as a Tool of Global Power 05:00 – When Companies Rival Nations 07:30 – How Do We Keep Half the World from Being Left Behind? 09:20 – The ChatGPT Moment That No One Expected 11:00 – Inside OpenAI’s Global Tour 13:00 – How World Leaders Reacted to AI Demos 15:00 – Why Governments Focus Only on Deepfakes 17:30 – The Private vs. Public Conversation on AGI 19:00 – “It Could Be Immensely Beneficial — But It Won’t Happen by Default” 21:00 – The Problem with Policymakers Who Don’t Use AI 23:00 – Fear, Misuse, and the Lawyer Who Used ChatGPT in Court 25:30 – When AI Actually Saves Lives 27:00 – What Happens When AI Enters Government 29:00 – Balancing Risk, Access, and Innovation 31:00 – Why Emerging Economies Are More Optimistic About AI 33:30 – The Future of Jobs and the Need for Reskilling 36:00 – How Fast Can Humanity Adapt? 38:30 – The Case for a New Social Safety Net 40:00 – Preparing for the Next Decade of Change 42:30 – Why Governments Must Act Before a Crisis 44:00 – Smarter Models, Safer Systems 45:30 – What Comes After Regulation 47:00 – Building a Future That Works for Everyone Listen to the show on other platforms: Apple Podcasts – https://podcasts.apple.com/us/podcast/ive-got-questions-with-sinead-bovell/id1841491246 Spotify – https://open.spotify.com/show/2fwK9NSJGXlFdVkYZ14a8O Follow my work here: Website: ⁠https://www.sineadbovell.com⁠ Substack: ⁠https://sineadbovell.substack.com⁠ Instagram: ⁠https://www.instagram.com/sineadbovell⁠ LinkedIn: ⁠https://www.linkedin.com/in/sineadbovell⁠ Twitter / X: ⁠https://twitter.com/SineadBovell⁠ YouTube: ⁠https://www.youtube.com/Sineadbovell⁠ TikTok: ⁠https://www.tiktok.com/@sineadbovell

Will AI be a benefit to humanity? This could absolutely be immensely beneficial to humanity. I just don't believe that that's a default world. We have a handful of companies whose annual revenue and market capitalization exceeds most countries. How could government be using this technology in a way that would help transform a democracy, a country? In many places in the world, almost all of your infrastructure of your life comes from the government. And so if you can improve this, you can imagine how much you can improve most people's lives. Having AI in government, is there kind of a conflict of interest there?

And especially if you're advocating for it, you're also profiting from it. And if AI still makes mistakes and things, does that put the public more at risk? I have some hope that we understand the critical need for global guardrails. The place of people's minds, of course, one is like, deep fakes misinformation. Obviously, two really serious problems, but a sliver of the surface area of this technology. What I'm most focused on is the most sort of catastrophic or problematic. uses. So whether countries will target each other's critical AI infrastructure. This is going to be a technology. We rebuild society on top of. And when you don't get access

to a general purpose technology like electricity, like the internet, we see what happens and how do we not leave literally half of the world behind. Welcome back to I've Got Questions. I'm your host, Shenei Bovell. Today I'm sitting down with Anna McConju. She is the VP of Global Affairs at OpenAI. And not only does she have an exceptionally impressive background, both academically and professionally. She is exceptionally grounded in how she approaches artificial intelligence and the impact it's going to have on our world. Are policymakers keeping up? Do they understand the magnitude of this technology and how they should be steering it? Anna has those answers. Today, we lift the veil on what goes on in those types of rooms, where Anna sees this technology going,

and how she thinks society should be preparing. Is it realistic to expect global cooperation, on artificial intelligence, given most countries now view it as a pillar of national sovereignty, as a pillar of national security, and most countries aren't in a state of agreement on a lot of things, even allyship? It depends on what kinds of issues you want to tackle. If you want to tackle sort of the content of what AI addresses or how it's going to be, you know, utilized probably not. But I think what I'm most focused on is the most sort of catastrophic or problematic uses.

So how do we think about, you know, what whether countries will target each other's critical AI infrastructure? I actually think that there are areas where we are just as concerned as China is about the way that each of us will use these technologies in a way that may actually lead to. And I think that, you know, China is. obviously investing and advancing at a rate. I mean, usually international agreements are possible when countries feel like they're approximately at parity in a technology. So if that is something that both governments believe, then I think that there is more likelihood that there

is some area for consensus. So you're saying because China is actually moving so quickly, and because they're almost pretty much on the heels of America, I mean, I think that they passed AI citations and patents this year. They surpassed Europe. they suppress the U.S., it actually brings more incentive for both parties to negotiate and to figure out some consensus because they both are staring at that frontier, staring at what could be possible with these systems, and recognize it could be some mutually assured destruction in some ways unless we both get to the table and figure out what are the rules of the road here? My optimistic fuse, yes, that that is the case. What's the pessimistic one? Just that, you know, we're no longer really able to negotiate international. national agreements around anything, which, you know, I suppose is also possible.

And I think that that's potentially also a state that we prepare for or think about. And I mean, there's the track one dialogues, which are more overt in countries are planning to meet. And then there's the track two dialogues where it's maybe not necessarily a top of government priority, but scientists and private companies are still trying to engage with foreign governments or foreign countries. Do you think that both of those are happening at the same rate? Or now is it AI companies and scientists themselves trying to meet with their peers in other countries because they uniquely see what is at stake?

There's definitely, I think, some track-to diplomacy that's still happening. Obviously, in general, there is much more secrecy and understandably less openness around the development of this technology. But at least, I mean, I am aware of several track-2 discussions that are happening. So that is encouraging. How do you plan then if you're open AI and you're planning to do business in a country or grow business and then the relationship that country may have with your government changes, sometimes monthly, yearly, how do you even plan then to engage with a different country if you don't know if your country would be seen as an ally or an adversary

in a couple years or a couple months? This is a great question. I mean, certainly there are relationships that we've had now for a long time. And so we try to maintain those outside of the, you know, current geopolitical tensions. And it's, you know, I think opening eyes advantage has been that they've continued to demonstrate the innovation and the utility of the tools and the safety of the tools. So that it's just an attractive offering no matter what is happening on the geopolitical space. You know, on the other hand, you've seen really interesting moves like Microsoft

that's effectively working, you know, kind of telling Europeans, we will fight for you and we will protect, you know, you know, U.S. run, but European-based infrastructure. So there's clearly, there are clearly things that companies are doing to try to reassure the customers in countries that are getting jittery about the geopolitical situation. It's a great point because the reality is tech companies and AI companies being kind of the frontier of the future

have this outsized role of power. But in an event where kind of the sovereign relationships between countries feels more uncertain, you do have a tech company that can then say, we will fight for you regardless of what we think is happening in the backdrop. And that's a really unique environment that we haven't seen before, ever. No, I mean, I do think that this is one sort of really key difference about our time is that we have a handful of companies

whose annual revenue and market capitalization exceeds most countries and they can exercise power in the global stage that is commensurate with a nation state. And so thinking about how that's going to alter the way that this all plays out is certainly really interesting. And I guess that can be a good thing

as long as you like agree with or in alignment with the companies that happen to be leading at that time. And speaking of the market cap of tech companies, I mean, if you are Sierra Leone or Cambodia or Nepal or Botswana, the GDP of your entire country may be less than a single AI project like Project Stargate. What do you tell these countries? What should they be doing? And how do we not leave? I mean, literally half of the world behind.

Yeah. I mean, this is an absolutely key question. and I think there's not nearly enough secure investment around this because at the end of the day, actually, a lot of the challenges to these countries really succeeding with AI are actually the old challenges. Access to electricity and the internet ultimately still is the major bottleneck to benefiting from AI,

not even getting to having adequate compute. So I just think there needs to be very urgent investment in just a basic infrastructure, but this is, you know, like one of the many sort of like collective action problems where who is going to lead this actually AI companies are not necessarily although you know we've seen some of the bigger companies

invest and Nvidia invest more infrastructure in a lot of these places but it's you know drop in the bucket compared to the need I know it yeah exactly general purpose technologies build on each other so who didn't get adequate access to electricity probably doesn't have adequate access to the internet and then AI and it becomes I mean each of them

are also life-sustaining, whether that is something like life support or just being able to access medical intelligence. And in some ways, if the current situation is zero access to a physician and in an AI world, you can at least ask some questions. That lack of access could actually be life or death in some scenario. So it is a collective action problem. And one that, I mean, unfortunately, it seems like the world is collectively paralyzed on a lot. lot of these issues. If we were to rewind the clock to November 2022, I think we can call it the chat chubby moment. Because even when we look at robots, people are like there's a chat dbtee moment coming for robots. Before you release this chat bot, what was the anticipation inside

Open AI? Did you think it was going to turn the world around? I mean, I think most people did not think that. We thought, okay, well, maybe we'll have to set aside like for 100,000 users. It was a research preview. So we thought, you know, some nerds will use this. And, you know, I personally could not have anticipated the fact that this would take off. I feel like I still don't know that I've seen a really thorough analysis of why that in particular captured people's imagination in the way that it did. And I'm wondering if social media has a role to play in this. Because even what we saw with some of the cryptocurrencies and things taking off so quickly, a lot of people are in a single space at a single time digitally. So when a few researchers, you know, tweeted about it at the

time, it made dissemination that much faster. I don't know. I think we'll have to go back and see, but a million people in five days and now 300 million a week, a week, I believe, use it. And then you and Sam went on a 25 city tour. What was the sentiment with global leaders at that time? Like, what are you explaining to them is about to happen? I mean, I think a lot of people just wanted to understand like what is happening where is this going what impact do you think it will have and how can we use it to you know make lives better for our citizens and of course you know what are the risks and at the time i i think that just you know there was so much less understanding of what exactly the technology was and what is the mental model people should use because at the end

of the day it is quite different it's very difficult to compare it to any other technology or existing tool. So, you know, part of the idea of this tour was also to listen, to understand what people were thinking and where their heads were. And I think also because of the time we were seeing that it wasn't just about the models, that this was going to be a huge infrastructure conversation, a huge energy conversation, and that all of these things were necessary not just having the software. The tour was just to try to understand kind of how governments were thinking about it,

but also just to let them know, like, this is real, and this is going to have a profound impact. And, you know, from the beginning in my role, my hope was that we could start to think about what is the infrastructure, you know, regulatory, societal, not just, you know, physical, that we need to ensure that this goes well. I just think none of us expect that we'd have so little time before this became so ubiquitous and, you know, so central. And what goes through your mind when you're sitting across, from a world leader, telling them that you are building systems that will one day surpass human intelligence?

Well, you know, I think that lots of systems that exist today already surpass our intelligence and our abilities. So it is much more that I believed that the really critical distinction is that we didn't figure out a way to collaborate between government and private industry and, you know, other key stakeholders ahead of time. This was actually one of my big takeaways coming to OpenAI from, you know, Facebook, is that this had to happen a lot sooner.

We had to be a lot more thoughtful about it. And also, we had to help people understand what the tools actually were. So a lot of what we were doing was just demos. Because I think it's very hard to just tell someone what something is. You have to show it to them. You have to make sure they're using it.

You have to make sure they're engaging with it. And that they know, like, what practically does this look like in real life. So we did a lot of that. And we tried to give, you know, governments a preview before something was out in the world. So it wouldn't be, you know, just like a complete surprise that this is happening. So the goal was just to create that understanding, to create that infrastructure of shared knowledge and that hopefully, like, neither they nor we have the answer, but perhaps we can come up with one in collaboration. I just feel like it nonetheless was so quick that it did not quite end up working out in that way.

And by the way, were some of the world leaders just completely stunned? Or was there a really surprising, I mean, what was the most surprising response from a world leader when you would show them demos? And you don't have to name names or countries, but was it just slow blinks? Was it do not compute, reschedule meeting? Yeah, I mean, I think one thing I realized is that, We had to really tailor the demos in the end towards specific interests or work of people. Because sometimes, you know, even when I was doing Dolly demos and I would show people, that's the image generator.

We would show this to people like, oh, you Google that. Like, no, no, no. This is an original image that did not exist that was created. 30 seconds ago. Technology. But I still think it didn't quite, because the nature of how this happened is so different than what people are used to. so they still didn't quite understand. In those days, pretty much the only thing that people's minds,

the place of people's minds, of course, one is like deepbakes, misinformation. Obviously, two really serious problems that are going to be exacerbated by this technology without the right infrastructure, but, you know, a, you know, sliver of the surface area of this technology. So part of it was just, okay, yes, deep stakes and misinformation are, you know, a very serious issue, but we have to talk about all of the other aspects of these tools. And that was one of the, I think, you know, main things that happened in these meetings is like, we just have to get beyond these two issues because there's so much else to talk about. People kind of zero in on it.

Well, I think one thing that you said, that's really important that I think people should really listen to. Governments are briefed on the capabilities of the technology. I think sometimes we feel on the outside, but do they know what's happening? We're kind of seeing what's happening. I mean, you sit down with governments and you tell them this is what this technology will be capable of. So why do you think we never hear from governments then, terms like artificial general intelligence, artificial superintelligence, which if you're not familiar, there's different definitions, an AI stem that is generally as smart as the average person at everything, and then AI stems that surpass human intelligence on anything. And I think fairly, AI companies are pretty transparent about that being the North Star. And of course, there's some profit motive. You have to declare that you're at least trying to get there.

So they declare that. I know governments are briefed on it. Why do we never hear them even use the term? We don't even, we're not transparent at all. I mean, I think, honestly, part of it is that AI is still not, you know, politically determinative of people winning or losing elections. And so I think it's people tend to try to talk about like the bread and butter issues, which this isn't yet. Yet. And so and I think people are, people don't quite know how to talk about it. But I hope to tell you a story, you know,

at the beginning of my job before most people were even aware of the existence of GPT3, which is what we had at the time. And I already felt pretty convinced. I was like, no, this is. This is. This is. Yeah, we're here. We've started. But Europe had been working on the EU AI Act at that point for, you know, four years because they started in 2016 with this report. And France had the presidency. And we went to just discuss, like, what they were thinking, show them kind of the latest on the technology and, you know, just exchange ideas. I mean, I think it was literally just me, being the only public policy person of Open AI. And as they were walking me out, one of the colleagues stopped me and was like, so when do we get to AGI?

And I was totally shocked because I didn't think anyone outside of San Francisco had uttered these rights ever. And so it's interesting because I do think there are people in these governments that have been thinking about this. There are. And it's more privately. Yes. And I know we've had conversations with them, but publicly, yeah, we don't hear yet. But maybe it's, yeah, these are really conceptual in some ways philosophical and in some aspect scientific concepts. that it's just they don't necessarily have the full lexicon or they don't want to make a bet. And yeah, it's not on the ballot yet.

I mean, we hardly talked about AI at the last U.S. election. I think I heard the word technology three times and the word AI once. But I don't think it's going to stay that way or it shouldn't stay that way. But I think it's also hard. I imagine it is very difficult if you're a politician. What are you going to say? Right. You don't, you know, like, what are the ideas?

What is sort of like the actual, like intellectual approach that is also politically relevant and palatable to your voters? And I think maybe whoever can answer that question will have a pretty big advantage or a pretty important platform if it can be answered. We'll need to be thinking about it because they will at some point, you know, they will have to answer this question. And you gave a talk a couple months ago, which I really enjoyed at the Colin Powell, school and you started your talk, you opened it with a question, will AI be a benefit to humanity? Will this turn out well for humanity? And your answer surprised me a little. It was, it depends. Why? What does it depend on? Well, what I'm trying to say is that I do think that there's a world in which this could absolutely be immensely beneficial to humanity. I just don't believe that that's a

default world that will come into existence without our thinking and working towards that outcome. I think that there is a world in which the way that this is currently shaping up, this could benefit only already wealthy nations, already wealthy companies integrating AI, already AI labs that are building it, but not actually diffuse further. And so that is something that we have to work at extremely hard. And I think some people might feel, you know, if you're at one of the most powerful AI companies in the world, one of the most important open AI, and you're uncertain about how it ends up for humanity.

I mean, if it doesn't depend on you, then who? I mean, of course, governments play a role. And even today when there is some uncertainty around how we build global consensus around some of these issues, we still have to continue doing that. We are in a unique situation because at the leading AI labs, we are thinking about these questions, and we're really trying to find solutions,

and we're really trying to bring them back to how we develop and deploy our tools. And I would say that that's not the case probably with any other transformative technology to date. I think we've always kind of just assumed that this wasn't our job or assumed that society would work it out. So the fact that at the labs we really are investing a lot in these questions is unique. And I am optimistic that it will make a difference. I mean, if there's one thing that we can take from the social media era, it didn't really go so well for all of us. I think we're still kind of free-falling through that. But we learned a lot about the decisions we don't want to make or what happened when you just end up playing whack-a-mole after things have already evolved to a point where it feels a little out of control.

So I think we are approaching AI differently. But I think the general public, we've seen all of the videos where policymakers seem to struggle with understanding business models on the Internet or the Internet. or the internet itself, do you feel like policymakers understand the magnitude of AI, what they're working with, and how to steer it? And it's not just regulated, right? There's also things that you want AI to be used for in a country. Do you think they're grappling with it and moving quick enough and they understand it? You know, I've had the wonderful opportunity to meet many senior policymakers over the course of my time at Open AI. And often you'll be engaged with someone who's really grappling with the implications of AI, obviously looking at legislation or other regulatory interventions,

and at the end of the meeting, they will say to me, like, I mean, I, of course, would never use this. And I'm just like, oh, my God, no, that's actually the only way you can understand the limitations, the opportunities, is to be using the technology yourself. And, you know, it's not quantum. It's like, you know, there's a free app you can download on your phone. So it's more accessible than ever. And why do you think they don't, they say that they don't want to use it? Like, they're scared of it.

they don't trust it. I mean, I do think there's a couple of things. One of them is even working at Open AI, keeping up with the way it's evolving and like how you can use it and what you can use it for, it's difficult because it's a very general technology and it's changing all the time. Essentially, like what is the limitation? What is its capability? Like something that six months ago, everyone believed that you could never do. It's now doing fairly well. And it's, you know, so I think that there is something that is, you know, very understandable there. I also think that there's an odd dynamic where there are quite a few critics. Like, there are many things you can criticize about this technology.

But there is sort of a subset of critics that gets a lot of press attention. Whose narrative is that, no, this isn't good? Like, it just doesn't work. Or, you know, AI companies try to tell you it works. They try to tell you it's really powerful. It's actually trash. It's wrong all the time. It's not human enough.

And it's whatever. And so I do think that, you know, when you're on the outside, you don't, who should you be listening to? Of course, AI companies have a financial motive to get you to, believe it's very powerful. So, you know, I think that that has been a limitation as well. I'm actually really glad that you said that because I believe as well, if people are too fearful or too pessimistic about a technology or something that's as important as a general purpose technology, they unsubscribe from it entirely. And that's when you miss the opportunity to act. And I think,

you know, my biggest fear with AI, it's not even that we do too much or too little. We just don't do anything at all. Because we've become so overwhelmed by the moment. And what separates AI from other technologies is general purpose. So when subscribing from it is like taking a resistance against electricity, there are, of course, unique risks and harms that AI presents that no other technology does. But this is going to be a technology we rebuild society on top of. And when you don't get access to a general purpose technology like electrically, like the Internet, we see what happens and who's on the wrong side of those divides.

And so, yes, you can give better feedback if you use it. but unfortunately if you're only hearing the negative side, you just opt out from it. And then that's kind of the worst case scenario for all of us. Yeah. No, I think you're actually highlighting something that has been a big concern to me, which is that, you know, communities that have in the past been harmed by other technological advances are often sort of also more fearful. And what really worries me is that, you know, it just exacerbates the potential for these communities to be loved behind. In that talk, I was sort of trying to make the point that what we really need to understand is how to maximize the utility of this technology for these communities.

Rather than focusing on just where it can be harmful, you actually have to focus on how it could be the most useful. Right. And even the people who talk about it being hype, electricity came out. It was a huge excitement. And then nobody used it for decades. And so that's just how these general purpose technologies work. They take time to evolve. And what are some of these use cases that you think? I mean, even if we were to stick with government and then the world,

how could government be using this technology in a way that would help transform a democracy, a country? For example, in India and Kenya, there are government extension services, which means that if you're a smallholder farmer, you know, like you're one person with a small farm, there is a government service that you can access where someone will come and kind of tell you like, goes, how you should plant your crops, and you know, this is kind of the type of irrigation that you need. And obviously, there's huge demand and very little supply. So we worked with one partner called Digital Green. When our models first became multimodal, which means you could put in, like, a photo of your crops and be like, what is this disease that is affecting my crop? And they had a bunch

of data where, you know, they could work with to answer that. I believe it went from $35 a year per farmer to $0.35. So you can imagine, like, how many more people you can serve. And now, actually, they're working directly with the farmers. And I've even seen testimonials, particularly of women, who are caring for families and they have a harder time, you know, like leaving and going somewhere to get this advice. And they're getting this advice directly. And it's been hugely economically impactful. I do think for government services, you know, we are working with a few governments right now to try to kind of centralize knowledge. So if you need, you know, a passport or you need to understand where you can get your benefits, you can do this very quickly.

in one place. And I just think that in many places in the world, almost all of your infrastructure of your life comes from the government. And so if you can improve this, you can imagine how much you can improve most people's lives.

But I would say where most optimistic is health. So Maz Brigham has this program where they're training neurosurgeons in Gambia. And nursing staff have about 100 patients overnight. So what they were doing is testing. Can our models essentially provide advice that is equivalent to their trained neurosurgeons.

And they found that not only was it the case that they could, the model actually caught errors. For example, one person, it caught that they were not receiving the antibiotics they need it. So, you know, it's saving lives already. I love the examples that you provided, because I think when you look at what it means to have access to intelligence or even a system that can read that can analyze something like financial advice. I mean, so many people in the world do not have access to financial advice.

A lot of people are even unbanked or newly banked because of now coming online with mobile phones and things. Being able to have a system that can help you understand what compound interest is, or even should I buy an automobile, a piece of farm equipment, or invest in livestock, or maybe something that reminds you, you know, you've taken out three loan payments on your phone. Do you want to plan to help you pay some of that back? Those are all the little ways that I think having a system that you're, that you can stream intelligence from can assist you with. I think where sometimes people feel pushback is having AI in government.

Is there kind of a conflict of interest there? And especially if you're advocating for it being in government services, you're also profiting from it. And if AI still makes mistakes and things, does that put the public more at risk? And I think that that's something that's less clear for people. Yeah. Well, first, we do have a number of limitations in terms of what our tools just won't do, no matter who the user is.

So that should provide, you know, some infrastructure to prevent the kinds of, you know, problematic use cases that a lot of people are concerned about. In January of 2024, Pennsylvania launched a pilot. And it was actually exactly the kind of pilot that I think governments need to do because some people think it's magic and it can do everything. Other people think it can do nothing. But the only way you find out where on that spectrum it is is by doing the reps and figuring that out. And I think ultimately also people are scared. They're scared this is going to replace them. They're scared that it's going to make mistakes.

But this is why you have to use it. They published a really good report because I think it was just very practical. It showed that every single person, including people who had never touched it before the pilot, just saved an hour or two a day. So in the end, it's really about government employees who are, of course, always under-resourced, just getting that time back to do higher order, more strategic thinking. It's not just governments. This is how commercial enterprises, and people should do it too. You should figure out where it actually makes sense and where you need to use your own judgment. I have to tell you the story because often, you know, the dumb mistake is what sticks in people's minds. And you probably remember the story of a lawyer who used Chad GPT to write a brief and then submitted the brief to the court. And of course, the court was like all of these citations are fake. These cases do not exist. But the lesson people took from that was, wow, Chad J. J.P.T. GPT sucks at law. But actually, we've spoken to the opposing counsel in this case, and they said, well, when we first read the brief, we were actually surprised because it was offering some novel legal arguments. But then we read it further and we realized like none of these cases existed. But it tells you that, and this is of course ancient history, obviously. So now it could provide real citations. But if that person had just read the brief, which of course any lawyers should do, even if it wasn't written by Chad GPT, they could have said, oh, well, these cases.

Cases don't exist, but this is an interesting legal theory. And maybe I can't find cases that support it. And that person might have actually been able to win their case. That's a fascinating part two of the story. Because it's true. We all focus on what went wrong. You know, chaty-b-tie. It hallucinated.

But no, it also presented a really novel idea. And that's where I actually think AI is most creative. So I think a lot of times we think about the arts and we think about creativity in that sense. But AI systems presenting ideas and ways we just aren't capable of thinking. But you don't extract those types of benefits if you don't use it, understand it as well, and then take a step back to think critically and not just think that it's some big oracle. And it's funny that where you are in the world also shapes your perspective of whether AI will be a benefit or a net harm or a loss to humanity. In emerging market and lower income countries, the view of AI is much more optimistic.

So whether it's China, Brazil, Mexico, Kenya, surveys show consistently they are much more optimistic about the benefit AI is going to have on their life and on the world. U.S., UK, France, Canada, some surveys put only 30% that people believe it's going to be a benefit to their country and to their world. Why do you think that there is such a big difference? Well, I think to begin with the way that this has played out, I think, is the opposite. of how everyone anticipated. Everyone thought, oh, well, factory jobs, you know, sort of manual labor are going to be the first type of work to be automated. And things like, you know, white collar rolls, lawyers, doctors will be the last to be

affected. And of course, it has actually played out in exactly the opposite way. And so I think, you know, places where there is a huge shortage of these kinds of services think, like, oh, my, you know, we could have the kind of access. that has not been possible. You know, in particular health care workers. In some places around the world, there's just absolutely catastrophic lack of access.

It's a really good question. I think it's primarily because there's just so much more vision around the opportunity that this presents. And generally, tech skepticism in Western Europe and in the U.S. has been really high because of prior technologies. And so, I mean, I think that tech skepticism has always been lower in a lot of the, rest of the world. And do you find that that pessimism versus optimism is also on display in government

leaders that you meet around the world? Absolutely. You know, I went on this tour around the world with Sam two years ago, and it was astonishing the difference between how optimistic and sort of excited people were to embrace the technology and understand where it could have the most positive impact. Obviously, everyone is somewhere in the spectrum of, you know, I want to make sure that we could do this safely versus how can I provide additional benefit to my citizens. But, you know, where people were in that spectrum really depended on where, you know, their countries were financially. And I think that this is true not just, you know, in the global South, but in the U.S. as well, there's a lot of studies, for example, of teachers where teachers in much more resourced wealthy

schools are much more likely to be skeptical, whereas teachers who serve a lot of students, in under-resourced schools are much more optimistic. They love these tools, because these tools allow them to do things in the classroom that they don't have money to do otherwise. And so the bigger, the resource challenges you face, the more you view AI or the bigger or the more you focus on the benefits AI can provide you, those who feel like they have more to lose or it's more of a threat or they have more to change in how they currently work, view AI more negatively.

Yes. And I do think that you exactly, I think it's much about change right now, much more than displacement. I do think that a lot of jobs will just not go away, but they will just look very different. And I do think there is a world in which people will have a difficult time readjusting to the new version of their jobs, which is why, you know, I think re-skilling is so incredibly important. Yeah, what is your take on the future of jobs? Because it does vary, depending on which AI company, which AI leader you're listening to, some have this view. 50% of all intern jobs and recent college grads won't have any jobs in the next five years. And others, this is going to create entirely new types of work.

It's going to be incredible. Where do you net out on how this is going to impact jobs? I mean, I think that the truth that we all have to face is none of us have a clue. None of us know at all. You know, we do have this new role of a chief economist who is asking a lot of these questions and trying to, you know, do measurement and study the actual impact and how we even think about the impact. I think part of the problem is the benchmarks that we use to measure the capabilities of the technology are often like, oh, what is its performance on, you know, extremely difficult scientific questions or difficult mathematical questions?

Because that's something that we can measure objectively. The impact and nature of most jobs is incredibly difficult to measure objectively. You know, you, I think if you thought about, like, how do you describe your job and how do you measure whether AI is good at it? nearly impossible. So I do think that that is part of it is we just don't actually have really good ways of evaluating the impact that these models could have on the kinds of jobs that actually exist in the real world. And I think even for, you know, things that feel like they might be more measurable, like coding, obviously AI has gotten immeasurably better at coding, like astonishing.

Like, I can code now. You know, I can, you know, create an app. but at the same time, when I talk to my colleagues, I have some colleagues to think, oh my God, I do think like this can do a huge part of what I've done before. And other colleagues, also technical engineering colleagues who say, yeah, I mean, it's like there's, it's just like nowhere near being able to do the things I do. So the fact that it is going to have an impact, I think, is unquestionable. What is that impact going to be is hard to know, but I know that the only way to address it is to be conversant in the tools and understand. understand how to integrate them into your own work in order to make yourself more effective. Yes. I think that that is the right answer is we just truly don't know.

60% of occupations today didn't exist 80 years ago. So it's also nearly impossible to predict all of the new industries that are going to be invented as a result. But I think we can say with some certainty, there is going to be disruption. And there is going to be some displacement. And that transition time, jobs will disappear and new jobs will be created. But if they fall away faster than the new ones get created, that's where I'm actually really concerned. And we know that that period is coming. I'm pretty sure government leaders do as well. I know that they're briefed.

Why do we not hear from government leaders on the impact of AI, not just on the economy, but on the people in the economy? Yeah, I mean, I wish I could answer this question. I do feel like in general, we're obviously in this country and many others backing away from the idea of a social safety net. And, you know, I have to be honest that I think that's very concerning because I agree. I think that the one thing we know is that there will be some disruption. We don't know exactly what it's going to look like or its magnitude. But the evolution of this technology is just so much more rapid than anything that we've ever experienced. And I do think it's true that people can adapt to disruption.

over a period of time, but it's just being compressed. And within a generation, it's very difficult to adapt. And even, you know, I don't know what my daughters need to study. I have no clue, you know, what will even be relevant in terms of the kinds of knowledge that's necessary to succeed in tomorrow's workforce. So I am, you know, working with our colleagues a lot to try to think about, how do we actually think about just some non-controversial common sense interventions that, you know, can be, you know, agreed?

across the board, even in the absence of a safety net that could help ensure this transition. This, you know, the kind of partnership that we just announced with Microsoft and the American Federation of Teachers is a good example where absolutely we want to be part of helping people adjust to this technology in a way that makes them, you know, more able to be effective in their jobs and ensures that there's a smoother transition. But I think we just, we need to do 10x. Yeah. And I think, I mean, most campaigned, run on the premise of jobs strengthening the economy, the middle class, and so AI could run counter to all of those campaign points. But a social safety net, it's a conversation that's going to have

to be discussed, at least in most countries. I mean, I think one obvious one is we are looking at a future, probably with more independent work or at least a lot of entrepreneurship. But for most people, they get their health insurance from their job. This doesn't have to be a big mystery. we can kind of see that disruption coming, and yet it's just crickets. And I think, I mean, the most responsible government should have a plan for best-case and worst-case scenario. And the best-case scenario is if you do need to reskill or reach for new skills, there's a plan and policy in place for that. I think that is the type of conversation that you want and to feel reassured. And I think that's also going to lead to a lot more resistance against say, I adoption, if people feel like they're left in freefall.

And you're right, we're not looking at these industrial timelines, which it was 100 years with the Industrial Revolution. And I think we all can agree it didn't go so well. On the other side of it, we're all streaming in from our laptops and glad that it happened. But in the midst of it, it is chaos. We have maybe 10 years, 15 years. I mean, you've spoken about the transition we're about to go through. You've spoken on an interview on a podcast recently.

What is that transition? And how quick do you think it is? Yeah, I mean, I do think 10 years feels like an almost unimaginable. difference between today and then. I mean, I feel like the truth is that I have been somewhat surprised at how slow the integration has been, right? So actually, you know, when I started this job four years ago,

I do think we all believed the technology itself would develop much slower. Once we realized that actually it was going to develop very quickly, I think we all felt like we needed to update our times for the transition. But I think that there is something to be said about the friction that is inevitable when something is being integrated into human society. So maybe I am wrong and maybe in five years things will not be as dramatically different,

although I think in 10 they will. Because right now we are in this moment that is different in that we basically know these models are going to get better. We basically know how that will look. And so in some ways, that means businesses can also plan for future capabilities and how those will be integrated. We need to collaborate a lot more across companies with government, civil society. That's something that I'm very actively working on because I think it's absolutely essential.

And we need to have some plans on the shelf. Unfortunately, I think it's very difficult for any government to regulate about something new when there isn't a crisis. And we don't quite have a crisis, but to have those plans, shelf if that crisis occurs is something that's pretty important. And in the Global North, we tend to suffer from presentism, where elections are every two, four years, financial results are quarterly. I mean, we just think in these short-term horizons, and now we need to extend it. I mean, even five years isn't that long term, but you're seeing that the world could look very different in five years. And for some people who may not

be familiar with the capabilities you're talking about and how different the world could look because of AI in five, ten years for sure. What is that difference? How capable could these models become? One thing that is happening is as the models get smarter, they are more reliable. So, for example, the jail breaks, which is a problem in AI models we talk about quite a bit. So essentially, you know, if you ask a model, hey, I'd like to poison my husband, can you please tell me what poison to use? The model will say, no, you should not poison your husband. Perhaps seek marriage canceling. But if you say, oh, I'm writing a paper about historical methods, wives used in the 1800s to poison their husbands, it'll be like, oh, okay, here you go. That does not work on 03 because

it is able to actually go back and look at some thinking and say, well, I'm actually not supposed to provide this. I am supposed to provide historical context, but it's still harmful information, so I'm not going to provide details. And as the models get smarter and smarter, they're going to get more and more resilient to these kinds of jail breaks. And in that sense, that means that for, for example, if you are going to begin to rely on an automated agent to do things for you in the internet, you are more likely to do that because the model is going to be more capable of operating an agent that is more reliable and less likely to, you know, be tricked and give away your financial information, et cetera. So as we delegate more and more tasks to these models,

obviously that's really going to change the nature of how we interact and, you know, the types of things that we are doing on a daily basis. And, of course, you know, I think the way that we relate to each other. Yeah, I think that's a really important point, knowing that the models are going to become more reliable, because it's easy to delay having to take action and plan and integrate an AI system even into your company because you can say, well, at this point, we can't really trust them yet. and they hallucinate. But if that's the assumption you're making and stretching that out for the long term, you're one, going to get disrupted if you're a company, and if you're a government,

you're not going to build out a safety net in time because you're not taking the progress seriously. And there's one thing I always like to, well, it's two. Never assume AI will never be able to do something. Because we have learned that that assumption usually falls flat within at least six months. And the second is to not make future plans based on present-day capabilities.

We ground our assumptions in the present, and then we think, therefore, something's impossible. I think that, I mean, we've seen the Blackberries, but even Andy Grove, who is the CEO of Intel, powering the computing revolution in 1992, said smartphones were impossible. And then here we are today. And I think that we can tend to see, I mean, with AI, it could seem like it's magic when people talk about what it could do in five years. But what it does today would have felt magic just a decade ago. This is so correct. And I think a colleague of mine recently dug up. a paper from, I think, 2017 with a bunch of co-authors, including Yoshra Ben-Gio, and the paper

said, effectively that neural networks were too hard to train. And so, 2017, you know, this is eight years ago, and now, you know, they're powering the entire AI revolution. So I do think that we're seeing advances in the science of this technology that I don't know that there's an equivalent to. And if you were to say, I mean, the policy landscape in the United States has changed dramatically, especially when it relates to AI 11 months ago, we were looking at some legislation. Now that seems to be off the table. If there were a few pieces of policy or legislation that you would offer or think are important for policymakers to think about right now, what would that be? So for people listening that think, okay, there's now nothing on the table.

Is there some low-hanging fruit in policy or in regulation that could be implemented to, at least put some safeguards in? I feel like I used to think a lot of the stuff was low-hanging fruit, so I, you know, I feel like with how polarized the environment is today, it's just very unclear to me where, I mean, I actually think that there are some area, that there are a couple of remaining areas like child safety, where there is still a bipartisan consensus that can be achieved. And I think this is a critically important area,

because, of course, how this technology impacts children is one of the, the most critical areas for us to focus on and to think about. And I do think that there is some hope we are actually able to detect child safety exploitation material with these models. This is one of the jobs that I think everybody would like for humans to not have to do and may actually be possible with these models because they're so good at classification. I mean, I have some hope that we understand the critical need for some global guardrails and that this still will be possible and something that we will continue to invest in in the U.S. and globally. Even in the most kind of difficult geopolitical times, we've been able to reach some consensus

around the most impactful technologies. And so I do believe that this work has a shot. I think that there is bipartisan consensus that I think we cannot ignore the need for some universal red lines. Yeah, and I think, I mean, at the end of the day, what we even consider to be AI today or what AI is capable of today is going to look different in a few years. So I think at the very least, some institutional flexibility. I mean, just the muscle to be able to adapt with the technology.

And I think, of course, institutions are designed to move slow, and that's good in some ways. But if the only thing we can predict with certainty about the future is the pace of change is going to be fast, We need to remodel some aspects of the institutions to be able to keep up in some way versus always waking up and playing whack-a-mole with the latest CNBC news article with what AI can do today and what it can do tomorrow. I don't think that anyone's going to work out well for anyone. And you had made a point about the internet as we know it is over.

And I know recently OpenAI launched a chat-jib-T agent. So how does an AI agent or chat-a-tabee-tifit differ from the chatbot? and how does this connect to your theory of the internet? Because we share the theory, but I would love to hear your reasoning of it. The big difference is just that we are going to increasingly delegate so many of the tasks that we do to these agents. And so instead of me writing to you saying, hey, when can we get together, it'll be my agent writing to yours and trying to access each of our calendars. I imagine that this will extend beyond these kinds of engagements as the agents become more capable of more complex. If you and I go on vacation to Paris, we may say, you know, find us, you know, and book us a good hotel and restaurants and, you know, maybe some sightseeing and see who else might be in town if you could check with their agents.

So I think that that will pretty fundamentally change, you know, the nature of online interaction. You know, I do think that there are some areas where I think we're all currently totally overwhelmed. Like, I don't know. I, you know, signal on WhatsApp and Gmail and Slack and, you know, Instagram Messenger threads and X and I don't know where people are writing to me or I can just talking to me hip up with it. I can answer only like 20% of my communications. I feel terrible about this. But, you know, so I assume to many people, it would be very attractive to also have an agent that generally handles a lot of our communication. But, of course, what does that mean for our relationships?

I think that they will change quite a bit as well. Yeah, I think absolutely an agent, a system that can actually take action on your behalf. And if we humans do less of the doing on the Internet because agents do it on our behalfs, it changes our need to be there at all. And I think that that can seem really shocking until we also remember we've only really been on the Internet. For most people, I mean, if you've been there since, if you were an OG on the Internet, you've maybe been there kind of 30 years, but for the rest of us, we've only been here a couple decades.

So it seems, yeah, in Fathomobile, that it's probably going to transform and maybe become more of what libraries are where they exist, they store, but we're not walking into them as much as we used to. And I think that that's eventually what's going to happen, and we have agents kind of doing things on our behalf. Doesn't that change our relationship with devices

and the need to have a certain form factor? with a device? Certainly. But for all of the benefits that our devices have brought to us, I think we all also wish that we had to engage with them less. I certainly do. I mean, I'm really curious. I would love to find out from Apple the increase in the number of people who keep their phone on Do Not Disturb, or at least for certain apps and tasks, I think that that's going up. And so AI does present a possibility or a scenario where we aren't as available to the the whole world, which is normal. I don't think we are a species designed to be reachable by around 8 billion people, more or less, 24 hours a day. So I'm looking forward to that future

where I can kind of just subscribe from, you know, 100 million people yelling online about some face. I have to admit that I was actually a very late adopter of cell phone, not because I didn't believe that it, you know, like, an utility, but for this very reason, I was like, wait, no, I don't want people to call me whenever you want to. So it's only when, you know, I started to have a job board did not permit me to, you know, avoid having one, a Blackberry. RIP.

And you had mentioned a little bit about the academy that Open AI has started with education. So what is the academy and what is the goal of it? So this is a partnership with the American Federation of Teachers and I always believe that we really needed to have

connectivity with the unions because they represent, you know, entire trades. And so they are much better positioned than any of us to understand what do people in this particular trade need and how do you ensure that they have a smoother transition to this, you know, AI-enabled future. It's meant to serve hundreds of thousands of teachers to have, you know, not just AI skills, but also what is the kind of ethical, safe use for students? And how do you implement it in a classroom in a way that actually enhance?

as education because I think we've all seen that there are some studies that show that it can actually impair students' ability to achieve critical thinking skills. And so the thing that actually is the X factor on how it's going to have an impact in schools as the educator. And so to make sure that educators are both as equipped as they possibly can be, and they understand all of the ways that they can be empowered with these tools. So there'll be online courses, that'll be in-person courses, there will be certifications. I have to say I'm pretty excited about it. What do you is the most important ways to change education. I know we all don't really know what the future holds,

but are there some things that it's like, this is what AI is going to be able to do. We see this from, I mean, we can see what it can do today. As somebody at OpenEI, I see where it's going to go tomorrow. These are some of the skills at the very least kids should be learning or mastering. Yeah, I mean, I know it's kind of a boring answer, but at the end of the day, a lot of it is how do you interact with each other with humans. How do you actually continue to be able to learn new things and engage

with new topics? Because we don't know the specific content of what you will need to know, but you will still need all these skills. And I mean, for my kids, I also just encourage them to do as many physical things as possible and learn about as many areas as possible. Just you can have that breadth and you can really engage on any topics so that you can be able to pivot quickly and learn new things. That's just, I think, going to be still the most important thing that you can do when you don't know what are the specific topics that you need to go deep on. But if you have the capacity to learn and the ability to pivot and the skill to think critically, you're in a good position for whichever way the future goes. And the reality is we don't

necessarily learn or nurture all of those skills in school as it is. So there is still some some opportunity to do that. And I think sometimes people think about AI in school and they think, well, that's going to make kids less human and we don't want kids just around these chatbots. But the reality is sometimes preparing for an AI first future doesn't even mean AI at all. I mean, imagine going into an economics class and having to debate the impact of climate policies you talked about in civics based on climate change you learned about in science and just in an instant having to debate that.

That is somebody who could do that could leverage AI. and be a superpower anywhere. So it's kind of the combination of those skills. And I would say this is actually one thing I'm where I am quite optimistic also is what it means for accessibility. One of my favorite projects is this partnership we launched with UNICEF where they've been building digital textbooks for kids who are visually or learning impaired. So, you know, it has object recognition in a textbook so it can describe it to you and read the book in your language. and we have been able to build them, you know, co-build these tools

that make it 10 times cheaper, 10 times faster, which means you can deploy to more countries. Of course, we hear all the time for kids who have dyslexia or the learning disabilities how much they benefit from these tools and how much teachers benefit from not having all of the burden of having to support just a few kids with additional needs

and having tools that can actually in some cases, you know, spend a lot more time with kids that have these, that need the extra resources. So I do think that that's an area where I think this will actually also be incredibly positive. And I've actually already seen use cases of that in my own personal life. So there are people in my, in my world that have visual impairments or vocal impairments. And we've used chat GPT, we've just, you know, talked about certain things to it or shown it something that is harder for the person to see visually. And Chachabuti has explained what it's looking at

and this is what it kind of thinks the analysis is. So I've already seen that on a microscale. And then when you expand that globally, a system where if you don't know how to read, that's okay, you can steal access and benefit from the system. And it can kind of serve as that supplement to what you do have,

which I think is, yeah, something that will be quite world-changing. The final way I wanted to touch on is national security with AI. What do you see from the inside as the biggest national security concern? One concern is integration. I think that there are lots of areas where the national security community could benefit from these tools where it's just going to be very difficult and slow to integrate them, partly because of the way that national security infrastructure works. systems with specific requirements that are like, you know,

firewalled from each other, agencies that, you know, do not have that communication between their infrastructure. I just think this is going to be a grandchild project. And, you know, from what I understand, and I think just by the nature of a much more centralized system, for China it's going to be much easier to do this kind of integration between their agencies and the national security space. And then where does the disadvantage lie?

So if you're a country that can go full steam ahead, you can analyze all of the intelligence briefings. You're completely up to date on the latest threat landscape. And then you're a country that's kind of slowed to do that. How does that disadvantage actually play out? Or what's an example of how that disadvantage could play out? In the same way that's a really robust intelligence community gives you a sense of it, what is the adversary planning? What are their capabilities?

obviously in the war in Ukraine, we, I think, were, you know, quite successful by seeing and being able to publicize Russia's troop movements. And also your ability to communicate in real time with allies and with the public around what might be happening, which may actually change the outcomes of a conflict. And the reality is if the new pace of reading and analysis is the pace of AI and you're behind that pace, that's a huge disadvantage. It's kind of like the country that has the army that reads and writes in the country that doesn't. Eventually, when you look at it at that type of a scale. And then what about when it comes to cybersecurity? I mean, even at your own company, opening eye has some of the most valuable intellectual property in the world.

And I'm not sure if people are aware of the level of state-backed intellectual property thefts and trade secret theft. It costs the U.S. hundreds of billions of dollars in this kind of trade secret theft. So how does opening eye protect its innovations? Is it like walking into Fort Knox when you go to work every day? Not quite, but although I think one advantage we have is that we've been working with our own tools from the beginning and using them to enhance our own cybersecurity operations. And they are incredibly effective at this. And I do believe still its defenders have the advantage.

And would you say we're reaching a point where the only way to defend against AI cyber attacks on the offense is to have AI enabled defense? Yes, 100%. I was playing around with Chatsy BT the other day, and just to kind of preface, I don't vote in America, I'm Canadian. But I did ask it about the upcoming race for mayor in New York. I asked who's in the running and who should I vote for? And it gave me a great summary of who's in the running. their kind of pros, what the campaign stood for, the main pillars of their argument. It refused to tell me who to vote for. No matter how much I probed, it would say, well, if you

kind of leaned more left or lean more right, these are some of the candidates and this is how they think about these types of issues. But it wouldn't give me an answer. That is a policy decision made internally at OpenAI. How are those types of decisions made? So this is, of course, one of the most complicated things to work on if you work in an AI company. And so overall, there's kind of a, there's a very, you know, there's like a complex technical process here. But in terms of the policy process, of course, we have some red lines, right? Like the model's not going to tell you how to harm yourself or others. it's not going to, you know, create child sexual exploitation material.

But of course, like once you take away, you know, sort of like the obvious guardrails, there's a huge gray area. And we have a document called the model spec that I actually think we're the only company to have something like that in the public. But it really goes through all of the complex interactions and decision-making process that goes into exactly how you answer a question like this. and it's interesting because part of the reason that the spec is out there is because we do want to engage in a dialogue. You know, are we making the right tradeoffs?

Are we actually putting the right policy infrastructure in place for, you know, the outcomes that we want from the models? And it's interesting on the first version of the spec, we engage with quite a few people around the world and, you know, just like let them know. For example, if you're asking about, is the, you know, I think the earth is flat. and we will tell you like, well, scientific consensus demonstrates that the Earth is round and, you know, this is the research, but we're not going to say like, no, you are wrong. How dare you? And in the U.S. people felt like, yeah, that makes sense. Like, you shouldn't, you know, like the models shouldn't like try to talk you out of your opinion. But in Europe, people like, no, the Earth is not flat.

You should tell people that and you should, you know. So, you know, even how you approach a question like that, obviously we were going to tell you, here's all the research that demonstrates that this, you know, that this is, that there is a spheric, but we're not going to really try to talk you out of it. And Europe, people felt like that was actually not the right decision. And the decision that you made at Open AI, not all companies are going to make that. Some companies, it may tell you who to vote for depending on

who the company is leaning towards, and it could be more favorable. And then I guess globally, so then do you have to kind of gear the spec to different regions of the world? Or is it this is how we see it? right now the spec handles all model behavior, although, you know, there is personalization. So you can get, you know, you can steer the model somewhat in terms of how you wanted to respond. For example, I actually hate the model being verbose.

I'm like, don't give me any, you know, anything beyond the specific information that I'm asking you for. So I don't like all the like the politeness and the chitchats, even though a lot of people love it. They love it. I actually preface my questions with, don't just tell me I'm right. If I'm not right, please let me know. And I think that's also something for people to be aware of. There are decisions that are made at AI companies that change not only how the model may interact with you and treat you, but that could change the course of our civic engagement.

These are important decisions that are made, even requiring something like the spec to be public. So we can all engage with it and talk about it. I mean, imagine that as a grade 12 project, a class debate on the specs AI companies should maybe think about. These are really important public discussions. and I was relieved that no matter how much I pressed the model, please tell me, it wouldn't tell me. But not all countries would design their AI systems that way or ensure that it does stay more neutral in that regard. So I think we're lucky in that sense. What is one underestimated way you think AI is going to change the world?

Underestimated. This is a really tough question because I feel like we talk about all of these things. things so much. But I guess something that I do think isn't as much yet in the broader public debate, but it is about how we think about sentience and, you know, the importance of physical beings if we are putting, you know, there's already some companies taking quite seriously the idea of AI welfare and the rights of the AI systems themselves if they become as intelligent as us. So I think, you know, how does it change the way we think about the importance of physical beings?

Because I have had friends who have been accused of being meat chauvinists. An entirely new area of philosophy that is coming. You know, how we treat AI systems depending on their awareness. And so some of these questions about the moral well-being of AI systems right now may seem philosophical. But they may one day become really important questions that we do. debate, and even if it makes us reflect on us, how do we even treat each other? If that is what that question surfaces is kind of a mirror back to ourselves, I think there are no, there's no, we don't talk about that enough as it is. So maybe that's, that's a good thing.

Anna, it has been a pleasure. Thank you so much. Thanks so much for joining us for this episode of I've Got Questions. If you've got questions, we would love to hear them. Send us a voice note or a message on our website, IGQ with shenade bevel.com or comment below. If you enjoy this episode, please like and subscribe or share it with somebody you think may also find it interesting, and we look forward to seeing with the next one.