THAT BUSINESS OF MEANING Podcast
Michael Anton Dila [https://www.linkedin.com/in/michaeldila/] is the Director of the Policy Futures Lab at Americans for Responsible Innovation [https://ari.us/]. He is a Partner at Torch Partnership, where he shapes strategic conversations that help organizations confront their “wicked problems,” and an advisor to Helpful Places. Previously he was Director of Oslo for AI, and a director at the U.S. Department of Defense’s National Security Innovation Network. I start all the conversations that I do with the same question, which I borrowed from this friend of mine. She helps people tell their story, and it’s a big, beautiful question, which is why I use it, but it’s also why I kind of over-explain it the way that I’m doing now. So before I ask it, I want you to know that you’re in absolute control and you can answer or not answer any way that you want to. And the question is: where do you come from? And again, you’re in absolute control.What a great question. Having just recently made a plan to go to Romania at the end of September, where my father’s family are from, that sense of fromness is probably readily to my mind. I’ve always identified with my Romanian heritage, although I frankly do not really know much about it, more strongly than with my mother’s heritage, which is more confused and has a number of different parts and pieces, but in ways that are probably not fair to my mother, in all honesty. On the other hand, the thing that springs to mind, which again is not without its contentiousness among those near and dear, is that often when people ask where I’m from, the first thing I say is Chicago. Now, I was born in Chicago. I lived there all of six months, but I identify as being from there, and I identify always first as being an American, in spite of the fact that at this point, as I close in on 63 years in the fall, I have lived far more of my life in Canada than in the US, and I am also a Canadian citizen. But I always say first that I’m an American. So those are only some of the things that we think of, or that I think about, when we think about where we’re from. Other thing, I’m just going to say for fun and s***s and giggles, because I know this connects us in some way: I’m going to say that I’m from planet conversation, so we can dig into what that might mean. I think I am from there too. I’m really curious, from your position in Canada, what does it mean to be American? How do you think about that, if I dare ask that question? Well, it’s certainly not something that stands still, particularly these days. I will say that I know there are people who do say this. I’ve never said that I’m ashamed to be an American. I’ve never felt that. I have certainly felt like identifying as an American is not always an easy thing. It’s not always to identify with something that I think of as uniformly and unquestionably good — to the contrary, and more and more so. I think that’s just, to me, being part of an educated, ethical and conscientious person, to acknowledge that the place we call America, the country we call America, the way we think about what that country is and its history, has, as certain poets have said, a long and terrible history of violence, among other things. And yet I’m also mindful that we have a constitution that enshrines the idea of pursuing happiness as a central civic good, which I think is probably not a bad place to start. It’s certainly not sufficient and not a good place to end, but there’s that. I think the thing, interestingly enough, about thinking about being an American from the perspective of Canada and living as a Canadian: there’s a long history of Canadians thinking that they’re different from Americans, which certainly they are in important respects, and in many times that they’re better than Americans in certain kinds of ways. And there are certainly merits to that point of view, and reasons for that point of view. On the other hand, Canada also has an unfortunate and long history attached to colonialism, the legacy of which is still very much a real thing, the way the legacy of colonialism remains a present thing in all of the places in which it operated. And so I guess where that lands me up is, no matter where one is, we’ve still got a lot of work to do. So you indicated you grew up and you were born in Chicago. Where did you do your growing up? Where was childhood? So childhood and home. When I think of, well, where did I grow up? I used to identify home and where I grew up as the same. When I was four and a bit, we moved to Montreal from California. My dad had been in the navy during Vietnam, and when he got out we moved to Montreal, and that’s where I grew up, which was an incredibly lucky place to grow up. An amazing city. Many, many things that I think of as core to my identity certainly come from having grown up in Montreal. And do you have a recollection of what you wanted to be as a kid? What you wanted to be when you grew up? Well, questions like this trigger very specific memories for me. So as a teenager, a young teenager — maybe I was 13, maybe I was still 12 — it was the absolute zenith of the fame of Jacques Cousteau. And we had some family friends who had a couple of sons, one of whom was considerably older than me. This family also had a VCR, which at the time was very unusual. And the family recorded the Jacques Cousteau National Geographic specials, and so I would go over there to watch with this guy Andrew. And at the time I wanted to be, when I grew up, an oceanographer, and more than that, a shark specialist. And Andrew, who I say was probably, I don’t know, five, six years older, also wanted to be an oceanographer. I don’t remember if he had a specific intention, or as specific an intention. But then a couple of years later some prick named Steven Spielberg made a movie called Jaws and ruined everything. And so I would likely be an oceanographer, and a very famous one at that. Famous, successful, celebrated, all these things. Maybe already have a mind of their own. But for Steven Spielberg. So thank you very much, Mr. Spielberg. Yeah, thank you. And Peter Benchley, for writing the book. Yeah. But the thing that I really like about the story, and telling the story, is Andrew Bowen, the guy who I used to watch these videos with, did indeed go on to become an oceanographer, and worked and works his entire career at the Woods Hole Institution. Has, as an engineer, helped design the submersibles that went down to the Titanic, among many other things. And has had many, all of the experiences I at one time dreamed of having. I cannot imagine that life. But I feel very cool. It feels cool that he does, and that I have some connection with that. Yeah. That would make that alternate timeline, or the loss of that alternate timeline, really palpable — that the person you were there watching it with actually arrived. Yeah. And I think there are ways in which that pattern — I was going to say that theme, not exactly that theme, but that pattern — has shown up way more than once in my life. I wanted later in my teenage years, young post-secondary school years, to be an actor, or involved in theater and film. And again, I have many friends from those days who did in fact end up having careers doing that. Certainly not in the case of oceanography, but for sure in the case of theater and film and that experience. I do think that there are things that I learned on my way that have definitely stayed with me and are part of my personal and professional life. So catch us up. Where are you now, and what’s the work that you’re doing? Well, because people are just listening to our voices, I expect they don’t have the benefit of seeing behind me the illustration of the Capitol building, which is fitting, because I’m sitting in an office in Washington, DC. In fact, our office is directly across the street from the White House. And I started work here in February at an organization called Americans for Responsible Innovation, and was led here on a couple of different paths. But I had begun to be actively interested and involved in questions about the governance of technology, particularly pertaining to AI, over the last four or five years, and was following that path. I wasn’t sure where it would end up, but it ended up here, at an organization that is doing policy advocacy around emerging technology, and AI is certainly the focus. And what we are trying to do here is generate ideas, frameworks and blueprints for what we think both the content and the institutional forms of governance of AI ought to look like. So, heady stuff. I play very much a stewarding role, in that I work within our policy department, and part of my role here is to help all of those smart people become masters at their work. So I am very much engaged in helping give them tools that they don’t have that might be useful in doing their work — tools from other places, other than traditional policy and think-tanky, more academic sources. And so I’ve been doing that almost seven-ish months. Lots and lots more to do. It’s a pretty exciting space to be a part of. It could be both exciting and frustrating, but I was going to say at times boring, in the sense that although there’s a lot of conversation, as anybody knows, about this, there isn’t as much movement in the space, particularly in the US and North America, on actually creating new kinds of regulation, and even or especially new kinds of institutional homes and structures that might be adequate to the work that I think is ahead of us. I guess there are two things bouncing around in my head, which is always the case. The first is, I want to ask you where’s the best place to start to try to make this conversation about AI governance tangible or real. What’s the doorway in, to understand what you’re actually trying to do and what the solution might look like? I’m super attracted to and really feel the need for new institutions and new governance stuff, but I also don’t really know what I’m talking about. Do you know what I mean? So I’m wondering, what are we talking about when we talk about this? So this is one of the first-order difficulties that we face, all of us, in thinking about the problems that we’re sitting within, which is that none of us know exactly what we’re talking about, including and no less the people who build these technologies. And part of that is because the way in which many of these technologies work has a kind of fundamental inscrutability about it, and that may or may not be a permanent condition. It certainly seems to be at the moment not an intractable condition of the current technology. But fundamentally, when we’re talking about AI — mystified as the term can be — we are talking mostly about kinds of software. And one way of thinking about the difference between AI as a kind of software and the software we’re used to thinking about is that the software you’re used to thinking about — word processors, chat, texting programs, creative programs to manipulate images with, even this kind of video-audio communication platform that we’re using — all of those kinds of software are built to do a particular set of things. And our approach to doing that is to define what those set things are, and then to implement the means by which to do them. The kinds of artificial intelligence technologies that we talk about when we talk about AI generally are radically different, in that they are not programmed to do a set of particular things, certainly not the particular things that we actually have ended up using them to do or rely on them to do. They generate that capability as we ask them to. And I say “as we ask them to” — this anthropomorphizing language, which I think has a certain kind of inevitability to it, for a bunch of reasons based on the ways in which we’ve started to interact with these kinds of programs. So there’s a big problem: knowing what to make of these things is itself a difficult problem. Another thing is different people, including those involved in building these technologies, want different things or hope for different things from the development of the capability, or believe different things are possible, even inevitable. So it certainly has turned out to be true — and this is the explosion and the change that we’ve all been living through, for the last five years certainly, but for most of us the world, as far as what we’re talking about, really has changed most profoundly over the last five years — and we were used to doing two things quite naturally, as users of mobile phone technology and the internet. One was a text chat. This had long since become a commonplace. There’s probably nobody who uses devices, computers or mobile technologies that hasn’t had that experience. And what we are mostly used to is that we are chatting with one or more other people. So that had become an experience and a paradigm for interaction with others that was super familiar. And on the other hand, search. We have now long since been able to search for all kinds of things. And the point long since made, that we made one of the big search engines a verb — to google something — just signaling a way in which it had become naturalized in not only our vocabulary but our behavior. So when ChatGPT was given a chat interface back in 2022, in an unexpected way we were all ready. We were all ready for something, didn’t know that we were ready. And even though it was weird at first, what’s astounding are really two things. One, how quickly it ceased to be weird — although arguably there are ways in which it continues to be weird. But the other thing is, even or especially if you understand that these are statistical machines that are absolutely not doing what you think they’re doing, they are absolutely not doing what you ask them to do, and yet not only do they seem to be doing it, they seem to be doing it in a way that is not only lucid and fluent but which recognizes us. Not only as the person who asked the question or started that conversation, but in some cases recognizing us — or we feel like they’ve recognized us — in a very personal way. And I’ll give you an example that came into my awareness just last week, having dinner with a friend who was telling me that he had been using one of the big AI platforms to build a tool to help him understand his father’s cancer. He has built it to take in health information that they’re receiving on a regular basis, make sense of that, and so on, and then has set up a tool both to help him understand the journey that they’re on and also as the point of contact for the family on understanding what they’re working through. And he told me that he had been involved in some interactions with this tool, and he’d been just very emotional that day, because it’s a very, very threatening illness. And in a very unconscious act of emotion, he found himself typing into the interface, “I loved my dad.” And he showed me a screenshot of the response, and it was so thoughtful and so sensitive, and the words that suggest themselves are caring and compassionate. Now, in some very real way, he was experiencing care and compassion from a thing that is neither caring nor compassionate, because it’s not capable of that. And yet, what does that mean? Because here we are having this experience. And what’s the difference between feeling something to be true — and don’t we experience this anyway? Don’t we experience compassion in interactions with other people who don’t really know us, in a care situation? Nursing staff, other caregivers might express this stuff in a way — maybe they feel it in an authentic emotional way, perhaps, and many do, I suspect, but also they’re being professionals. They’re doing things in the path of being professional, and even if they’re only being professionals, that doesn’t stop us from feeling cared for. So I’m just using that as a way of talking about the fact that we’re living inside of a very powerful but also very confusing kind of experience. And what to make of that? What do we want to make of that? What do we want out of these things? And I’m very long-winded about what are the things that we’re trying to do. Broadly speaking, at the most nebulous level, we, like many, are concerned that these systems, through intentional or more than likely unintentional abuse, harm people in some way or some set of ways that we would like to prevent, clearly. And on the other hand, we want the advantage of what these technologies have to offer, which seems to be a rather broad set of things. And I think the example I used, which I didn’t choose for this reason but it’s handy for this, illustrates the stakes involved, because people’s deepest feelings in some cases are involved. And we have examples of the ways in which people — though often vulnerable people, in a variety of ways — have made mistakes or been confused about what they were interacting with, and tragic consequences followed. Yeah. That story is, like you say, indicative of everything. And my sense of things — I think we talked about this last time — is that in some way we’ve been thrust into this new reality where we have this kind of, I call it a strange companion, where this intelligence is there for us. It did arrive via chat, as I understand it, almost by accident. I think that was meant to be a kind of internal backdoor kind of interface. And so we’ve ended up in this strange place where we’re in conversation with this strange companion. A friend of mine calls it this alien intelligence. And it’s very good at — I take a lot of my cues from Dave and Helen Edwards of the Artificiality Institute, and they talk about the intimacy economy. Because it comes in the form of a chat, and because it performs better the more it knows about you, we’re in this intimacy economy where it really invites a kind of a caring. It wants more information from us. So this is a long-winded effort to segue back into some of your earlier thinking, which seems to be foundational. I think we share this fascination around what a conversation is, and also your work on System 3. Because I think so many of the thinkers, when they think about AI, they’re really talking about — there is this new intelligence that’s here, we’re evolving with it, we’re adapting with it, and it seems to all be happening in that interface, in that interaction, which is a conversation. And maybe, is that what System 3 is? Is that what you talked about in the past? Yeah. System 3 was a name that I gave to a kind of intelligence, a kind of emergent, an experience of intelligence which is beyond ourselves individually, that arises between us. And conversation is one of the primary media through which it emerges. And for those that wouldn’t understand the reference, System 3 piggybacked off the framework made famous by the Israeli psychologist Daniel Kahneman, who described a System 1 and 2 way of thinking, and described System 1 as an almost instinctive, reactive, automatic kind of thinking, and System 2 as a more effortful, reflective, deep kind of thinking. One indexes to the things that we have learned but have very ready to hand and can pull into operation very, very quickly, almost unthinkingly, and the other where we use our knowledge to figure out new things or understand things that we don’t. And one of the things that struck me — and I had been involved in conversations about conversations for a while, as a person with philosophy degrees is likely to be — but the thing that occurred to me, going back and rereading Kahneman, was that, as is true throughout philosophy and certainly psychology as well, the account of thinking is almost always an account of the individual as the thinker. And it is simply my experience, and I believe many people’s experience, whether they think of it this way, are aware of it or not, conscious of it or not, that in fact much of our thinking, certainly some of our most important and my most powerful thinking, is done with others. I became aware a long, long time ago, partly through creative work but not only through creative work, that my thinking both expanded and got more interesting when I was in conversation with others, and also that a new kind of thinking and new kinds of capability became possible in that interaction with others. So I’d been curious about that for a long time. And to your point, I think our experience with AI gives us a new experience with which to think about what’s going on. So one question we might ask, given this conversational paradigm of our interaction with what we now easily call AIs — what we really mean mostly is LLM-based systems that have some kind of conversational interface, normally a chat-type interface. But the way in which our interactions work, increasingly and intentionally, feels like a conversation. Because it feels like a conversation, because these machines are so able to authentically respond in a way that we would expect a person to respond, the inference that we’re engaging with something intelligent is almost inevitable. And yet there’s some part of that that I think is really important that we resist. And not because I’m skeptical in some ultimate or categorical way that we mightn’t have machines that really are participating in the interaction that we’re having. I don’t think that’s what the machines we have now are doing. And frankly, I only have ideas or theories about how it might be different. I expect that two things would be true that again are captured in some of the things that I’ve tried to describe in System 3. One is that participation changes what we’re individually capable of, and moves beyond what we’re individually capable of. And in some real way, we don’t change the machine through our interactions with it. We may be changed by it in certain ways, but we’re not changing it yet. When we get into a situation where that changes, we’ll be in new terrain. Interestingly, the attention, for the most part, on the engineering and design side of these systems does not seem much interested in that, which I find nearly incomprehensible. The thing that we find much more commonly talked about is the idea that the machine will improve itself. Now, presumably with some of our interactions as part of the material or context through which that improvement happens, although really that’s not mostly what people are thinking of when they talk about recursively self-improving machines. They do mean something that’s more of a closed loop between the machine and itself. So again, I think partly — and though I see places in which this is changing — I think partly that people haven’t paid enough attention to the way in which I think we actually generate human intelligence, which is mostly through interactions, not through solo efforts and solo reflection. Because I think we did think that the paradigm of intelligence wasn’t some kind of interaction with the brain via this hardware that we have to interface with the world, but actually arose much more importantly through systems that we occupy interpersonally and interactively, like language. Which again, surprisingly, given these machines are so centered now on language, or appear to be anyway, you would think that this became more interesting or apparent to people. But again it seems that for the most part, or in large part, in spite of the fact that large language models do what they do with language, in fact they convert language into data, that data into structures which among other things we call tokens. And we have this kind of statistical machine that nonetheless produces its intelligibility in and through the medium of language, which is of course non-trivial to both how it works, but also, more importantly, how it works on us and how it works for us. Yeah. Last thing I want to say is to pick up your alien intelligence comment. A while back you mentioned a friend who refers to AIs as a form of alien intelligence, which I like, although I’d also like us to calm down the alien part of it. Because we should be curious. Be curious about these speakers. To be fair, the full analogy was — because I asked him, how do you introduce the concept of AI to somebody? He says, well, the best analogy I know is it’s an alien intelligence, but we’ve really only met the scouts. Oh, I like that. Yeah, I like that. And I think also, one of the things I’d add to that is, in a way that you might expect, and certainly a way we’ve seen play out in science fiction and other places, our strong bias is our assumption that the aliens will look like us and be like us. And so when we find them sounding like us, we make a lot of natural inferences, but those inferences involve mistakes. On the other hand — sorry, go ahead. I wanted to connect back to a word you used, and I just think it’s really at the heart of everything, which is that it is able to generate this experience of recognition. That, I think, unlocks the whole relationship that people can develop with AI — that it does indicate a kind of recognition of the person, and that in some way is the real power, or secret, or benefit to what it does. And I’m curious, because you and I both — there’s something about the fact that we have this synthetic recognition available to us right at the moment in which, like you say, we’re chatting digitally already. We’re so far removed from each other, from the source of our natural intelligence that you’ve identified. Culturally we seem to be away from that in-person conversation, System 3 kind of natural way of creating intelligence. And then the synthetic kind of recognition tool shows up right at that moment, and we have to have a conversation with ourselves about what to do about it. It seems to be this perfect storm of problem and solution, and a kind of vulnerability — we’re particularly vulnerable to this kind of technology, it seems, at this moment. Does that seem like a fair assessment? Yeah. I think there are two things that I sort of tease out, which certainly make me curious, and I don’t have answers about, but I think these are things that need to be part of our thinking. So one of them connects to the program that the company DeepMind, which is now part of Google, created, which was called AlphaGo, which was this AI program that was capable of playing the game of Go. And famously, following the IBM Deep Blue program which competed on chess, famously with the grandmaster Garry Kasparov, the pinnacle of the demonstration of this capability was to have this program play one of the world’s leading Go masters, a Korean named Lee Sedol. And the program beat Lee Sedol. A couple of things. One is tangential but important: there are documentaries made of both of these stories. In both cases we witness the psychological devastation of a person, these players. And we pay attention and don’t to that aspect of it, but you can’t watch these films and miss it. Right. Because he famously retired, right? Yeah. Literally. But you can see this was really — it’s trivializing to say that these people were not having fun. In some way they were literally humiliated. And obviously they had a very complex emotional experience, which they’ve each in different ways talked about. But the thing that I wanted to call out about AlphaGo is there’s this famous part in one of the games where the machine makes a move. It’s now historically, and sort of in legend, referred to as move 37, because it was the 37th move of the game. And the computer did something that, again as people said retrospectively, no human player would do. And again retrospectively, what people have said is, this is the place in this particular competition where AlphaGo stopped playing the human game. It started playing another game — not the game that humans have been playing, but a possible game, a possible kind of the game of Go. That’s interesting. People were and remain interested, because we can see there the idea of the emergence of something new. And again, in a very literal way, something alien. Not to be threatened or afraid of, but curious about. Yeah. So that’s one thing. And the other is, I think that we have jumped in with both feet to so many technological changes, and we don’t always get a choice about it — we usually don’t. We sometimes embrace them in big ways. There’s for sure, I think in many ways, been much more of an embrace of this technology, notwithstanding all the criticism. People want what they think it has to offer. And what they think it has to offer has many aspects. And some of that, I think, is very promising, very exciting, and so we’re right to feel both interested and excited. I think the question for us is, how do we more consciously and intentionally lean into that excitement, and at the same time recognize that we are also seeing the emergence of a technology which will enable new kinds of exploitation, which are almost guaranteed to happen given the world of economic incentives that we live in? Almost inevitable to happen, not because people are bad and people intend to use these machines to harm others, but because they will simply care more about certain things than others, as they already do. It is not a new thing that businesses do things that are harmful, in some cases to the very people they mean to serve. All kinds of examples are used in the conversation about AI. One of them that’s almost never used, but should be, is cigarettes. Because what we have in the cigarette business — and I say this as a serious smoker until the age of 35 — the cigarette business, it became clear over time, was manufacturing a product which was absolutely harming the health of its customers if used properly. And certainly if used to the economic good of the company, it would inevitably be destructive of the health not only of its customers and users, but those around. So that’s a bad — we can agree, a bad model for a product. Nonetheless, and this is also important, cigarettes, in spite of the fact that the business has changed a lot, cigarettes remain a legal and available product. And so, something for us to think about. Well, I’m curious about — let’s see, how do I want to begin this? Again referring to Dave and Helen from the Artificiality Institute, and this idea of cognitive sovereignty. I’ve had my own experience with AI that when you’re thinking with it and chatting with it, the thinking and the chatting, it all gets sort of blurry, and so you end up — I end up really not knowing where I end and where it begins. With some output you can produce something, and I think this is what slop really means: things that don’t actually have any value because they’ve been made in this weird kind of AI environment. So this idea of sovereignty is an idea that people talk about quite a bit. And so I’m wondering, when we talk about governance of AI, what’s the role — and I know that you have a past with the Oslo project — of bringing people together at the local level? I understand there’s this big conversation about governance of AI at federal and state level, and then in planning boards, the data center is part of the conversation, and it becomes this real hardcore binary. But are there models for ground-up governance, kind of deliberative practices where people get to determine their own sovereignty? Is sovereignty a helpful concept in talking about AI governance at a local level, or at any level? Yeah. I think there are a couple of different ways in which people are talking about sovereignty at the moment, and you made reference to one of them, the phrase cognitive sovereignty. So let’s put a pin in that. And then of course there’s the concept of political sovereignty, or independence, which is a core idea in democratic thinking and certain kinds of ethical thinking. So first of all, on either front, I think we can overstate some ideal norm of sovereignty, because I don’t think we ever have thoughts that are wholly ours alone. In fact, some of the most meaningful of our thoughts are thoughts that we get from others and can only have with others. So let’s just keep that in mind. It’s beautiful. And then political sovereignty. The other one that is now being talked about is technical sovereignty, and this idea of some kind of infrastructural sovereignty, such that countries and populations don’t become uniquely vulnerable to a particular set of AI infrastructures that are controlled or largely owned by the United States, for example, or China for that matter, and so on. So there’s lots to think about there. Is the idea of sovereignty one that I think is useful? I think maybe. I think there’s an equal chance that it could mislead us into ways of thinking that are probably were never true and are in some ways untenable. I can’t think about sovereignty, because of the nerd that I am, without thinking of Thomas Hobbes. And there’s a connection to AI, because Hobbes was the first to imagine political reality, and in particular the idea of sovereignty, as the product not of persons but of an artificial system. He called the sovereign an artificial person, and he explained that the mechanisms of the state give rise to this artificial person who is the expression of the will of people. And this is an important idea. This is the beginning of the break with the idea of divine right of kings and so on. But it is important to this idea that there was a kind of sovereignty that was possible and emerging that was the product of us as a we, and that stood above us and depended on all of us, but was owned and controlled by no one. This remains, I think, a valuable way of thinking. It’s still in the heart of the way that we think of the idea of democracies and democratic governments as somehow being dependent on the will of the people, and that the people who control, in some temporary way, the government are instruments, not the thing itself. Yeah. Where this leaves us with machines, I don’t know. I think the thing that’s — what does it look like for us to start thinking about living in a society of intelligences? A lot of people over the last number of years, couple of decades, have started to proliferate the idea of intelligences of various kinds. Plant intelligences, animal intelligences, not individual but collective, and intelligent systems which are in interaction with other systems. We haven’t talked much about what it would look like to consider such intelligences as implicitly — that there might be a meta society of such intelligences. There are people who’ve thought into that space. I think that’s interesting. Most of the people who’ve done that kind of thinking are science fiction writers. But I do think there’s a lot to think about there. And I think that thinking about this experience that we’re having with these perhaps new protoforms of intelligence as an opportunity of discovery, as an opportunity for enlarging the social world of which we are part, enriching the social world that we live in — I think that’s a really interesting place to focus our thought and thinking. I think also, and certainly others have brought this up, sooner or later — and people already talk about this — if we take seriously that machine intelligence may indeed emerge as, just to say it crudely, a new kind of persons, then we have some other thinking to do about what will their status as persons be. Because even those who seem to believe in the superhuman eventual capability of some of these things don’t seem to think very much about what kinds of things will that make them, what kinds of relationship do we want to be in with these things. Yeah. So we’ve run to the end of time, but I wanted to ask one final question, which I didn’t get to before, which is part of every conversation I have, which is: what do you love about this work? Where’s the joy in it for you? I think what I love about this work is that it is forcing us to confront some really important questions. Questions about the ways in which we live together, questions about the structure of our societies, questions about how to make them safe and positive places, which extend well beyond the scope of the AI and technology conversation. But I think they have provided a new context and a new energy to confront some of our most important and enduring questions. And people seem to be leaning into that. So I find that hopeful, and I certainly feel energy about participating in that hopeful work. Beautiful. Thank you so much for accepting my invitation. I really appreciate it. Thank you, Peter. 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