Human Resilience in the AI Age

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There is a version of the AI future that does not arrive with a bang.
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No conscious machine announcing itself.
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No single moment when the meteor hits.
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Instead, it arrives quietly.
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A recommendation here, a risk score there.
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A route selected, a sentence completed.
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A candidate ranked, a child taught.
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A neighbour informed by a different reality from your own.
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And slowly, almost politely, artificial intelligence becomes the thing beneath things.
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An operating system for decisions, relationships, institutions, and everyday life.
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My guest today is Lee Rainey, Director of the Imagining the Digital Future Centre at Elon University.
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For more than two decades, Lee and Jana Anderson have been asking experts to look around corners and over horizons, producing more than 50 reports on the future of digital life.
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They began in the early days of broadband, then mobile connectivity, then social media, and now they are tracking what Lee calls the fourth great turning of digital life.
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Their latest report, Building a Human Resilience Infrastructure for the AI Age, asks what may be the most important question of all.
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Not simply what will AI do, but what will humans need in order to survive, adapt, and remain capable as AI becomes woven into the systems around us.
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In this conversation, Lee says something crucial.
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The challenge may not be one big artificial general intelligence moment, it may be the quiet takeover of systems and decisions.
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AI insinuating itself into the structures that already mediate our lives, work, education, finance, healthcare, government, media, and more.
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And that is where this conversation meets the heart of machine.
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Because the future is not only about smarter machines, it is about altered humans.
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Lee and I talk about resilience, but not as grit, not as the old idea of simply bouncing back.
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This report argues that resilience now has to become infrastructure, institutional, civic, educational, psychological, social, and ethical.
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We talk about existential literacy, about friction as a human good, and about why the future of agency may depend on our willingness to pause.
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This is not a conversation about rejecting AI.
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It is a conversation about what must not be handed over in my language, what is unmachinable.
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Because if AI does become the environment, ambiently so, then the question is no longer whether we will use it, but the question is whether we can remain human inside it.
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Welcome, Lee.
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It's so fantastic to have you here.
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Thank you.
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I know it's early where you are, although I know you're always an early bird, but you're early with everything.
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You are the early warning system on AI.
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That's our aspiration.
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We talk to experts like you to try to figure out where we're going, and that's our goal.
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Yes.
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Well, I followed your reports and your research work, both you and of course Jana.
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Jana Anderson, who I met, I think about 10 or 11 years ago.
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And you're both fantastic.
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I follow your work and try and share it as widely as possible, alongside lots of other contributors to your reports.
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But I wonder for people who aren't that au fay with yours and Jana's work here, whether you could just give a little bit of background how Pew and Elon have come together and the sorts of subjects and the way in which you research them has continued to evolve.
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I was hired at a think tank in Washington, the Pew Research Center at the Turn in the Millennium.
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And at the same time, my daughter was a student at Elon University in North Carolina.
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So I got to know the faculty there as I visited campus.
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They were interested in the work I was doing.
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I had also just come from a magazine gig where I was the uh managing editor of a newsweekly magazine in the United States that was famous for doing college rankings.
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And uh, so I was treated as royalty when I came on campus in the hopes that the rankings of the school would improve.
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And it did, but it had nothing to do with me and my daughter.
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It had to do with the school doing really well.
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Uh, but it it put me in touch quite early on with the faculty, especially in the communications department, the people who study media and strategic communications and information ecosystems.
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And soon enough, uh Jana Anderson and I, a professor at Elon, discovered each other.
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And she's a workhorse.
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She's just a great researcher, ambitious, and very indefagatable.
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She just wants to do lots of things.
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So we figured out we could do work together really quickly.
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So, really, for 23 years, we've been putting out these future of digital life reports.
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And in the early days, we were asking about what's the future of mobile connectivity and what's social media gonna do to us?
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And is the web gonna be overtaken by apps?
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And what are what's gonna happen with extremist groups?
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So we have this long-running uh series of reports.
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The the one we're gonna be talking about today was the 52nd report that we had done together.
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And we eventually got pretty good at sort of seeing where conversations were going, we're seeing where predictions were going about the internet, and we wanted to talk to experts like you about what they saw around the corners or over the horizon.
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So that sort of mindset informed a lot of our work.
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And and uh I thought I was going to retire from from my career uh when I left the Pew Research Center, but then the president of Elon called me up and said, Do you want to keep doing this work with Jana?
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And I said, sure.
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So that's why I'm now housed uh in the uh Imagining the Digital Future Center at Elon and since since mid-2023.
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And that's when we really became sort of enchanted with you and your work and begged you basically to answer our questions.
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And um, and so we've been doing a lot about artificial intelligence, this sort of the fourth revolution in digital life we've covered.
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The first was sort of early days broadband, you know, everybody thought that was radical at the turn of the millennium.
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Then we studied mobile connectivity, then we studied social media, and now this is the fourth turning of the wheel.
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So we're kind of lucky social scientists just for doing that.
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And we and it became really um obvious that the big direction we should go is what's the fate of humanity as artificial intelligence, particularly um the Big Bang moment was November 30th, 2022, when ChatGPT came into the world and everybody became uh aware that these systems were growing.
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So that's how we produced these reports about the future of human capacity, as well as now this newest report about uh resilience strategies for humans to uh make sure they survive the onslaught of AI.
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One of the things I've always loved about your reports, even before I was a contributor, which it is, by the way, an honor to be, is the blending of the, you know, the real executional, practical stuff that people talk about and that you include in the conclusions and the findings, and also the civilizational context.
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You know, it's so hard to put that macro and micro together or the conceptual and the practical together.
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But every single time you and your reports always do it.
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And the one that you just uh alluded to that came out in April 2026 is building a human resilience infrastructure for the AI age.
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It seems very different to some of the previous reports.
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So, for example, being human got a lot of stats in it, qual quant, drilling down into work and whether people think uh or the experts that you've interviewed or who've been surveyed think human work is going to be replaced by AI?
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Are they positive, negative, optimistic, pessimistic?
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This is much more conceptual and you've arrived at this concept of resilience.
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I wonder if you could explain a little bit about that and why you thought that that was, you know, the big sort of finding or outcome.
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Beginning a couple of months before we field the survey to be thinking about the main idea that we're going to pursue.
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And we and we are not driven by an agenda.
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We're we're in driven by where our sort of gut sense and our reading of the landscape shows us that you know interesting conversations are emerging.
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And we don't want to do Me Too work.
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We want to push the envelope, we want to be at the edge, and we want to think about things that people haven't yet really thought about in a in a grand context.
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So frankly, Tracy, uh, it was your answer in 2025 that pushed us to pursue the resilience idea in 2026.
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I will remind you that your answer, um, when we asked about human capacities, we were asking about what is A going to do to creativity, to curiosity, to social intelligence, to critical thinking, all the sort of basic stuff that had been talked about for a long time about how are humans going to survive the AI onslaught.
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And it was your ideas about the merger of machine life and human life and how to sort out the distinctions between uh machinable, as you call it, and unmachinable aspects of life.
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And it felt like it was a time for us to stop documenting people's worries and concerns and begin to think about strategies or capacities humans have to think about doing well as AI encroaches on so many more aspects of human life.
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And it was so interesting to just do the literature review on this.
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I had a vague sense about what might be said, but it was just so astounding to me for reasons that I probably should have anticipated.
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When you start asking about resilience, you're talking about a lot of painful things.
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You eventually get into the literature on PTSD.
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How do people survive deep trauma in their lives?
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You get into the literature about grief and who doesn't do badly as they're in the midst of a grieving process, and those who just get completely demoralized and lose faith and hope and capacity to rebound.
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And and so it was an interesting exploration in the first place.
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And one of the things we tried to do in the survey was explore different dimensions of resilience, and that that's where the magic came together in this report.
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We and frankly, there were just really fascinating and beautiful surprises in these data.
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And we we can go through those, but it was just a it was a different kind of learning experience.
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The other thing that it felt like an okay moment for a center like ours to really come up with something, it wasn't a manifesto, but it was close enough to sort of saying, here's how to think about this and work on it, not just sort of what are the diagnostics of what's going on.
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And it was a very different kind of report.
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I, you know, I'm glad you picked up on that because it was a it was given in a different voice than our previous reports.
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It was treated as a mini manifesto, and it was meant to launch new conversations about, okay, now we know this is going to happen to us.
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We know that our capacities are going to be challenged.
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So what do we do about it?
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And um and writing in that voice was a you know really interesting thing for us to try to do.
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How do you think the notion or concept of resilience has been received by those who weren't contributors who are outside of it, maybe in uh PR or the media or other academics who will obviously be following the findings of your reports?
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Uh tell me a little bit about whether it's been different.
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Maybe it's been the same.
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I don't know.
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It no, it has been different.
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And it in part because of the things I've already described.
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It felt like a um your invitation a couple of years ago was, okay, let's think about solutions.
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And it we we hadn't explicitly gone after that in the way we did directly in this report.
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So I think the reaction to it broke into uh some really interesting, distinct camps.
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There were some people who were just happy that we had something to say about solutions and something to say about a concept that moved the debate to a different plane.
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It wasn't just hand-wringing about the things that were going to happen, but it was thinking about strategies.
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Uh other people were really enchanted with or interested in the idea that we took as a surprise and wrote as basically the sort of headline overarching framework and concept of this report, which is that traditional notions of resilience and that and things that scholars and other experts had been looking at for generations, was not sufficient to be thinking about the future with AI in it.
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Their argument was, yes, of course, we'll have to be adaptive.
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Of course, the capacities for grit uh for absorption of challenges and moving on from them, the capacity just to persevere is always going to be important when you're thinking about resilience.
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But the real shocker to us was how many different voices, including yours, referred to institutional needs that are arising in this era.
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The basic argument was AI systems are now mediating so much of life.
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They're regulating our rights, they're regulating our risks, they're mediating the information that we get and things, that it will take a systemic response to those challenges rather than an individualistic response because you just need the force of institutions, you need the collective expertise of institutions, you need the enforcement mechanisms of institutions to push back against some of the most troubling challenges that AI has raised.
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It was fun to write that up because it was just not the thing we were expecting when we first went into the field with this survey.
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What's the age profile of most of the contributors?
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They're sort of middle-aged uh experts from a variety of fields.
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So there are people like you who are just sort of in applied critics and pundits and operational people who are trying to help people navigate this world.
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If the database we've developed is not representative, just we should say, as we're talking about this, this is not a scientific sample of expertise.
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It's it's sort of people we respect and we've watched and people who have interesting things to say about technology, some of whom fit your profile, just experts in the field doing the work.
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Some of them are scholars, a lot of scholars who are more from a critiquing and punditry perspective.
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Some of them are the pioneers of the internet itself.
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I mean, Vint Cerf, Doug Engelbart, uh, other people have been respondents to our surveys for forever, and we're so grateful to them.
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Some of them are building the technologies.
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Uh, it was really interesting to see that we had some folks here, both sort of inside some of the AI companies, and then people who had left AI companies partly because they're concerned about the future.
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So it's a it's a very diverse sample in its way, more male than female.
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We allow people to be anonymous in the surveys because sometimes we know they're inside companies where they aren't following the company line as they write their answers, so they don't want to get in trouble and they don't want to have their words misinterpreted as the official position of the company they work for.
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And it's it's a pretty North American sample, a good response from Western Europe in particular.
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But we we get a smattering of Asian and Ocean and respondents from Oceania.
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We we've had a much more um robust response rate in Eastern Europe this time than we have before.
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So it's it's a mixed bag, but it's it's uh, you know, people like us more or less.
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That's great background, actually, to that.
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I wondered about age because of the importance of institutions, as you say, that came out very clearly in the report.
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You know, this almost assumption that somehow, some way, institutions can crack this if we just help them enough.
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And I wonder if like a younger generation are like of um a bit over institutions or they want their own institutions, like we've seen the growth of Dow's decentralized sort of versions of governance.
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Um so it's what it's one of the interesting things, I think, is there an assumption that I think in the report it comes up quite a few times, you know, global institutions, for example.
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And of course, at the moment we're seeing the proliferation of the world into multipolar sort of spheres of influence.
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So the institutional question's a good one, isn't it?
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Yes, it is.
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And I you're right to pick up that that uh younger folks, just as a rule, are more skeptical, more wary, more likely to say that institutions just what are they?
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They're so old school and many of them are so hidebound.
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So, you know, it's a synonym with bureaucracy and red tape rather than the glue that holds civilizations together.
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But it was interesting here to see that there were uh uh sort of eclectic answers on this.
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There were some people who talked about distributed institutions.
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Uh, there were some people who talked about applying sort of the better practices from the modern era and collecting information and doing crowdsourcing of information that thought that institutions might be able to recover partly from that.
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But it's a tough sell, particularly in America, where the decline of trust in institutions has just been spectacular over the past two generations.
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So we're arguing upstream, uh, or the the experts that we're giving voice to in this survey are arguing upstream against institution building as a civilization strategy or societal strategy, because it's just no nobody uh is feeling very good about institutions these days serving people's purposes.
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Because in the report, one of the findings is, and correct me if I'm wrong, is it five layers for institutional first infrastructure?
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The second one, I think, that's in there is really interesting.
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It's that civic layer, which feels quite millennial in a sense, you know, community-driven, participatory, uh, thinking about your local area, shared values, collective deliberation.
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That feels to me like it was really bubbling up through the findings.
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Yeah, good read.
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And it to me, that's sort of the most exciting place of potential in these archives, because people don't necessarily think that civil society is in the kind of trouble that sort of formal institutional public governance structures are in trouble.
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And there are ways in which almost by force, because things are so bad, particularly in America with institutions, that building stuff from the ground up just makes a whole lot of sense.
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I mean, we picked it up in other ways in previous surveys and the work I was doing at the think tank, the Pew Research Center.
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The only way Americans think trust is going to be rebuilt is neighborhood by neighborhood, shoulder to shoulder, person to person solving problems.
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Because you know, toxic partisanship now is the dominant broad societal story.
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Nobody thinks that there's a way to break through that until people start seeing their neighbors as allies again.
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And of course, one of the big challenges of that that's that's implicit, no, it's actually explicit in a number of ways in this report is the epistemic fragmentation that we're going through, people having different realities that they're responding to, people having trouble navigating to the truth, people not having a sort of shared sense of what reality is, is one of the hindrances across the board on this, but particularly at the local level, where you and your neighbor might live in completely different information zones.
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And in your estimation of this, the machinable parts of them are just so at variance, they might as well be living in two different galaxies.
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So there's if there's a way that at least if you've got a local problem to solve, if the sewers need to be fixed, if there's a disaster in the local area where people literally have to help each other to survive well, that's the sense that people are going to be forced to come together to solve local problems because they can't avoid them.
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And that might be the formula for better institutional trust to emerge.
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I'm sure if politicians just let us all get on with it, it would be absolutely fine.
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That's just my my view.
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Um, you also have the cognitive layer.
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This is another theme that came up, I thought.
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I know everybody's jumping on the word literacy at the moment and attaching it to everything, but a kind of cognitive or AI literacy, but going further than just you know, cognition or metacognition, actually thinking about the ethics, the sociology, philosophy, some of the things that perhaps in decades and eras gone past you would have called it human flourishing.
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How does human flourishing and a cognitive layer sort of sit together?
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There were two things that were, again, sort of surprises to me coming out of these data that were so interesting to write up.
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The first is the almost across the board encouragement of these experts to build basically friction into processes that deliberate pauses, literally, that can be orchestrated by technology, but in some cases just by personal processes.
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Practices that friction is our friend, these folks were arguing.
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And it is the thing that AI is pushing against, is meant to solve.
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It's supposed to get us more efficiently to answers or to moving on with our lives.
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But there's so much argument in different contexts in this expert commentary that pausing, living with the messiness of humans dealing with each other in the context of metacognition, just remember where your blind spots are.
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Remember where you might default to an easy answer rather than wrestling with a harder answer.
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Obviously, the call to check your sources very well.
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And so there's this huge argument for what the Greeks taught us, which is a concept of phrenesis, which is practical applied wisdom.
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You know, you learn stuff in life and you then you live it because you've learned from your mistakes or you've advanced your knowledge and things like that.
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And so that that was one of the calls here.
00:23:01.759 --> 00:23:09.039
The other one was the strong encouragement of these experts to expand the notion of AI literacy.
00:23:09.200 --> 00:23:11.279
I mean, you know, you got to know how to use the tools.
00:23:11.359 --> 00:23:19.920
I mean, that's job one, just because you need to know what you're talking about and need to know how to frame your arguments or to frame how you're going to live your life with these tools.
00:23:20.160 --> 00:23:27.200
But the sense that that what they called existential literacy is the grander call to us.
00:23:27.519 --> 00:23:42.319
That an array of institutions, an array of personal practices, an array of ways that we were are civically going to be supporting each other is through teaching ourselves about the grandest parts of human existence, the stuff that you call unmachinable.
00:23:42.400 --> 00:23:58.000
You know, it's it's it is metacognition, it is critical thinking, it is collective um decision making, it's in and kicking back uh against the systems that are sort of forcing you to move in one direction or another or trying to make decisions for you and things like that.
00:23:58.160 --> 00:24:02.799
There's a sense that a quite whole framing of how to live your life.
00:24:02.960 --> 00:24:23.279
I mean, basically back to what those Greeks were talking about and what actually really one of the striking things about this work is that the people who have thought longest about resilience are people who are religious leaders and spiritual communities, you know, literally defining uh what communities are and how people um ought to consider living their lives.
00:24:23.599 --> 00:24:25.519
Yeah, that is really interesting.
00:24:25.680 --> 00:24:26.640
So let's get into it.
00:24:26.799 --> 00:24:28.640
Remind everybody, it's a big report.
00:24:28.799 --> 00:24:30.079
How many pages have we got?
00:24:30.319 --> 00:24:31.519
300 something?
00:24:31.839 --> 00:24:33.759
It's 375 pages.
00:24:33.920 --> 00:24:40.400
Uh, we sent out an invitation to a couple of thousand experts, and 386 responded to them.
00:24:40.559 --> 00:24:50.559
Again, a nice diverse sample, not the scientific study, so we're not trying to hold out our quant quantitative data as you know, absolutely dispositive from all over the world.
00:24:50.799 --> 00:24:57.519
And about 160 of you folks wrote really incredibly powerful, thoughtful essays.
00:24:57.680 --> 00:25:06.400
And so sorting through those essays and finding the themes and patterns in them was uh was the biggest job of writing the report on this.
00:25:06.559 --> 00:25:08.319
And frankly, AI made it better.
00:25:08.480 --> 00:25:16.720
I mean, it just there was a way in which we could be thinking about the arrangement of the themes and the orchestration of the report and the order of the report.
00:25:17.039 --> 00:25:22.000
AI was a big help in doing that sort of grand thematic first cut at the data.
00:25:22.319 --> 00:25:36.960
We turned it into our own stuff, but it was unlike previous years where we didn't have AI tools like this and didn't want to use AI tools like this, we now discovered that at least at the layer of organization and structure, AI was a really helpful part.
00:25:37.039 --> 00:25:41.200
And we asked you experts in our survey, you will remember when we got your answers.
00:25:41.359 --> 00:25:45.440
The next question after that was, how much did AI help you write your answers?
00:25:45.519 --> 00:25:47.759
And a lot of about three-quarters said, not at all.
00:25:47.920 --> 00:25:54.799
But a quarter of experts, you know, folks who know this stuff, said it was a help, and I used it, and I'm not gonna shy away from it.
00:25:54.880 --> 00:25:55.119
Yeah.
00:25:55.359 --> 00:26:00.960
Yeah, I remember answering that question because I was always I was hovering over thinking, I wonder how many people be honest about this.
00:26:01.119 --> 00:26:02.079
I'll be completely honest.
00:26:02.240 --> 00:26:17.920
I mean, they're my ideas, but I find them so much better crafted with the help of AI that it can summarize, pinpoint, compare, especially when you're in it, when you've been in an idea or a concept and you you you have your own blind spots, don't you?
00:26:18.000 --> 00:26:22.960
And actually, you want to say to somebody, can you objectively just sort this like a bit of a sorting hat?
00:26:23.279 --> 00:26:25.839
You know, what's the priority point I'm making?
00:26:26.000 --> 00:26:28.079
And I'm sure the same for you with the analysis.
00:26:28.400 --> 00:26:41.920
Well, and the other thing that I'm hooking up, it's just sort of sitting in the academy, as I do now at Elon in uh North Carolina, is that the most creative teachers of this stuff are encouraging exactly what you're talking about.
00:26:42.160 --> 00:26:49.519
You know, red team my answers, or show me where my blind spots are, or show me where my argument isn't convincing, and things like that.
00:26:49.599 --> 00:26:54.799
And it they're finding that their students are becoming better thinkers and writers because of it.
00:26:54.880 --> 00:27:04.880
And a lot of professors now are sort of saying, uh, as a matter of extra credit in the course, if you, student, teach me something about AI, I'm gonna give you an extra credit.
00:27:04.960 --> 00:27:09.279
So it's a co-learning environment where uh that shows up in our report too.
00:27:09.440 --> 00:27:11.039
Yeah, a bit of reverse mentoring.
00:27:11.119 --> 00:27:11.680
We love that.
00:27:11.920 --> 00:27:20.480
So, I mean, the chapters, I'm I won't I'm not going to obviously list them all here, but just to give people a flavor, they go from everything from you know prioritizing autonomy.
00:27:20.559 --> 00:27:29.920
I mean, agency, we'll talk about agency because it it's the first chapter and it's and it's I mean it's close to my heart, but it I think it comes out in the report just how important it is, cultivating human agency.
00:27:30.079 --> 00:27:53.359
But obviously, you talk about institutions, the ultimate team up, which we've just been talking about, humans and AI working together, existential literacy, which you also mentioned, workquake, we'll come back to that in a minute, navigating labor shifts and the pursuit of meaning, the great divide about the inequalities, heart and soul, you know, the thing about the human connection, overcoming complacency and the lure of convenience.
00:27:53.519 --> 00:27:55.200
I mean, that came through massively.
00:27:55.279 --> 00:27:57.519
And everybody feels it in there every day, don't they?
00:27:57.680 --> 00:28:07.519
And of course, misinformation, illusion, the epistemic vigilance, and lots and lots of broader insights closing off with what is the path to human flourishing.
00:28:07.839 --> 00:28:09.839
Can we go back to work quickly?
00:28:10.240 --> 00:28:17.440
Because you've done so much work on this through the previous um reports and and uh research as well.
00:28:17.759 --> 00:28:25.519
What did you find that was really surprising, or maybe nothing was, uh, but really surprising about this, navigating the labor shifts and the pursuit of meaning?
00:28:26.799 --> 00:28:31.039
We've had a really interesting evolution on thinking about this.
00:28:31.200 --> 00:28:35.680
Our first expert canvassing on the subject was 2013.
00:28:35.920 --> 00:28:44.000
So it was right after the first wave of reports from Oxford and some other places about the potential for massive job loss.
00:28:44.240 --> 00:28:51.119
So we asked the experts folks, are more jobs going to be created than lost or lost than created?
00:28:51.279 --> 00:28:52.880
And we had a 50-50 split.
00:28:53.039 --> 00:28:58.880
Half the experts said history is a good teacher here, that we've survived disruptions.
00:28:58.960 --> 00:29:05.039
It's it's been messy as the disruption occurs and it's it's caused a tremendous amount of human and community pain.
00:29:05.200 --> 00:29:15.759
But eventually we come out the other end with wealthier societies, more jobs being created, new jobs uh coming into being that were never possible before, and that should happen here.
00:29:16.160 --> 00:29:21.279
Those who push back against that answer basically said this is a different moment from the past.
00:29:21.440 --> 00:29:29.839
We've got, you know, the nano uh informatics revolution, we've got genetic revolution, we've got the cognitive revolution itself.
00:29:29.920 --> 00:29:31.039
We're studying the brain.
00:29:31.200 --> 00:29:36.880
And so at the same time, it's the term of art in the academic community, is polycrisis.
00:29:37.039 --> 00:29:46.720
There are so many things unfolding so fast on so many big fronts that you know humans can barely keep up with the biggest of them, the job quake kind of things.
00:29:46.799 --> 00:29:59.039
But there are we just won't survive this onslaught, and it will, and the disruptions that are gonna be caused are gonna be so disorienting that we basically won't have our wits about us and come out with solutions on the other end.
00:29:59.519 --> 00:30:14.400
So we move along, we move along, and even in that early survey, though, people were saying the saving grace for humanity, whether you thought the job quake was gonna break bad or break good, the saving grace was what was called soft skills.
00:30:14.799 --> 00:30:29.200
Remember that that phrasing, it was gonna be the um community-based things, the critical decision-making in uncertain environments, uh, critical thinking, social and emotional intelligence, and things like that.
00:30:29.359 --> 00:30:45.759
Well, soon enough, when AI began to show the capacity to look like it was doing things that were empathetic, that were exposing curiosity or somehow, you know, furthering creativity, this is now on the table.
00:30:45.920 --> 00:30:51.279
That's why we did the survey we did in 2025 about human capacity and followed up uh with this one.
00:30:51.440 --> 00:31:01.839
So, what was new in this report was the sense that people's jobs are now so deeply bound up with their identities, their sense of purpose, the way they make meaning out of their lives.
00:31:02.000 --> 00:31:03.839
That's the thing to be thinking about.
00:31:04.000 --> 00:31:10.400
There's still, you know, expert commentary one way or another about whether the job loss is going to be greater or less than what we currently have.
00:31:10.559 --> 00:31:24.960
But there's absolutely no doubt among you experts, I would say, that the way in which people think about how to build their lives and how to make meaning out of their lives, and particularly whether their job gets lost or not, it's certainly going to be disrupted.
00:31:25.119 --> 00:31:31.839
And figuring out how much work they want to do to make themselves relevant for pay and how much they want to move on to other things.
00:31:31.920 --> 00:31:33.200
That that's the play here.
00:31:33.359 --> 00:31:38.640
That's the thing that's most interesting to be thinking about as a future concern to address.
00:31:39.359 --> 00:31:39.839
Exactly.
00:31:40.079 --> 00:31:46.480
And curiosity came out quite high, didn't it, in um, as you mentioned, in the previous Being Human report.
00:31:46.799 --> 00:31:50.720
And I just wonder where are we going with curiosity and AI?
00:31:50.880 --> 00:32:00.720
Obviously AI is doing some amazing pattern recognition and it's delving into all of the training data that we are so um lovingly providing it with.
00:32:00.960 --> 00:32:06.480
But it can't think about or invent things that it has absolutely no training data on.
00:32:06.720 --> 00:32:13.200
Where do you think we are, either from your own point of view or through what came out through the report on curiosity?
00:32:14.319 --> 00:32:28.799
The new thing that it that we've done in these future reports since our uh three years at Elon is to add where relevant public opinion comparisons to the you experts and your data.
00:32:29.039 --> 00:32:36.000
If you might remember, in 2025, the experts were pretty sure that the impact of AI and creativity would be to expand it.
00:32:36.240 --> 00:32:41.359
I'm just personalizing my sense of what the answer is because they had different reasons for thinking that.
00:32:41.599 --> 00:32:54.960
But my sense is, and I bet you this is the case with you too, when you have an itch on any subject in any context, this can take you down the deepest rabbit hole that you want to go down.
00:32:55.119 --> 00:32:57.440
So it's not necessarily thinking up new stuff.
00:32:57.599 --> 00:33:10.640
I mean, I that I mean, which is a classic definition of creativity and a foundational one, but I'm thinking more like I'm sitting here uh as I'm I'm writing the questions for this survey that we field it to you on resilience.
00:33:10.720 --> 00:33:13.920
And I wonder what the grief community has taught us about this.
00:33:14.079 --> 00:33:22.480
I didn't know, but I found out relatively quickly and could then go to some incredible literature uh that helped us frame some of the questions on this.
00:33:22.720 --> 00:33:30.079
I wonder what the difference is between individualistic uh resilience and community-based resilience.
00:33:30.240 --> 00:33:39.519
Obviously, uh communities have suffered big losses, disasters uh, you know, in wartime, you know, just the kind of you know, horror that they're going through.
00:33:39.680 --> 00:33:41.119
What's the literature show on that?
00:33:41.279 --> 00:33:50.880
And again, AI is not a bad starting place as long as you don't get sort of tricked by it, or as long as you don't think it's you know the be-all and end-all answer to things.
00:33:51.119 --> 00:33:55.759
So I was thinking about creativity in that way as I was trying to interpret these answers.
00:33:56.000 --> 00:33:59.279
Uh and so I'm interested in kind of how you think about it.
00:33:59.359 --> 00:34:13.119
But the one other thing that was striking as we compared expert answers to general public opinion, just as average citizens, representative sample of American adults, uh, American adults were deeply pessimistic about the impact of AI and creativity.
00:34:13.199 --> 00:34:19.119
So they're different from you experts who are ha had pretty good hopes for it in that across the board.
00:34:19.199 --> 00:34:28.559
We uh all of these traits that we asked about in general public opinion, creativity was one of the things that average everyday folks thought that's gonna get hammered too.
00:34:28.639 --> 00:34:35.679
There's just uh no way AI isn't gonna overtake uh basically all the essential human traits that we were talking about.
00:34:36.000 --> 00:34:39.039
Yeah, that that's that's upsetting, isn't it?
00:34:39.280 --> 00:34:42.159
That um people think that, and that it could also do that.
00:34:42.320 --> 00:34:52.800
I mean, when I've researched things in the past or I've been working on projects, not everybody wants to be creative or they need a little bit of help at the beginning because creativity is quite intimidating.
00:34:53.039 --> 00:34:54.639
So people need a starting point.
00:34:54.719 --> 00:35:04.000
And I wonder if actually, you know, the whole role of AI is actually maybe to be a little bit of a starting point for that, to give some framework so that people can be creative.
00:35:04.159 --> 00:35:19.679
I mean, I've always thought that AI, certainly in the short term, is not going to make us more productive because I haven't seen over these longitudinal studies uh in the workplace that anything of all of these tools, the productivity tools we've got, has made us more productive, particularly.
00:35:19.920 --> 00:35:31.840
You may disagree, but I've always thought it would make us more creative, just especially for people who are working on their own or they have an idea and they don't have anybody in the home or in the office to discuss it with.
00:35:32.000 --> 00:35:41.039
Yes, you can't replace, you know, the watercooler moment where something sparks a completely innovative idea that, you know, is just very serendipitous.
00:35:41.199 --> 00:35:54.320
But imagine all of the things that go through one's brain in the day, a way of recording or linking them together, like having the, oh, I just thought of that in the shower moment, but through having a chat with ChatGPT or Claude or whatever, surely is a good thing.
00:35:54.400 --> 00:36:03.599
And I I really think at some level, I know there's a lot of talk about it really bringing in a lot of mediocrity, but I think for a lot of people it's going to upskill us in creativity.
00:36:04.000 --> 00:36:08.079
Yes, and there are in the two surveys that we're talking about of experts.
00:36:08.239 --> 00:36:20.400
I mean, one of the pieces I would say of conventional wisdom that now comes out of your world is that if done right, AI can be an incredible time saver.
00:36:20.559 --> 00:36:23.119
And so then the question becomes, what do you do with that time?
00:36:23.280 --> 00:36:28.559
And you can be an idiot about it and not creative at all and just laser day away or whatever.
00:36:28.719 --> 00:36:35.199
But if you if it sparks for you and it takes you down different pathways, uh, all for the good.
00:36:35.360 --> 00:36:50.000
And so there's a there's a sort of call in these data for thinking about where AI creates abundance and the possibilities that abundance gives us that it didn't give us before.
00:36:50.079 --> 00:36:55.840
I mean, professional expertise, for instance, is now being commodified in some respects.
00:36:56.000 --> 00:36:59.840
And where does it give us sort of new capacity to do new things?
00:37:00.079 --> 00:37:08.320
Where are opportunities being opened up that only required high levels of education, high levels of professional uh training and things like that?
00:37:08.480 --> 00:37:13.599
Where can now everyday citizens do that and bring their own sensibilities to those processes?
00:37:13.840 --> 00:37:28.800
There's gotta be a flowering in in directions of where abundance frees resources and where people feel the capacity to move on to other things because they've got now some other system humming away in the background taking care of the things that they used to spend their time doing.
00:37:29.119 --> 00:37:29.679
Exactly.
00:37:29.840 --> 00:37:44.639
Now, on the flip side of that, of course, uh, we had the film Idiocracy quoted in the report, and I'm sure it was more than once, and lots of people pointed to the fact that, oh, it's going to make people stupid or artificial unintelligence or human stupidity, etc.
00:37:44.880 --> 00:37:47.599
Can you talk to that theme as well and what the findings were?
00:37:48.000 --> 00:37:56.960
Well, the new thing there, I mean, obviously in the quest of uh human agency, there's a sense that the deferring to AI has been a long-running conversation.
00:37:57.119 --> 00:37:58.079
We've picked up on it.
00:37:58.159 --> 00:38:00.159
We did previous reports on it.
00:38:00.320 --> 00:38:07.280
What the new piece of it that you know made sense once I read it was that humans, first of all, we're efficiency machines.
00:38:07.360 --> 00:38:08.320
We want shortcuts.
00:38:08.400 --> 00:38:19.039
And we're and there are plenty of ways that the average human, even the discerning and caring human, you know, needs to practice heuristics and and to know where to, you know, not waste the time doing things.
00:38:19.280 --> 00:38:30.719
And one of the um tricks, I would say, in here in quotes maybe that AI plays on us is to give definitive answers or to give answers that look definitive, look sufficient.
00:38:31.119 --> 00:38:36.239
If you're a satisficer, you know, that's good enough if you've got to hand in a report to your boss.
00:38:36.400 --> 00:38:48.480
Um, and that the the definitiveness or the seeming definitiveness of AI answers is going to be one of the real traps of it, that we will defer to it in ways that are just totally inappropriate.
00:38:48.639 --> 00:38:59.760
And so that was one of the elements of what you're talking about, which is the wall-e world, where you know people are sipping their umbrella drinks at the poolside and just letting AI do everything for them.
00:38:59.840 --> 00:39:18.159
Um, and again, sort of that goes back to this idea of uh friction finding or practices bringing friction to your work to make sure that you're in the in the loop and that your sensibilities and your perspective and your capacity to think through things is enhanced rather than uh handed off.
00:39:18.719 --> 00:39:31.440
Yeah, because a lot of people were talking about just how invisible it's going to become, and that that makes it easier to sort of hand off things to it because I think you were talking of it in terms of being frictionless or friction-free.
00:39:31.679 --> 00:39:35.199
But that invisibility, I think that invisibility worries people.
00:39:35.760 --> 00:39:37.599
Yes, uh very much so.
00:39:37.760 --> 00:39:55.360
The um again, sort of that's the um the element of the uh important finding at the very beginning of the report, which is essentially in many of these experts' estimations, the arrival of artificial general intelligence or artificial superintelligence, a big bang moment.
00:39:55.440 --> 00:39:59.280
The meteor is gonna hit, and then you know, the day after that, everything has changed.
00:39:59.440 --> 00:40:20.000
There was a much more subtle and interesting, and I in my sense of it was a reasonable argument that it's the quiet takeover of systems and decisions in the insinuation of AI into systems that already exist that evaluate and mediate and make recommendations and make predictions about us.
00:40:20.159 --> 00:40:29.360
So there's that silent operating system that these experts were talking about when they were talking about rebuilding and newly building institutions that will have our backs.
00:40:29.519 --> 00:40:32.320
I mean, it was in some ways you can't keep track of all of this.
00:40:32.480 --> 00:40:48.800
So you need uh systems of accountability and insistence on transparency and enforcement mechanisms because it's just too complicated for individuals or even groups of individuals to pay attention to every element of this that is bringing itself into your life.
00:40:49.039 --> 00:41:01.199
So that's that was the institutional argument, and and I'm glad you brought that up because it was, you know, these are scholars and in and folks with insights, even in the tech world, where it's not going to be when the meteor hits that's the big moment.
00:41:01.280 --> 00:41:06.480
It's gonna be the quiet takeover and the quiet ways in which it insinuates itself into our lives.
00:41:06.800 --> 00:41:17.199
Yes, because towards the end of the report, you talk a lot about there are findings around physical AI and AI becoming, you know, part of an ambient system.
00:41:17.360 --> 00:41:19.360
This is what I mean by the invisibility.
00:41:19.519 --> 00:41:21.360
Obviously, we're in a sort of halfway house.
00:41:21.440 --> 00:41:25.519
We're in we know we're not we're nowhere near that yet, but people can already feel it happening.
00:41:25.679 --> 00:41:41.519
And so they're talking about AI coming into smart systems, as you say, embedded into them, where you'll have, you know, the sensors and the facial recognition and the biometrics all talking to each other to act, maybe on behalf of citizens, maybe not, in real time.
00:41:41.679 --> 00:41:56.559
And I was looking, I mean, I've had for several years in my presentations that humanoid robot that they have on the streets of Bangkok, for example, you know, which is it's all very well looking as sort of Optimus and all the things it could do in the home and having a humanoid in every home, etc.
00:41:56.719 --> 00:42:12.800
But the flip side of that is, you know, having these kinds of humanoids or any kind of AI embedded in the infrastructure, embedded in the systems we've got, bringing together facial recognition of street protesters, identifying them, looking at their records, making an arrest, whatever it might be.
00:42:12.960 --> 00:42:18.480
And all of a sudden it's all happened before any human brain can really put any of this together.
00:42:18.880 --> 00:42:27.679
Yeah, the real timeness of that, the fact that these systems can, first of all, sense information and then process it.
00:42:27.840 --> 00:42:32.880
And that and the context, therefore, of the application of AI, it's responsive to that.
00:42:33.039 --> 00:42:42.239
I was at dinner with a friend last night who was repeating the thing that you and I have heard a whole bunch, but it was astonishing and and deeply demoralizing and frightening to him.
00:42:42.320 --> 00:42:53.440
He said, Do you know if you jaywalk in China, you get a text saying you're the you've been fined$25, and it's before you hit the curb on the other side of the street.
00:42:53.519 --> 00:43:00.079
And I say, Yeah, that's what's that's what's going on, and that that's exactly the ambient quality of this stuff.
00:43:00.239 --> 00:43:03.119
And it's yes, it's it's the programming in real time.
00:43:03.199 --> 00:43:08.320
So, you know, long ago, computer systems had to think about how to program everything.
00:43:08.480 --> 00:43:10.480
If this, then that, and things.
00:43:10.639 --> 00:43:23.199
In in this new era, it it's really operating on real-time information, real-time insights, real-time context that is the special flavor of AI in this ambient world.
00:43:23.599 --> 00:43:26.880
Yeah, and who does AI ultimately work for?
00:43:27.039 --> 00:43:29.119
Was a brilliant question by John Battel.
00:43:29.199 --> 00:43:32.880
And I thought that's one that's so easy to overlook, actually, isn't it?
00:43:33.280 --> 00:43:33.599
Yes.
00:43:34.239 --> 00:43:58.320
And as again, with these expert surveys and the real-time research I was doing at the Pew Research Center, one of the striking things about social media as we were studying its rise, you will remember this, in the earliest days, 2008, 9, 10, with Facebook, Twitter, and things were just coming into being, there was almost universal hope.
00:44:00.159 --> 00:44:02.079
Democratize information ecosystems.
00:44:02.159 --> 00:44:04.400
It was going to allow many more people to tell their stories.
00:44:04.480 --> 00:44:12.639
The gatekeepers were smashed, and look at what, you know, how they were limiting the capacity of people to learn about each other and learn about things.
00:44:12.960 --> 00:44:20.719
But the thing that didn't get insight at first was that those systems were optimized for attention and engagement.
00:44:20.880 --> 00:44:28.960
The business model was, you know, keep people on these systems as long as possible because we're selling ads to them, or we're selling them to advertisers, really.
00:44:29.440 --> 00:44:45.840
And when you optimize, who it turns out that we learned around 2012 with Edward Snowden, and then later in the sort of misinformation fake news era of the 2016-17 type, that when you optimize for attention and engagement, you go to the bottom of the brainstem.
00:44:46.079 --> 00:44:47.679
You find out what angers people.
00:44:47.840 --> 00:44:59.440
You get them paying attention to your site and your information by annoying them and by creating enemies for them and creating opportunities for them to attack their enemies and sometimes doing even worse than that.
00:45:00.000 --> 00:45:07.519
The new thing that AI is adding to that makes this not only is it optimized for attention and engagement, it's optimized for intimacy.
00:45:07.760 --> 00:45:20.800
If you think about the AI agents that are being created and the systems that are being created to encourage interactions with AI agents, is that you have to trust them with your information to act on your behalf in the world.
00:45:20.960 --> 00:45:30.719
And you have to figure out how to cope with the other systems that are representing other people and institutions in the world.
00:45:30.880 --> 00:45:33.440
And so the way to do that, of course, is to build intimacy.
00:45:33.679 --> 00:45:44.320
That's how you build trust, is you are vulnerable, you are more disclosing over time, volume of interaction increases with the people that you trust and the institutions that you trust.
00:45:44.559 --> 00:45:50.079
And so you study the incentives and you study a lot about how systems are going to unfold.
00:45:50.159 --> 00:46:01.519
So one of the reasons that you all were arguing, you all experts were arguing for institutions, is that's just even more dangerous than just attention and engagement.
00:46:01.599 --> 00:46:07.519
If you're optimizing for I'm gonna like you, I'm gonna trust you, I'm gonna maybe fall in love with you.
00:46:07.760 --> 00:46:20.960
Um, that's that's a it's a handoff of human agency and human and information about people that's exploitable and um that can be turned to great harm uh on in the wrong hands.
00:46:21.119 --> 00:46:26.639
And so there's a that that's I think that's exactly what John Battel is arguing for here.
00:46:26.880 --> 00:46:44.000
If you are not in charge of the agents working on your behalf, if you haven't sort of made sure that you, at the end of the day, you the person are making the final call and things that matter to you, that's just a recipe for uh the loss of human agency and the loss of human capacity.
00:46:44.400 --> 00:46:45.440
I completely agree.
00:46:45.599 --> 00:46:55.760
And I mean, when I've been thinking for a long time about, you know, the psychology of the self, the biology of the self, and then this third dimension, the technology of the self, I've always said but we don't own the technology.
00:46:55.920 --> 00:47:01.039
So it's a part of ourselves that we're now connected to and dependent on that we don't actually own.
00:47:01.199 --> 00:47:15.679
I mean, you could take it to its extremes and think, you know, in future, if you're uploading or downloading skills or whatever and you're using those, if you don't own the channel, you don't own the pipe, you don't own the connection, you know, you're just signed up to some terms and services.
00:47:15.840 --> 00:47:22.719
Anybody can switch that off anytime they like, and you can think about that in any number, hundreds and hundreds of different examples.
00:47:22.880 --> 00:47:28.960
But it reminds me, you talking like that reminds me that about anthropomorphism, because that comes out in the survey as well.
00:47:29.119 --> 00:47:39.920
I mean, people like David Gunkel, who um I just think his work is fantastic, and he's been talking about robot rights, robot rights are coming for what, 15 years, probably more.
00:47:40.079 --> 00:47:44.639
And that shows up for the first time, really evidentially, I think, in this report.
00:47:44.800 --> 00:47:57.679
And people seem to have a worry about robots or AI having its own rights, and at the same time that it's going to be anthropomorphized in order to create that kind of digital intimacy that you've just been talking about.
00:47:57.840 --> 00:48:02.559
So those seem to be another two themes that come out very clearly again this year.
00:48:03.039 --> 00:48:12.719
Yeah, uh the ultimate question there is, of course, when human rights clash with AI rights, how are the courts going and judges going to decide?
00:48:13.119 --> 00:48:14.480
You mean the AI courts?
00:48:14.719 --> 00:48:18.800
Yeah, that may maybe that's yeah, that's part of the mix here.
00:48:19.039 --> 00:48:32.480
But you know, there have been some pretty powerful arguments that we have already lost sort of the human-centeredness of the rights debate by handing so many rights to corporations.
00:48:32.639 --> 00:48:36.719
I mean, they act in our behalf, that there's a logic to thinking about that.
00:48:36.800 --> 00:48:44.800
They make deals on our behalf, they regulate in some aspects of our lives with human capacity already being adjudicated.
00:48:45.280 --> 00:48:54.320
But, you know, it just creeps people out to think that the systems might be given the same deference that corporations are.
00:48:54.480 --> 00:49:01.280
In America, sort of the most debatable or the thing that's most hotly debated is political speech.
00:49:01.519 --> 00:49:13.519
And now, you know, it's enshrined in our laws in America that corporations have speech rights and can give money, and money is equivalent to speech in basically any way that they feel like it.
00:49:13.679 --> 00:49:20.159
And so we're already, we've already sort of lost the claim of human uniqueness in a legal context.
00:49:20.239 --> 00:49:36.079
And there, of course, there are other people who are arguing at some point, once we understand maybe what consciousness is and and things like that, there might be ways in which these systems themselves, with all the connections they make and all of the intricacies of and sophistication of them, they're eventually going to have feelings.
00:49:36.239 --> 00:49:38.079
They're gonna potentially uh suffer.
00:49:38.239 --> 00:49:43.760
And uh, that's a hairy one for for us to be thinking about, and it's definitely in our future.
00:49:44.079 --> 00:49:44.480
Yeah.
00:49:44.800 --> 00:49:48.559
So, Lee, as we just start to conclude this, what if we missed out?
00:49:48.719 --> 00:49:56.800
What have I not asked you about that you think's really important that came out in the report and and people listening to this need to know about or they should dig into a bit further?
00:49:57.119 --> 00:50:02.960
I just want to carry on the argument about the John Patel argument, basically operating on our behalf and things.
00:50:03.280 --> 00:50:17.280
Because one of the, to me, surprising predictions here that it just makes total sense once you think about it, is that we're heading into a world where we're already bound up in our relationship with AI agents in some respects.
00:50:17.519 --> 00:50:21.679
The social complexity of that is going to be pretty staggering.
00:50:21.840 --> 00:50:33.199
You know, we right now we our brains have evolved for managing relatively intimate relationships with, you know, if you believe Robin Dunbar at Oxford for about 150 people.
00:50:33.360 --> 00:50:41.519
You know, we to know who they are, who their alliances are with, how to work with them, to figure, you know, have a theory of mind of them, all that sort of stuff.
00:50:41.679 --> 00:50:48.880
And in the arrival of the internet, I started sort of trying to mimic his work, and it's it's so sophisticated, it's it's not possible to do anything.
00:50:49.039 --> 00:50:52.079
It was not easy to do with the available tools.
00:50:52.239 --> 00:50:58.639
But maybe 500 to 1,000 relationships are things that we manage, even you know, folks that we don't necessarily know.
00:50:58.719 --> 00:51:09.920
But with these tools now and connectivity that was baked into them and the social graph that was baked into them, we've got you know orders of magnitude, more relationships that we are regularly trying to work our way through.
00:51:10.079 --> 00:51:26.480
Once you start adding AI agents to that, both my agents acting for me and your agents acting for you, and corporate commercial agents acting for them, and government agents and their uh AI systems acting for them, the complexity of that is gonna be mind-bending.
00:51:26.639 --> 00:51:43.519
And again, it's sort of the call for institutions to sort of serve our purposes and to make sure that we just don't get overwhelmed by that, that we don't become inundated with in ways that we can't possibly manage our ways out of, that we lose our agency almost by default.
00:51:43.920 --> 00:51:45.280
I was gonna say exactly that.
00:51:45.440 --> 00:51:46.719
Are we even involved?
00:51:46.960 --> 00:51:48.880
Like are we even?
00:51:49.039 --> 00:51:59.280
Is that I know it's the classic the human in the loop, but it's difficult to know at what stage, what interjections, what uh permissions, for example.
00:51:59.440 --> 00:52:08.880
Because when you talk about frictionless, and other people did in the re report as well, when I hear frictionless, a lot of the time I'm thinking permissionless, it's just it's completely permissionless.
00:52:09.280 --> 00:52:09.760
Yeah.
00:52:10.079 --> 00:52:19.280
When we did a survey of U experts a couple of years ago asking about the prospects for ethical AI, the grand finding of that was who's ethics?
00:52:19.599 --> 00:52:34.400
Because we all walk around in our heads with different moral values, with different contexts of our moral upbringing, with different schooling in and around how to be in the world and how to think about the world, how to be a good or intelligent agent in the world.
00:52:34.559 --> 00:52:47.039
And so customizing that for the variety of individuals that are going to want to enact their agency and their morals in circumstances where others might not want them to.
00:52:55.760 --> 00:52:56.559
Yeah, exactly.
00:52:56.639 --> 00:53:11.519
And to take that point and a couple of others that you've been talking about and we've been touching on, I think if you don't have your own agency, not only can you act on your own behalf, but you can't envision a future for yourself either.
00:53:11.760 --> 00:53:13.119
And I think this is really important.
00:53:13.199 --> 00:53:36.559
And I've written some papers there on ResearchGate, and I know and other people are starting to look at this, I think, in this whole AI-mediated world feeling quite pre-decided, um, and pre-decided on the basis of, as you say, you know, not your ethics, my ethics, but some invisible or potentially corporate-based ethics, who who knows, because we you don't actually know you're not in the system.
00:53:36.719 --> 00:53:41.199
The system is applied to you, but you don't necessarily have any agency or any say in it.
00:53:41.519 --> 00:53:55.199
And I think this is really interesting that without this sense of agency, regardless of thinking about what's human and what's uh non-human, but without it, you can't create these possible futures, these plausible possible futures, a preferential future.
00:53:55.440 --> 00:54:04.239
And actually, you're just coasting along, being sort of nudged and directed in somebody's version of the future, but isn't necessarily yours.
00:54:04.320 --> 00:54:16.079
And I think it's really interesting that uh Carissa Valise has just come out with her book Prophecy as well, which seems to be talking about something similar, you know, the algorithms are pushing you in a certain direction.
00:54:16.159 --> 00:54:33.360
And I would say it's not just that, it's that you don't notice that and you don't even know that you could have a choice in a situation because not only is a choice not given to you, it doesn't even occur to you that you should have a choice because everything is running on these rails, if you like, these AI rails.
00:54:33.679 --> 00:54:47.199
I don't know what your thoughts are on that, whether you I'm sure you've been thinking about it, but in this predecided algorithmic world, who is actually defining and deciding our future because it doesn't even feel like it's us.
00:54:47.760 --> 00:55:02.719
Yeah, some of the most interesting insights from this new report was to think about not so much the enablement of the kind of things you're describing, but how to create adversarial ways to push back against them.
00:55:02.880 --> 00:55:23.599
I mean, in some respects, sort of the grand, one of the grand insights of the Enlightenment, and then you know, the creation of the kinds of governments that we currently have is to know that there are disputes inevitable in any kind of human environment, and to think about how humans can enact their interests by contesting things, by demanding answers about who's responsible.
00:55:23.760 --> 00:55:29.679
Yeah, by even declaring if an AI system screws up, who's gonna take the fall?
00:55:29.920 --> 00:55:33.280
The current argument might be these are black boxes.
00:55:33.440 --> 00:55:40.480
We don't know that the forensics are too mysterious, uh, and we we can't um dissect who made the problem.
00:55:40.559 --> 00:55:48.000
Well, then the argument should be well, if you can't figure that out, maybe these systems shouldn't be given the kind of power that they're given.
00:55:48.079 --> 00:56:13.119
So it's not so much how to enable all the glorious things or how to the some of the possibilities of the dysfunctional things you're talking about, but just sort of putting in place the kind of institutional pushback and friction and giving humans the right to sort of assert themselves in environments where, as you're so lovely describing, they might not feel that they've got a choice.
00:56:14.159 --> 00:56:14.800
Yeah.
00:56:15.039 --> 00:56:19.119
Um, so just to wrap up, did you see um the students at the university?
00:56:19.199 --> 00:56:35.840
There was a university in Florida, you'll know it better than me, who had a point of view about the um that speech, the graduation speech, when it was put to them that, oh, we're launching into the world of AI, the new era, the next industrial or intelligent revolution, and she got booed.
00:56:36.000 --> 00:56:37.519
What were your thoughts on that?
00:56:38.400 --> 00:56:47.280
Well, there's this really emergent conversation in the United States, I think in the UK as well, is um the backlash is forming pretty aggressively.
00:56:47.599 --> 00:56:51.519
And the points of friction are there are a couple of them.
00:56:51.679 --> 00:56:53.519
One is literally the data centers.
00:56:53.679 --> 00:56:59.039
So there's a lot of new evidence, starting at the place I used to work, the Pew Research Center, but now lots of polling being done.
00:56:59.440 --> 00:57:02.639
There's a NIMBY, not in my backyard sense of this.
00:57:02.800 --> 00:57:03.840
Don't build them near me.
00:57:04.000 --> 00:57:08.559
They're not going to be good, they're going to hike my electricity rates, they're not going to create meaningful new jobs.
00:57:08.800 --> 00:57:10.800
They make so much noise, people can't even sleep.
00:57:11.039 --> 00:57:11.440
Yeah.
00:57:11.679 --> 00:57:16.719
And at the student level, uh, you know, the students who booed that speaker were humanities students.
00:57:16.960 --> 00:57:31.360
So it was the people who are sort of by definition of how they've organized their education, are thinking of these about these existential questions and worried about human capacity in the way that folks who study humanities think about it.
00:57:31.440 --> 00:57:33.280
I mean, that's the glory of the humanities.
00:57:33.360 --> 00:57:40.639
You think about this stuff and ponder the mysteries of it and think of all the ways it gets screwed up and all of the ways that we fight back.
00:57:40.800 --> 00:57:42.639
But that's you know, that's their frame of reference.
00:57:42.719 --> 00:57:51.679
So having somebody come in and say, this is going to be a big force in your lives is not necessarily not knowing your audience, among other things.
00:57:51.920 --> 00:58:01.039
But the um ways in which the backlash is forming feel to me quite like you could begin to see it with social media around 2014-15.
00:58:01.280 --> 00:58:13.440
Um, that the original enthusiasm was very much sobered by the Edward Snowden, the information wars, and and all that stuff of the 20 teens.
00:58:13.920 --> 00:58:20.079
And that infrastructure of opposition and skepticism and pushback and wariness is now in place.
00:58:20.480 --> 00:58:40.719
Thanks to social media, there and almost immediately now there was a community of smart people and smart institutions that basically push back or just sort of say, wait a minute, let us test it before you let it loose on the wider world, or here are the things that you uh you're gonna get sued for if you don't do it the right way.
00:58:40.960 --> 00:58:50.320
And so that's now you know already in place in the United States, and this backlash, particularly among the young who are deeply worried about their futures, not just humanities students.
00:58:50.480 --> 00:58:52.960
It there's this sort of dread you know coming out.
00:58:53.199 --> 00:59:10.480
Remember their education, the dominant force of their early education was COVID and getting remote learning and all of the trials and troubles of that, and losing your friendships, losing your extracurricular activities, not being able to make new friends, not being able to socialize.
00:59:10.639 --> 00:59:18.000
That's all informing a sort of deep skepticism among the young in some cases for the future they're heading into.
00:59:18.320 --> 00:59:31.360
Well, that seems a good note to end on, but let me just give you the opportunity to say anything else you'd like to about the report or the importance of the main findings, and also maybe hint at what's next.
00:59:31.760 --> 00:59:38.239
I mean, people are hungry for answers or hungry for insights that can help them enact their agency.
00:59:38.320 --> 00:59:43.199
And so thinking about that and probing some of the obvious questions that came out of this survey.
00:59:43.599 --> 00:59:46.239
You know, what is the flavor of the of the backlash?
00:59:46.400 --> 00:59:53.360
What are what are the ways in which uh these companies are going to have to adjust to the growing opposition that's coming?
00:59:53.519 --> 01:00:00.880
You know, for a while we've said that there's an arms race between the United States and China, and that's in an American policy, that's the primary thing.
01:00:01.039 --> 01:00:09.039
Now the Trump administration itself is sort of saying, wait a minute, we're watching the models, making them report to us when they're coming into being is a good thing.
01:00:09.199 --> 01:00:20.159
So there are ways in which the exploration of human capacity and human glory and and the sort of great things that have uh helped us, you know, for better or for worse, conquer the planet.
01:00:20.239 --> 01:00:23.280
That that feels like the call of the future research.
01:00:23.599 --> 01:00:23.920
Yeah.
01:00:24.079 --> 01:00:26.880
Well, I depend on your brilliant reports.
01:00:27.039 --> 01:00:28.960
They're amongst my absolute favorites.
01:00:29.119 --> 01:00:30.880
Thank you for doing them, obviously.
01:00:30.960 --> 01:00:32.159
And they're always splendid.
01:00:32.239 --> 01:00:34.960
We'll put a link to everything, obviously, in the show notes.
01:00:35.119 --> 01:00:37.119
But just thank you again, Lee, um, for your time.
01:00:37.199 --> 01:00:41.440
It's a privilege to get to speak to you, and thank you for all your and Janna's work on this.
01:00:41.519 --> 01:00:45.280
And I hope that we can get more and more people to read them and contribute, I'm sure.
01:00:45.599 --> 01:00:46.159
Thank you so much.
01:00:46.400 --> 01:00:47.760
So fun to be with you, Tracy.
01:00:48.320 --> 01:00:51.679
Mechine Dialogues is a special series from the future of you.
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