Event page & Video recording

250 years in, the American experiment stands at a crossroads. Where will we go next?

Founded on bold democratic ideals, the US has continually reinvented itself: expanding civil rights, absorbing generations of immigrants, and emerging as a global superpower. Yet the very forces that have fueled our country’s growth now raise urgent questions about its future. Gathering leading thinkers, policymakers, and experts for a day of virtual conversations, the State of America Summit explores where America is headed next as we approach our nation’s 250th anniversary.

How resilient are the institutions that have sustained us? What lessons can be drawn from our historic triumphs — and shortcomings? Join us as we map out a new era of the American experiment.

American Labor at 250

featuring Beth Simone Noveck, Allison Pugh, Betsey Stevenson

From farms and factories to offices and Silicon Valley algorithms, the history of America is also a history of work — and new technology is bringing about a sea change in American labor. AI stands to bring about massive disruption: millions of jobs stand to be both displaced and created worldwide in the next five years. Even as new industries and skill sets emerge, all American workers — blue-collar, white-collar, and everyone in between — will have to contend with a new labor reality. What is the future of American work? Who will have the power to shape it?

Transcript

Betsey Stevenson: Hello! Well, welcome to our conversation about the future of work. I am really excited to be joined today by, Allison Pugh and Beth Novak, and we are going to be moving beyond this question of what jobs will AI take. To think about some of the more subtle questions about how AI might change our social and institutional relationships by changing work. How… can we… keep things deeply human, even if AI can do it, and who's going to have the power to make these decisions as the technology advances? So when I, when I was asked to participate in this, one of the things I really, really loved about this conversation was just the very different perspectives that we each bring. So, I'm an economist, and I really bring that economic lens to the question of sort of thinking about who bears the costs, and who might capture the gains. And, you know, Beth, when I think through your work.

Betsey Stevenson: Really around, like, democratic capacity and institutions and the role of citizens and workers in participating in decisions. I think you really bring this important institutional lens that, honestly, personally, I am spending a lot of time thinking about, because I think it might matter more, honestly, than the economic lens. And then, you know, Allison, your lens is much more experiential and sociological. And I will tell you, I've also been thinking a lot about your lens lately, which is this idea of the roles we play in society, and how they're going to be shaped, the dignity, the security, belonging, you know, what is the connective labor that we do that brings us together as a… as a society. So, all of that, I think, brings, you know, a lot of questions about what we think are gonna change, and so I'm just gonna open it up with

Betsey Stevenson: One big picture question, which is, what do you think are the consequential changes that… is missing in today's conversation that you're most… worried about or optimistic about that might come to fruition because of technological change? And Allison or Beth, either one of you can, chime in.

Allison Pugh: Beth, why don't you go first?

Beth Simone Noveck: I'm happy to…

Allison Pugh: Do whatever you want.

Beth Simone Noveck: I'm being put on the spot here, but I'll be happy to take the baton here, and I agree that I'm only going to go first so that I get to hear from both of you in short order, because the different perspectives are what's so exciting. So I think, to cover both the negative and the positive, let me sort of do kind of one on each front. My concern, and Betsy, this is really a question that I'm going to want to ask back of you, is that so much of the conversation around work and the impact of AI really is dominated by the economic lens of productivity and efficiency. And I'm concerned that, and that's not new to AI, we talk about this with every technological advancement, and it's understandable why we want to understand the efficiencies that AI is going to bring for us, but I think it obscures a lot of the question about productivity for what? Efficiency for what?

Beth Simone Noveck: and is obscuring a conversation, especially in the work that I do, thinking about the public sector and its adoption of AI, but not exclusively, is, is it leading, is this adoption of AI leading to better decisions? Is it leading to better value for the public and customers? Is it leading to better work for workers? And I'm very interested in Allison's perspective here about both the economy of care, again, for workers and for those that they serve. So I think, you know, we tend to… the question of what we value is obviously what we measure, and what we measure is what we value.

Beth Simone Noveck: So that's one of the negatives that I'm concerned with, or at least one of the problematical things, and I'm glad we're going to open up that conversation. The positive, let me say, is that one of the greatest powers of these technologies is because they're so good at measuring patterns in data, and now measuring patterns in words. is these are superpower technologies for enabling new kinds of listening at scale, and I hope we'll get into that. And that listening could unlock the ability for better conversations with workers, with the public, about what we want the future of AI to be in our workplace, in our schools, and in our communities. I think that's a conversation we're not yet having. It's a super hopeful and positive conversation about the way that these very same tools, even as they may disempower us on some

Beth Simone Noveck: Fronts could actually be very empowering and give us more voice in how we deploy these technologies in the workplace. So let me stop there and pass it to Allison.

Allison Pugh: Hmm. Thanks, Beth, and thanks, Betsy. I'm really looking forward to this conversation. That's a very positive vision. I agree with so much of it. I agree that, you know, what we measure is what we value, and that is a feedback loop that actually can be quite damaging, because what do we do with that which we can't measure? So, if we're thinking about, like, AI as a labor-saving device. it kind of implies that the only thing we care about is labor, and some things start to be defined as labor, and what does that leave for us at the end of the day? Where is art? Where is care? Where is relationship? And if AI is doing that, then… I don't know what it's for. And so I'm much, as I guess is obvious, I'm much more skeptical about its power, I would say, or it's, you know, kind of, it has a force for good. I would say that, you know, I would… I'm very…

Allison Pugh: pro-AI, really, about, things that don't involve human relationship. So, I'm very interested in AI and, you know, as a… I know that they're doing things like inventing new antibiotics for, you know, bacteria that are antibiotic resistant, you know, helping us in that rat race, and I'm… interested… I was thrilled to hear that, AI was helping us decode sperm whale speech, and all sorts of things like that, you know, like, great, the mystery that AI can… mysteries of life that AI can solve. My problem is that it's actually increasingly, since its deployment, since generative AI's deployment in 2022, I guess we're talking about, it… it… It's, increasingly being deployed

Allison Pugh: as to replace and to… to replace humans and to automate relationship. And, Betsy, you kind of said… you kind of asked us, what are we not talking about? In my opinion, that's what we're not talking about. We're talking… we talk about, as we… as we say, efficiency, productivity. Even AI critics, I think, talk about bias, and they talk about surveillance, and they talk about job disruption. But I am, like, laser-focused on the impact of AI on human relationship. We have… we are… we are kind of in the… in the heyday of… social science demonstrating the impact of human interaction on human well-being. These are kind of… the studies are coming in, you know, fast and thick, that are proving the impact of human interaction, social… social interaction on human well-being. And the At the same time, for some reason.

Allison Pugh: maybe coincidentally, we appear to be hurtling towards the automation of those relationships and those social interactions, and I, for the life of me, do not understand why we are on this course, and that's the kind of conversation I want us to be having, first and foremost.

Betsey Stevenson: So, I want to pick up on something that I think can connect directly between the two of you, and this is, like, our ability to relate with one another. And Beth, one of the things you said was, maybe we'll get better at listening. And Allison said… you said, at least we might get better at listening to sperm whales, and I actually… I love that idea! Like, I was like, okay, that… I really am on board with, listening. And… but I guess I really wondered whether we would get better, or potentially worse. And… I'm gonna give you, like, something that… you know, I… I don't know how many… if either of you have paid much attention to Starbucks' unionization effort, but, like, one of the things that was really interesting to me about it was the reason Howard Schultz was so…

Betsey Stevenson: upset or, like, confused, was he was like, I gave you all the things you wanted. I gave you, like, good wages and healthcare and education benefits, so why would you need this stinky union? And the answer was, because we don't have a voice. And you can paternalistically give us all the things. And it's still not enough if you're not listening to me. And so this listening is super important, and I… as an optimist, I… Beth, I heard you as saying, like, AI will make us better listeners, but as a… I guess the worry in me is also that maybe we will think we… know. what people are saying, and actually become worse listeners. So, what do each of you think about that? Like, how… how do we guarantee that technology makes us a better listener instead of a worse listener?

Beth Simone Noveck: Well, let me correct one misimpression here. The technology will not do anything by itself. And it will not make us better listeners. The question is, and you hear this in what all of us are saying, is that it's how we use the technology. And I think we all agree that the tendency to go, AI will, you know, lead to worker replacement… no, no, no, AI's not firing anybody. Humans are firing people and using AI as an excuse. So I want to make sure we don't give undue agency or anthropomorphize these tools. There's a, you know, the misfortune that it's called artificially intelligent has left us with, unfortunately, some baggage.

Beth Simone Noveck: That creates the sense that this is human, and I want to get back to Allison's point about human relationships, and there is nothing human about these tools, which is why I talk about them as data processing tools. This is a better calculator and a better word processor, and I know that undersells and doesn't quite accurately describe what they can do, but I use that terminology deliberately, so that we are more at least intentional about saying, what do we want to do with these things? So let's come back to the sperm whales for a moment. It's a problem we… it's such a big data-crunching problem. The search for orphan drugs, the ability to just crunch through, and we've seen these medical applications that are so exciting, because it's just things humans couldn't do. It's just crunching a boatload of data to look and see, oh, is this molecule appropriate for this disease?

Beth Simone Noveck: And those are the really helpful things. And that comes back to the listening topic. Again, AI won't do anything by itself, but one of the things we have to recognize is that the web And I am very much guilty of this. I'm old enough to remember when the commercial World Wide Web started, and a lot of us, myself included, went out and talked about the Halcyon days of free speech that were going to be upon us, and how we would all go out and start talking. And it is true, everybody has a podcast, and everybody has a YouTube channel, and everybody's talking, but the big challenge with everybody talking that we, as Bush used to say, misunderestimated, is that it makes it really hard to listen when everybody's talking. So the thing I'm excited about, or optimistic about, maybe not hopeful, but, whatever the correct word is here.

Beth Simone Noveck: is that we could do better listening, if we will, is another question. So I'm excited about the fact that Bowling Green, Kentucky said, we're going to go out and ask our community, what do you want the future of our community to be? And then when 8,000 people reply, AI helps them to actually sort it and organize it. Or in California, they went out and created a project called Engaged California After the Wildfires, and past residents. how could we have done better with our wildfire response? And then used AI to be able to, again, organize that, turn it into a set of 19 policy recommendations, 5 of them who move forward, including things like certain kinds of permitting that they're speeding up, and undergrounding power lines, you know, creating a sort of stronger channel between citizen voice and actually political outcomes for people. But it would be just as easy, and we're seeing

Beth Simone Noveck: countless examples of people doing the opposite. Using AI, for example, to simulate humans. Why do I have to go out and talk to a customer if I could have a simulated customer? And there are lots of companies, if you drive around the Bay Area, you will see the ads on the sides of buses talking about, you know, how you can buy yourself, essentially, an AI focus group to test your cola or your toothpaste. And the danger is that both CEOs and, governors and. other managers and leaders will say, I don't actually need to talk to humans when I can go talk to AI that can simulate for me what I think people will say, and ignore that voice. So voice is a possibility, but it's not a probability.

Allison Pugh: Yeah, that's… Great, those are some really good examples. I love the Bowling Green example. I would say that, I'm gonna start my answer with a story. Which is, I wrote a book, The Last Human Job, it came out in 2024. Since then, people write me emails and letters, and one of them I got from a postal worker. And… She said, I'm so glad that you identified this thing that I do, which I called connective labor, this, you know. work of seeing the other and having them feel seen. And she said, I'm retired now, but in my… when I was working, you know, I retired this past January, and my customers, my postal service clients, came in and gave me a party, and We used… she told me, we used to, you know, on the long lines on the… at Christmas, we used to have people sing their favorite Christmas songs. And, she just described… Yes, a government service.

Allison Pugh: But it was a government… government service. like, epitomized by her, a person, and her… her connection to, her community. And she was… Such a good example to me of what… actual government service is, which, as you mentioned at the top of this webcast, Betsy, it's actually people interacting with people. So, yes, listening better will help the 8,000 respondents if somehow their idea makes it into the top 5, that whatever. But I'm actually talking about the interaction that happens at the front lines. And that's not replaceable. That is, there is something very powerful about having a human being on the other end. And… We mess with that at our peril. And I want us to keep that front and center. I am happy and fine with policymakers from Ohio to California grabbing, or we'll give the East Coast, too, from New York to California, you know, kind of

Allison Pugh: Deriving some kind of pattern from all the mail they're getting. But don't forget that the interaction between us is what makes our democracy, and we can't… we can't miss that. I want to add, just parenthetically, that while I am… I have all this optimism about AI, non-relational AI, and I would like us to have a name for that. I actually am pretty worried, because the direction of AI is following I would call it human vulnerability to feeling seen by a machine. And so, the technologists are turning towards that, and it's becoming the kind of number… it started as maybe a business-to-business ploy, we'll make you more productive, look, we can rewrite your paragraph! And now, it's, we can see you, we can… we can, you know, don't worry, we… we can give you this kind of frictionless sycophancy of…

Allison Pugh: You know, you are right, and people feeling validated. And that's really what they're selling, and they're actually continuing to deploy it, and in fact, I've heard their new products that are about to hit the, I don't know, hit the economy will be, you know, kind of home assistants that mix, you know, kind of this being seen by machine, and also a productivity, you know, aid. And that's, for me, terrifying, personally.

Betsey Stevenson: So… we've all… we've brought up a lot of different things. I wanna, I think focus… on… Something that touches on something both of you just said, which is to think about… What is our… the current health? of our… our trust, and our connections with other people, and our trust and connections with our institutions. And I'll… I'll tell you, I did… Back during the Great Recession. I wrote a paper that said, yes, trust in institutions is really low, but the economy really stinks right now. It's very normal for trust in institutions to decline when the economy declines. And when the economy rebounds, our trust should rebound. So that was, you know, 2009. It wasn't a bad guess. If I look back at the data, you know, which is what I was doing in this paper, 40 years of data, it was a good forecast.

Betsey Stevenson: Based on the past, but it's not what happened. We did not have any rebound in trust. And not only did it not recover in terms of trust in institutions, but the trust, interpersonal trust, relationships, all of that has gotten worse over, really, the last 20 years. And… you know, it's… AI is coming into that world. And… I guess I'll… I'm telling you what I think, and then I want to hear your guys' thoughts. I feel like that's the bigger problem, and sometimes we're missing that when we're focusing on what AI, you know, it can or can't do, because as Beth, you said. it's… human… humans choose what AI will do or not do. Humans will deploy it. Humans will decide whether to lay people off. Humans will decide whether to have relationships with machines rather than relationships with other humans.

Betsey Stevenson: But we're coming into this in a really dark place, frankly. And so, how are you thinking about that, and is there a way to have the technology? you know, help us recover from that? Are there things that we have to do to make sure that we're not dragged further down into an even darker place?

Beth Simone Noveck: I guess that was directed at me, so I'll start there, but I'm… I'm really looking for some hope here from Allison about the…

Allison Pugh: That's not usually my role.

Beth Simone Noveck: protecting what is human about work and about our relationships, and there's so much, there's so much in here. Betsy, I think, you know, number one, we've had this generation-long slide and the result of widening income inequality, declining life expectancy, rising and ever more complex challenges from climate change to the cost of healthcare. It is no wonder that people are despairing, and that despair is growing deeper. We have had institutions that have not been responsive enough at addressing these challenges. You know, we're… the challenges are getting harder, and our institutions are not getting more effective, so… you know, there is the piece which is… and this comes back to, sort of, to talk about the efficiency thing that we talked about before, that when we can do things like… and I love your Postal Service example, when we can do things like use AI

Beth Simone Noveck: in the form of optical character recognition to read your chicken scratch on the envelope, that frees up time for that postal worker to have that human relationship. And I love this story, because as my mom was dying, one of the most important relationships was the postal worker who helped with the mail, and who we had such a… who was… who was so helpful at managing, and man, it was just such an important personal relationship. So this story resonates with me. When I worked for the state of New Jersey leading AI, we made the decision that when we deployed chatbots, we were not going to deploy a chatbot at the public. We were giving chatbots to the people answering the phone. We were giving chatbots to the people at the front desk, so that person could look up an answer to a question.

Beth Simone Noveck: and then turn around and have a human conversation at the desk or on the phone with another human. So that's a very deliberate choice. Could we have said, let's eliminate the worker and, you know, give you a chatbot to answer your question instead? Of course we could have. But we deliberately made a decision not to do that, not only because of trust, but because we thought you're going to get a better answer from a human that has tacit and lived experience. So, all that to say, it is… you are right that the twin… the double-edged sword, the twin problem here of low trust in institutions, plus low trust in these technologies. that are, controlled by private actors who are accountable to no one. Where we're hopeful, and I put this in inverted quotes, we're hopeful that some of these companies may become public, because it might give us just a modicum

Beth Simone Noveck: of additional transparency over how they work is deeply dangerous. It's deeply dangerous, it's deeply concerning, and it's why we have to make very, very intentional choices about, again, how we're using these tools. You know, I often use the analogy to nuclear. You can use it to run your power plant, you can use it to build a bomb. Right now, we're building a bomb that's blowing up The nature of human relationships, in deeply destructive ways, and we have to be thinking again about the fact As Thoreau said, not to… how we don't become tools of our tools, how we instead take power over these things, and make very intentional decisions about where we want to use them. And that includes also decisions about where we don't want to use these tools. Again, you can use them for surveillance. Bad idea. You can use them to…

Beth Simone Noveck: you know, summarize what people are telling you, as they did in Mexico when they had a first-in-a-generation conversation about the future of their justice system. Face-to-face, at tables, actual neighbors talking to one another. AI was just… they basically just recorded the conversations and then used AI to help summarize what was said at the table, but it was, again, an adjunct to the ability to have a human interpersonal conversation. Anyway, so much in that. Sorry, I've gone on on too many fronts, but The short answer is, we have to be seeking to reverse this decline in trust, or we're in big trouble.

Allison Pugh: Yeah, totally agree. Loved that… your choice in New Jersey about giving chatbots to this people, who were doing that work. I thought that was really interesting. Regarding trust, Betsy, I would say… that… Like in many things, AI is not the cause of the problem, it's almost the symptom of the problem. We have had this declining trust for some time, and then AI comes and a little bit, I would say, you know, catalyzes further, a further slide down that hill. But, like, for instance, a lot of, I think, the decline in trust… I've read studies that Associated with rising inequality, and it's a kind of, you know. When we lost the sense of us all being in the same, boat.

Allison Pugh: And so instead, we have many boats, and my boat over here, I'm going to protect its future, but not yours. The loss of a sense of shared fate, I think, has a lot to do with underlying trust. Now, how do we get shared fate? You're… I mean, I don't want to be a broken record, but in my opinion, you get that by having these kind of everyday, mundane interactions across your across your everyday lives. So, and that's what's being automated. So what's happening is, countries, not just the U.S, kind of advanced industrialized countries, are saying, we have a loneliness crisis. And at the same time, they're, Basically, pursuing efficiency at every chance, in public and in private enterprise.

Allison Pugh: And so what you have is, like, you go to a restaurant now in California, say, and what's automated is the person who's supposed to be taking your order. That goes to a machine. What's not automated is the person making your order over there in the kitchen. So we don't have these kind of everyday interactions with people who are different from us in our community, with people who are kind of co-present. That, to me, is the kind of… building blocks of trust, and I think it's why we suffer. I come from a kind of depersonalization crisis, where we, kind of have lost the sense… psychologists call it mattering. Do you feel like you matter? And increasingly, portions of our society do not feel like they matter, and part of that is the loss of a shared fate.

Betsey Stevenson: I, you know, I want to end with circling back to something that, Beth, you mentioned at the beginning, and obviously as an economist, I think a lot about, which is, when we think about efficiency, and Allison, you just raised this issue, like, you know, we are pursuing efficiency at all costs, like, why do we have it? And of course. there are no increases in living standards without increases in efficiency. Like, those are synonyms, essentially. We increase our living standards by doing the same amount of stuff with fewer resources, and those resources can be capital or labor. The… the thing is, is what… where are we getting the efficiency from, and then what are we sacrificing? And I think that those are, like, the bigger questions that I'm hoping… You know, we can all start talking about, in terms of not just… Whose labor are we saving?

Betsey Stevenson: But what are we giving up when we save that labor? And Allison, like, you were mentioning, sometimes labor saving is coming at what, as an economist, I might call a quality you know, I am getting a less quality service because I'm not having that human interaction. But we do a pretty bad job of measuring that, and if people sort of accept this change… you know, we're sort of left in a… you know, in a place where it might not be what we all desire. But I think the bigger question comes back to this point of… of inequality, which is when we save labor, who's benefiting, right? And, I mean, we run into this with… now I'm going to bring it back to the institutional cultural. I find that Americans really struggle To accept things like, hey, we're richer as a country, so we should have… we should mandate vacation days.

Allison Pugh: If we made.

Betsey Stevenson: mandated vacation days, then, like, everybody would get a little bit more, and we'd be sort of spreading work and spreading time off. Or even, like, mandating maternity leave, or, you know, our paternity leave, like. or saying that, you know, we're… we… or even accepting the idea that we're gonna spend a larger share of our GDP on healthcare, and that's not a bad thing, that's due to the fact that all the other needs are largely met, right? And so, how do we start to… Have those conversations that help ensure that we use these efficiency gains to increase the living standards of Most people, instead of, like, having a very, very narrow slice, that are living a life that most people can't even conceive of.

Allison Pugh: Yeah, totally agree. I imagine we probably have to wrap up, so I will try and make it the best.

Betsey Stevenson: They're like, that's too big of a question for the end.

Allison Pugh: Well… I, I think the… you're kind of saying… can you tell… can you repeat the question? I'm sorry, this one may have to edit over time.

Betsey Stevenson: How do we start to have a national conversation that helps people see that the kinds of… Policies that, you know, give benefits to workers are really about actually Ensuring that labor saving is actually benefiting everyone, and not leaving some labor saved out of work, while others are getting higher profits from having eliminated other people from work. Like, there's a whole different way we could do it, where…

Allison Pugh: Yeah.

Betsey Stevenson: We save the labor, and that labor goes on vacation. Or, we can save the labor, and the excess profits go to… You know, some tech oligarch.

Allison Pugh: I guess I'm… I would say that the answer probably is institutions that we don't seem to have. The… the, there's… I think kind of what you're describing are… is a cyclical, what has been a cyclical experience of capitalism, either kind of full… full-bore, unfettered, just the liberty of, you know, kind of oligarchs, and something a little more tempered that also includes worker voice and, spreads the benefits more widely. And… I don't… it feels like we're sooo much out of whack. With, you know, the billionaires being created every 5 seconds, and all of, as we've mentioned in this, in this conversation, so much of the benefits of these, of this, race, this AI race, going just into the pockets of very few people.

Allison Pugh: it does feel like people are… that there's a backlash to that. It feels like the end of that, or that cycle is gonna… is gonna move in a more… we're gonna have a more distributive moment. Maybe that's the optimist in me, and maybe, this is not my wheelhouse, so perhaps Beth will now correct me about what's coming. I would say that when you look at other places, which not coincidentally have more trust, have more institutions, like Norway, for example, Norway just banned AI, essentially, for elementary school age kids, for the use of it in education. And I think that is fantastic. I think that is so wise, and requires… You know, a leadership that can kind of see… what AI is good for, and what AI is not good for. And one of the things it gets in the way of is a relationship between teacher and student, and early education, you know, the acquisition of crucial skills. I would say

Allison Pugh: you know, you hear about cognitive surrender, you know, AI is leading to cognitive surrender. I would say AI is leading to connective surrender, and that's what we need to be really afraid of. And the thing that will forestall that, I can only hope will be this backlash, perhaps leading to institutions, perhaps stemming from some real social forces coming from the bottom, saying, you know, we don't want to live in an oligarchy, or we don't want to live in a situation in which these benefits accrue only to the very top. Let's distribute them more widely.

Betsey Stevenson: Beth, why don't you give us… take the last word?

Beth Simone Noveck: Ugh, too much pressure here. So very quickly at the end here, I think, and I love this term, I just want to repeat what you said about cognitive and connective surrender that we're at risk of, and it's why you see, students booing at graduations when AI gets mentioned, and why you have this rise of a new generation of the neo-Luddite kids who Switch to flip phones, because there is a craving to at least explore if we can't rescue what is most human in our relationships. I think there are two practical things we need to do. In terms of policy, in terms of our actions to enable that future. And it's perhaps a bit counterintuitive. One is, maybe not at the elementary school level, but later, at least as adults, we need to learn what these tools are, what they do. what they're good for and what they're not good for. You can't have a seat at the table and be part of the conversation

Beth Simone Noveck: If you don't know what you're talking about. And whether that's policymakers on Capitol Hill, or that's workers in the workplace, I think basic free training to understand what these tools are, is… then leads to the second recommendation, which is giving people a seat at the table. It's including workers in the conversation about how you want to use these tools in the workplace, so that they are… we love efficiency and labor saving, right? You want to eliminate the drudge work. We want to get rid of the rote and the routine that… to free up time for the interpersonal and the connective. But that conversation around how we want to use these tools is the second recommendation, and it needs to happen in our schools, in our workplaces, in our own families, the conversation about how are we using these in… with homework? How are we using these, you know, in…

Beth Simone Noveck: deciding what we have for dinner, or in doing our work. So I think it's two things. We do have to invest in learning and training and making that free and accessible for all people. And the Scandinavian countries have been far out ahead in saying, Finland, for example, saying, we're going to train everybody in AI. They did that years ago. And other countries saying, we're going to make that investment, but then comes the second part, which is investing in the processes, the mechanics, the machinery, and the time it takes for us to have the conversation about how we want to use these tools.

Beth Simone Noveck: which tools, for what purposes, and what we don't want to do with them. So that would be my two recommendations, and they're not just global policy things that have to happen on Capitol Hill, they're things that I think we can do in our own homes as we have this conversation with our families about what these tools are and how we do and don't want to use them.

Betsey Stevenson: Great. Well, I think that's actually, a perfect note to end on. I think we can…

Allison Pugh: I want to ask one more thing for everybody. Can we do that? One more thing for everybody? I loved your question that you sent us on… 10 years from now, what consequential change in work are today's headlines missing? Like, I… I thought of a headline. Like, we should have… I think each of us should have a head… should invent a headline. That… that will happen in 10 years, a prediction. And also, can I say, you were so brave, Betsy, to bring up your… your prediction from 2009, because… That is… That's bravery, to stand…

Beth Simone Noveck: You made, at least you made a prediction.

Allison Pugh: Exactly.

Betsey Stevenson: I think…

Allison Pugh: We should each come up with a headline.

Beth Simone Noveck: Okay.

Betsey Stevenson: Okay, well…

Beth Simone Noveck: to go first, and then Betsy, and my… Yeah. So, to give… to buy myself 3 seconds to think about it.

Allison Pugh: Yes, I'm sorry, I did think about it earlier. And I don't actually know whether this is true. This is my most optimistic headline, and it was, Rates of men doing connective labor achieve gender parity at last. And the reason… there's a backstory to this. The reason is, is because I do think that, as AI does more and more thinking work. The feeling work will be not only what it means to be Female, but it will be what it means to be human. So I think, men have to get on the train, because Connective labor will be what humans are valuable for in the future.

Betsey Stevenson: I totally agree. Beth, do you have one?

Beth Simone Noveck: All right, so I will, in the interest of time, I will wrap up and say that, the headline… the headline we ought to be having is not about AI replacing workers, but workers shaping how we use AI. That's my hopeful headline. Again. it's not a… it's not a probability, it's a possibility if we embrace it, and so that's why I think we need to have something that we're aiming for. We need to have that mental model, that picture of where we want to go. And the place we want to go to is a world in which we are using these tools to give the public, workers, all of us more voice in the decisions about how we realize these benefits and what we do with those efficiency gains. All right, Betsy, no escape for the moderator. You have to answer your own question.

Betsey Stevenson: Well, you know, I… my hope… Is that 10 years from now, we'll be talking about, how few people took vacation. Back, you know, in the past, and how important vacation and time with family and connected time within your communities with no financial compensation, but how important that is for a life well lived. And so that's my… why I stay a tech optimist, is I hope it gives us all time to connect with the people that, you know, we value in our communities.

Allison Pugh: Didn't let me in?

Betsey Stevenson: end by saying, I value both of you, and I am so glad I had this opportunity to have this conversation with you.

Beth Simone Noveck: Likewise.

Allison Pugh: Thanks so much, Betsy, and.

Beth Simone Noveck: Thanks for doing this. Thank you.

Betsey Stevenson: Great, thank you. Now… Samantha.