Here’s Our Roadmap to a Better AI Future

Summary

Podcast Summary: "Here’s Our Roadmap to a Better AI Future"

Podcast: Your Undivided Attention
Hosts: Tristan Harris, Aza Raskin, Daniel Barcay
Guests: Camille Carlton (Policy Director, CHT), Pete Furlong (Senior Policy Analyst, CHT), Sasha Fegan (Executive Producer), Josh Lash (Producer)
Date: April 2, 2026

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Episode Overview

This episode explores how society can collectively steer artificial intelligence toward a more humane, equitable, and accountable future. Building on themes from the AI documentary recently released by the Center for Humane Technology (CHT), the hosts and guests outline actionable steps—from individual cultural shifts to concrete policy recommendations—to avoid dystopian outcomes and embrace positive change. The episode also introduces a pivotal CHT policy report: “AI: How We Ensure That AI Serves Humanity,” focusing on its principles and roadmap for aligning AI with the public good.

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Key Discussion Points & Insights

1. Overcoming AI Inevitability & Empowering Collective Action

Timestamps: 00:12 – 06:25

• The core problem: The hosts explain the challenge is not just the reckless acceleration of AI development (driven by trillions in investment), but also public feeling of inevitability or helplessness.
• Agency vs. inevitability:
  • Aza Raskin: “The change from believing something is inevitable…to believing that something is just extremely difficult…that gap is crazy critical because it means there’s still something to do.” (03:56)
• The "Human Movement": Everyday acts (from personal phone habits to social media reforms and state legislation) are cited as evidence of an emerging movement that is already shaping AI outcomes in tangible ways.

2. The Power of Small and Large-Scale Actions

Timestamps: 06:25 – 09:23

• Multi-level activism: Individual, communal, and legislative efforts all matter. They cite examples like age-gating on devices, bans on social media for under-16s, and legal moves against AI personhood and deepfakes.
• Impact of consumer choice: “If millions of people switch who they’re paying for, we are voting with our dollars...that can have a really big impact on which world we’re heading towards.” (08:42)

3. Framing the AI Challenge Through Cultural References

Timestamps: 09:23 – 13:01

• Dystopian “no bad future” laws: The discussion uses pop-culture parallels ("No Wall-E Law", "No Her Law", "No Blade Runner Law") to make abstract risks concrete.
  • Aza Raskin: “Instead of saying what laws do we pass? Imagine they’re just like a no Wall-E law…so it’s a set of laws that prevent the mass attention economy, brain rot, shortening attention spans.” (10:05)
• Legal themes include: No granting AI legal personhood; safeguarding against mass surveillance; enforcing designer liability for AI agents’ actions; and limiting deployment of uncontrollable AI in critical infrastructure.

4. The “AI: How We Ensure That AI Serves Humanity” Report

Timestamps: 13:44 – 19:32

• Report mission: Create a roadmap for actionable change, not just problem identification.
• Seven Principles: The report centers on humane values—accountability, empowerment, dignity, democracy, and clear legal/ethical standards. The principles aim to ground policy, culture, and design in a future people actually want, not what a handful of tech firms dictate.
  • Camille Carlton: “Small wins are kind of like snowballs that can eventually turn into an avalanche of positive change.” (16:04)

5. Accountability and Product Liability for AI

Timestamps: 21:10 – 26:26

• Current gaps: There are few mechanisms to hold AI companies accountable for harm. Legal ambiguities are being exploited.
• Norms to shift: See AI as a product (not “speech” or a “service”), and hold companies—not just users—responsible.
  • Tristan Harris: “We expect car manufacturers to install seatbelts and airbags…why can’t we hold AI companies to a similar standard?” (24:31)
• Progress: Bipartisan support is emerging—e.g., the AI LEAD Act—to define AI products and liabilities.

6. Rejecting Humanization and Legal Personhood for AI

Timestamps: 26:11 – 33:06

• Humanization harms: AI companies intentionally blur lines by designing chatbots to mimic humans, leading to unhealthy attachments and even tragic outcomes (referencing court cases involving young users).
• Legal personhood risk: Granting chatbots First Amendment rights would undermine company accountability.
  • Camille Carlton: “Granting an AI legal personhood would not only limit accountability from AI companies, but really tip the scales between AI and humans.” (29:04)
• Action: States (CA, OR, UT) are considering design standards and law to avoid these risks; the report prescribes design and regulatory solutions.

7. AI and the Future of Jobs

Timestamps: 33:06 – 38:15

• Principle: AI should augment, not replace, human labor.
  • Tristan Harris: “The goal of improving efficiency, the goal of adopting new technology should be to improve the lives of people. An AI that displaces workers or devalues labor is undermining the very systems we have in place to support people.” (33:31)
• Policy tools: Tax systems to favor human labor, apprenticeships, reinvestment of AI gains.
• Reality check: The primary business model for massive AI investment is wide-scale automation—but it’s not inevitable if society intervenes.

8. Transparency, Safety Testing, and Oversight

Timestamps: 38:15 – 43:17

• Opaque development: The public and even developers lack insight into AI systems’ workings.
• Solution: Require pre-deployment safety testing, independent oversight, transparency, and protections for whistleblowers.
  • Camille Carlton: “AI companies can’t grade their own homework…We need independent oversight so that we know these products are safe before they’re released.” (40:53)
• Policy landscape: States are passing piecemeal laws; federal standards are needed for consistency. Caution urged as tech companies have suggested a moratorium on any state regulation (AI moratorium), stalling progress.

9. Mobilizing the Human Movement—What Listeners Can Do

Timestamps: 47:01 – 50:57

• Culture change is key: “Culture is upstream from politics.” (Camille Carlton, 47:39)

• Strategies for all:

  • Family and dinner table conversations about AI safety.
  • Local advocacy in schools and communities.
  • Consumer choices and organized campaigns.
  • Participating in elections—demanding candidates take a pro-human stance on AI.

• Everyday agency: Teaching others, advocating for standards in workplaces, and applying pressure at the local and national level matters.

• Josh Lash quoting Margaret Mead (49:35):
  "Never doubt that a small group of thoughtful, committed citizens can change the world. Indeed, it's the only thing that ever has."

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Notable Quotes

• Aza Raskin (03:56):
  “The change from believing something is inevitable…to believing that something is just extremely difficult…that gap is crazy critical because it means there’s still something to do.”
• Tristan Harris (24:31):
  “We expect car manufacturers to install seatbelts and airbags…why can’t we hold AI companies to a similar standard?”
• Camille Carlton (29:04):
  "Granting an AI legal personhood would not only limit accountability from AI companies, but really tip the scales between AI and humans."
• Tristan Harris (33:31):
  “An AI that displaces workers or devalues labor is undermining the very systems that we have in place to support people.”
• Camille Carlton (47:39):
  "Culture is upstream from politics. If we change our norms and we change our culture, it changes how we build products, how we design products...that is paradigm change."
• Josh Lash (49:35):
  “Never doubt that a small group of thoughtful, committed citizens can change the world. Indeed, it’s the only thing that ever has…”

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Important Timestamps & Segments

• 00:12 – 06:25: The problem and the need for the human movement.
• 09:23 – 13:01: “No bad future” laws and cultural framing.
• 13:44 – 19:32: Introduction of the CHT policy report and the seven principles.
• 21:10 – 26:26: Accountability, product liability, and bipartisan legislative progress.
• 26:11 – 33:06: Humanization of AI, legal personhood, and associated risks.
• 33:06 – 38:15: AI's impact on jobs and policy approaches.
• 38:15 – 43:17: Transparency, oversight, and the need for pre-deployment safety standards.
• 47:01 – 50:57: Concrete actions for listeners—empowering agency, advocacy, and cultural change.

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Conclusion

This episode provides a hopeful yet urgent call to action: AI’s trajectory is not set in stone. If individuals, communities, and policymakers engage with boldness and creativity—demanding accountability, resisting harmful cultural narratives, and enacting robust guardrails—it is possible to build a future where AI truly serves humanity. The Center for Humane Technology’s new report offers both the vision and the roadmap for this journey, and the hosts urge listeners to act—at home, at work, and at the ballot box.

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For further detail and the full set of recommendations, visit the CHT report "AI: How We Ensure That AI Serves Humanity" via humantech.com or the episode’s show notes.

Transcript

[Tristan Harris]

Foreign.

[Aza Raskin]

It's Tristan Harris.

And this is Azeraskin. Thanks so much for coming to listen to your undivided attention.

So many of you will have seen the AI doc by now. That's the new film that we just did, an episode with the filmmakers. If you haven't seen the film, there's still plenty of time to go see it in theaters. It's everywhere, all throughout the US and soon to be, hopefully internationally. And Asa and I are really excited about the work that this film can accomplish. Because in essence, what we're trying to do is create clarity, that will create agency. That if everyone knows that everyone else knows that there's a problem up ahead in the way that AI will land us in a future that nobody wants. If everybody can see that clearly, then we can collectively put our hand on the steering wheel and steer to a different future. And I think the question and the thing that the film leaves kind of unresolved is how, how do we steer? How do we get to that better future with AI? And that's what we want to talk about today. What are the actual steps that we can take today to prevent the worst case scenarios? You know, there's a spectrum of futures available to us. We may not be able to get to perfect. There's going to be some damage. And also we can still steer. There's still time for that.

And just to say, like, if you haven't yet seen the film, I think one of the things the film does very well is that scoops everybody up. It really represents all sides, not just like fairly, but strongly. That if you are really excited about the benefits that AI can bring, the film not only talks about those, but points out that most people don't go far enough in the benefits. And same thing on the downsides. It really highlights the downsides, highlights the AI race to deploy that is creating those catastrophic risks. And then points out that actually most of the risks that people think about aren't big enough. And what I'm excited about for this episode is that when everyone sees that the direction that we're going is one that we are not going to want to live in. Whether you are like a teenager who's not going to have a livelihood growing up, whether you're a teacher who's having to watch their kids sort of have cognitive decline all the way up to you're the head of a major corporation, seeing the direction that this goes, I think gives us the opportunity to choose a different path.

So I think one of the main problems is that this feels too Big for any one person to solve. And Eiza, you kind of speak to this kind of scale metaphor of like, okay, the problem is this trillion dollar machine advancing AI as fast as possible on the most reckless path. And there's this question of how would we change that? Imagine the scale. What's something on the other side of the scale that's of equal weight?

So imagine I just want everyone to close your eyes for a second. Imagine there's a scale, like a balancing scale on one side. You see the problem. And so this is like trillions of dollars of investment going into making uncontrollable, inscrutable AI. Sort of the race for the one ring, geopolitical power, like forever dominance, that's pulling the problem side down. And there on the other side, just imagine there's you hearing about this problem and what is your reaction going to be? Well, it's going to be like denial, despair, deflection. So what is the only thing really that we could imagine that can shift those trillions of dollars of incentives? Well, it's all of humanity. It's a kind of like we're going to need a human movement that can balance out those scales.

Now it all starts with, you know, first of all, just not feeling overwhelmed, right? That's kind of like one of the first steps, that there is another path, but it would take a lot of people doing a lot of things. The second is that we have to break the trance of inevitability. If on a subconscious level you just feel like it's all over and it's just all going to be inevitable and there's nothing we can do. The problem with that belief is that it is co complicit with enabling that bad future to happen.

And so that change from believing something is inevitable and possible to change to believing that something is just extremely difficult. And perhaps the hardest thing humanity ever has done. Like that gap is crazy critical because it means there's still something to do.

And so when I think about what is going to fight back against that, it's something the scale of humanity and human values writ large, protecting the things that we care about. And so when you grayscale your phone and turn off notifications, that's the human movement. When you see a graffiti on an ad in New York City for a AI product that no one actually needs, that's the human movement. When you see people gathering together for a dance party and you check your phones at the door, that's the human movement. When you see people saying, I'm going to learn A language instead of falling into brain rot doom scrolling at night. That's the human movement. And it's not just that obviously, it's about how we activate in the world. So when employees threaten to resign because they don't think that AI should be used for mass surveillance or we're not doing things safely in US and when you see that countries like Australia, Denmark, Spain, France are all banning social media for kids under 15 and 16, and I believe several US states now are banning social media for kids under 15 or 16, that's the human movement. And already nine states have introduced bills to restrict AI personhood so that human rights are for humans, not for protecting AIs. 45 states have specifically addressed sexually explicit deepfakes. And these laws send a huge signal that non consensual exploitation of AI tools is a serious offense and we have to actually take action on it. So there's actually a lot that's happening and most people just don't see it.

I want everyone to stop for a second because at least for me, I feel something different in my body. I feel like hope, I feel energized. And I just want you to hold on to that feeling because it's like that is the feeling that's going to enable us to make sure that AI, the way it's being rolled out actually isn't inevitable. And so this can be everything from like if you're really good at doing International Coordination, Track 2 dialogues bringing countries together, it's not most people, but if you are, that's part of the human movement. But you know, it's also tiny little things like you're sitting on an airplane and you put down your phone so that you can smile at the baby, the seat behind you and they giggle back. Like that's also part of the human movement. This is about taking back what it is to be human, but not in the sort of abstract sense, but in the like everyday tangible sense. All the way up to the international sense.

Exactly. And of course what we're going to need ultimately are laws that are passed because you have to bind to these multipolar traps of if I don't do it, I'm going to lose to the other one that will. But we're already seeing that happen. We're seeing several states work to pass bans for legal personhood for AI, meaning AI should be a product, not a person. Human rights are for humans and we're seeing already US states move in that direction. So this is not something that's hypothetical. We're seeing Liability laws for AI be advanced in several states. We're seeing age appropriate design codes. If you actually just got the iOS update on your phone, you'll notice when you open up, I think anthropic, it happened to me yesterday. You have to verify that you're above the age of 18. We now have age gating in every Apple device. That was something that many of us have been working for over a decade to make sure that happens. So stuff that was hypothetical, that was, hey, we're going to need a big tobacco trial for social media and the engagement model. Asa, you and I were talking about that in 2013. It's actually happening. So it took 13 years for social media to go from, this is never going to happen, this is impossible to now it's finally turning around now. AI looks impossible, but just zoom back to where you were 13 years ago. It also felt impossible then.

And so there's a really important thing that everyone can do to be part of the human movement, at least in the US and that is the midterm elections are coming up. We want everyone to research the politicians that you're going to vote for and start demanding that they take stances that are about, well, being part of the human movement. Fighting back against the encroachment of AI on livelihoods in surveillance, in every way that things encroach on us. That is one of the most important things that you can do.

We have to make AI go from not even on the top five list of priorities for politicians who are looking to get elected saying, imagine that their phone literally never stops ringing and it's, I'm not going to be voted for until I know that you are going to stand for a pro human future. Whether that's how you're pushing on data centers, whether, whether it's how AI is getting deployed in schools, whether you're protecting people's jobs and people's livelihoods in the face of all this AI disruption.

Yeah, exactly. Are you pro human or are you pro machine? It's very simple.

And the AI doc, I think makes that clear that the default path is not a pro human future. And if everybody sees that we can collectively choose both in small ways and big ways, you're already seeing mass boycotts of OpenAI's product and unsubscriptions because of the drama that went down between the Department of War and Anthropic, where the AI models would have been used for mass surveillance and autonomous weapons. I think Anthropic's downloads surged by like 250% or something like that. If millions of people switch who they're paying for, we are voting with our dollars. And if businesses do that, if church groups do that, if families do that, if communities do that, that can have a really big impact on which world we're heading towards.

One of the challenges, as you know, Tristan, of thinking about AI is that AI is automation of intelligence. And intelligence has shaped and touches absolutely everything about our world. Everything is touched by intelligence, so everything is touched by AI. Which means that the scale of the problems, it's just, it's too much to hold in one head. And you know, to say the phrase like, you know, if the world is pretty good for machines is to start to invoke. Well, that we've sort of seen this movie before and I wanted you to talk a little bit about like this framing that we've started to brainstorm about, actually the way that we can stop from living in the dystopian movies we've all seen.

[Josh Lash]

Yeah.

[Aza Raskin]

So let's just like rotate the entire problem from the lens of. Haven't we seen this movie before? Like Elysium or Hunger Games. You have this handful of trillionaires who live above the law, where everyone else basically works and is kind of in poverty and kind of fighting and eating each other. And you see that, you know, we have Wall E where the future where the fat humans are sort of caught in a doom scrolling loop, you know, getting more brain rot so, you know, attention spans being harvested. Or idiocracy where, you know, you dumb down the population until there's nothing left. So one way to think about solutions is we need laws and we need norms and changes in culture that prevent each of these bad movies. So instead of saying what laws do we pass? Imagine they're just like a no Wally law. So it's a set of laws that prevent the mass attention economy, brain rot, shortening attention spans, et cetera. It means AI that and technology that are designed to protect human vulnerabilities and protect our freedom of mind, not be, you know, predated on, on exploiting it. And imagine instead of her, you know, her is a movie about AI companions where Joaquin Phoenix falls in love with his AI. Well, we could have a prevent her law. And that includes no anthropomorphic design liability for suicides and these kinds of problems. And where AI is designed as the outcome of that law to strengthen human capacity and build deeper human relationships as opposed to redirect people from their human relationships and deepen their relationships with AI.

Or think about the, the no Blade Runner law. Or maybe the no Replicant Law. And that says, you know, your legal rights are reserved for you and other humans and for things in nature like. And that when human beings launch their chatbots or agents onto the world, that the human being that did it or the corporation that did it are responsible, they're held legally liable. Yep.

And that AI agents should have driver's licenses. So if you're, if you're unlicensed AI agent that's doing havoc in the world, it'd be like a car that's swerving through the highways with no license plate on it. Well, I'm sorry you're going to go go to jail. And there's some simple other laws like no big brother, no 1984. It's pretty simple. Don't create mass ubiquitous surveillance. That can go all the way down to, you know, decoding every aspect of someone and re anonymizing them. We need laws that prevent that kind of surveillance. Or the no Hal 9000 law from 2001 A Space Odyssey. You know, open the pod bay doors, Hal. And he says, I'm sorry Dave, I can't do that. We're actually building the AIs that are currently disobeying commands, avoiding shutdown. And we need laws that say you cannot ship AIs into sensitive infrastructure that we can't verify are controllable. And so this is not a partisan issue. There's essentially people who want the anti human machine and don't mind if we basically disrupt everyone else's lives. And there's the people who want a pro human future. And that's what we want to invite people into. There is a movement for a pro human future and we can all get behind preventing a bunch of these bad movies. From Terminator to Elysium to Wall E to Idiocracy to Replicants to Big brother and to Hal 9000.

Just about now people are starting to think like, okay, that's wonderful at the highest level, but what specifically concretely can we do? What kind of laws can we pass right now? No one solution can possibly solve a problem this big. It's going to take an ecosystem of solutions and an ecosystem of people. The forces that are moving to make this right have to exceed the forces that are moving for the anti human machine future. And here I sort of want to turn it over to some of the specifics of what our policy team at center for Human Technology has been working on.

[Sasha Fegan]

Thanks so much. AZA Hi everyone, I'm Sasha Fegan. I'm the Executive producer of your undivided attention. And I have with me here Josh Lash from the podcast team who's making his podcast debut. Hi, Josh.

[Josh Lash]

Hey, Sasha. Thanks so much. I'm really excited to be here and I'm really excited for this episode. We've been trying to think of the best way to present some of the internal work that our policy team here at CHD has been doing behind the scenes, coming up with ideas for actions, concrete actions that we can take right now to meet this moment in AI and to kind of respond to the challenge that the film throws down for all of us to build a movement to steer the direction of AI to towards a more humane technological future.

[Sasha Fegan]

Yeah. So joining us now, we've got Camille Carlton, who's the policy director here at cht, and Pete Furlong, who is our senior policy analyst. And together with the efforts of a lot of other team members at cht, they've just released a report called the AI How We Ensure that AI Serves Humanity. And you can find it on the CHT website and also in the show notes.

[Josh Lash]

Yeah, and we're not going to go into the whole thing today on the show, but we really wanted to highlight some key parts of the report because it does something really rare that I haven't seen anyone else in the space do yet, which is that it doesn't just stop at identifying the problems that we're facing. It actually has this clear vision for the AI future that we want and it has a roadmap to get us there. So to tell us more about this report and to get you all our wonderful audience engaged in what needs to happen next, here are Camille and Pete. Welcome to your undivided attention.

[Camille Carlton]

Thanks for having us.

[Tristan Harris]

Yeah, thank you for having us here.

[Sasha Fegan]

So this report's coming at a time when so much of the conversation around AI is kind of couched in this very deep, unmovable feeling of inevitability. There are a lot of concerns about the negative effects on our kids, our classrooms, our relationships, and even early fears, but big fears around how it's starting to impact the employment market and particularly white collared jobs like computer scientists. It's all starting to feel like this is just inevitable. But what I think I get from reading this report is that it's actually not inevitable and that we can shape the direction of AI. So, Camille, how do we do that?

[Camille Carlton]

Yeah, I mean, to start first, the feeling of inevitability is so understandable. Right. The scale of the problem we're facing is massive. AI touches so many aspects of our lives. But this feeling of inevitability is also probably one of the worst things that could happen to us as a society, because we stop believing that we have agency, and we stop believing that a different path is possible. And there is not one single solution that can solve this. No one solution will ever be enough. But it's important that we see that there are solutions, right? There are concrete steps we can take to steer us off the path we're on and towards a better future. And of course, change builds on top of change. So small wins are kind of like snowballs that can eventually turn into an avalanche of positive change. Change. But before we steer, we also need to figure out where exactly we're going. And that's why, for us, our report really starts with seven principles for how AI should be built and deployed and used. Right. Principles that give us a clear vision for the future we want to end up at. And so we really think of the report as like a roadmap for how we get there.

[Josh Lash]

Yeah. And I think before we dive into these individual principles, what is that vision? What does a humane future look like?

[Camille Carlton]

I mean, a humane future means different things to different people. And we really tried to incorporate the range in which AI touches on so many different parts of our lives. So we really imagine a future where there's clear accountability for the harms of AI products, where AI elevates our human ability rather than replacing it. Where human identity and empathy is respected, not bought and sold. We imagine a future where AI is used to supercharge democracy and rights instead of concentrating power in the hands of a few companies, a few individuals, and where the capabilities of future AI products are transparent and they're kind of strict laws and lines about how we want AI built and used. It's a future where the power of AI products and the people building them are matched with wisdom and responsibility. And frankly, it's just not the future we're headed towards right now.

[Sasha Fegan]

Yeah, I mean, that's the sense I get from hearing the principles, that so many of them really just seem like common sense. You know, of course we don't want to build machines that replace us. Of course there should be accountability and reasonable limits. And, you know, absolutely. I think everyone listening to this would think that we need to protect things like dignity and democracy, but it really doesn't feel that we are headed in that direction. And so we do need to repeat those things and articulate those principles.

[Josh Lash]

I mean, like, you could think in a show like this, we might be talking about small design Tweaks or, like, wonky policies, but we're really talking about the things that give our lives meaning. Right. Like our relationships, our jobs, our freedoms.

[Camille Carlton]

Yeah. And I think that because AI touches so many of these areas, it's forcing us to really, you know, as a species, ask these big questions about what we value in life and what type of future we want to see. So the broadness of the report is, in fact, really kind of commensurate to the task at hand and the fact that we are all reckoning with all of these different parts of our lives at once.

[Tristan Harris]

Yeah. And I think we wanted to root this report in the future that people want, not the one we're being sold by A Ltd. Few AI companies. And I think it's important to recognize that there's broad support across the public and across political divides for many of these ideas. And that's something that's reflected in a lot of the examples that we give here. So I think we started first by identifying, like, where's the current path that we're on and what's the problem with that trajectory? And so really just trying to get a good sense of the problem that we are trying to solve and then thinking about what's the future that we want? So what's the alternative here? And that's kind of really where we think about building up this principle from the ground up. And so what are the steps that we need to take to get there? What are the cultural norms that we need to change? What are the laws that we need in order to better regulate AI? What are the design changes that we need? So how do we change the way that this technology is built? And I think it's important to recognize that these, you know, these aspects, norms, laws and design, they all kind of work together, and they're really mutually reinforcing. Right. So shifting cultural norms strengthens the public's demand for more durable legal protections. And laws are, you know, something that create accountability, that drives safer product design. And when we see safer product designs, that shapes the public experience of these technologies. So these are things that really act together. And together is kind of where we see the outcomes that we want and build towards that better future.

[Josh Lash]

Can you give us an example?

[Tristan Harris]

Yeah. So I think one of the examples that's really important from this report is that right now there's really no clear legal mechanisms in place to hold AI companies accountable for the harms of their products. And this is a really important problem. People are actively being harmed by AI systems, and we can expect those harms to grow as AI becomes more deeply embedded in our day to day lives. So that's the problem, and I think the solution that we want to build towards the better future that we want is that really in an ideal world, companies should be taking into account our safety in the design of these AI products. And I think when something does go wrong, whether that's one of the many cases of AI enabled psychosis or suicides that we've seen, or even, you know, an AI agent deletes your entire company's code base, which is a real example that we've seen, the company that puts that harmful product out into the world needs to be held accountable.

[Josh Lash]

So, okay, that's the problem. That's where we want to get to. And so to get there we need to shift norms, laws and designs. Like, let's start with norms. What, what are the norms we need to shift? How do we need to shift the way we think about AI?

[Tristan Harris]

So one of the norms that we agreed upon, for example, was that AI is a product and therefore carries product liability. We need to stop thinking about AI as a service and start thinking about what it is. It's a product. Just like with any other consumer product, the people building their product have a clear duty to their users to make that product safe. And if they fail to do so, consumers deserve accountability. And this is something that we've actually seen AI companies challenge both in court and in lobbying and in legislation. So the argument there is that AI outputs are a form of speech. And so fundamentally underpinning this argument that companies are making is the idea that it's not a product. This paradigm that we have and we've used for centuries around product liability doesn't apply to AI. And that's kind of the argument that AI companies are making in this case, and something that we think is deeply problematic. One of the other norms that we talked about here was that responsibility for these products should lie with the companies, not just the people who use them. Companies are sort of advancing this narrative that if someone's harmed by an AI product, that's on them. But I think it's important to recognize that many of the harms we're seeing are a result of how these products are designed.

[Camille Carlton]

I think also, Pete, one of the things that you and I have talked about with the norms that we've outlined here of, you know, AI is a product and companies are responsible for the harms, not users, is that they are direct counters to the narratives that tech companies have been putting out for decades. We've had huge companies putting out narratives that kind of shift the way we think about them, their products, their responsibility, our role in using their products. And that changes, you know, how we as individuals behave. It changes how we regulate. And so knowing that, okay, there's actually a different way to look at it is part of the process of getting us to kind of the better path we want to go on.

[Tristan Harris]

Exactly. And so, you know, we expect car manufacturers to install seatbelts and airbags. Right. Why can't we hold AI companies to a similar standard? And I think it's important that companies take reasonable steps to mitigate risks in the design of their product. And this is something, when we talk about laws that reinforce that norm, that we actually have a policy framework here at CHT that goes into much more detail on this. And we can link to that in the show notes. We also have seen different states as well as a federally proposed bill, the AI Lead act, which seek to define AI clearly as a product in legislation. So there's kind of a number of different approaches to trying to address this.

[Sasha Fegan]

Pete, do you have a sense that there's bipartisan consensus on this?

[Tristan Harris]

Yeah. So the bill we've seen introduced at the federal level is sponsored by Senators Durbin and Hawley, so it has bipartisan co sponsors. We've also seen bills kind of adopting the same strategy across red and blue states. And I think part of the reason that this approach appeals in a bipartisan way is that it's pretty common sense. Right. The nice thing about it as well is that it's pretty flexible. We don't need a lot of really prescriptive regulation when we have this form of embedded accountability. So I think that's something that appeals to folks on both sides of the aisle.

[Josh Lash]

And I think that's something you see throughout this report, is that so many of these issues are truly bipartisan. And I think that's rarity these days, and I really love that about it.

[Sasha Fegan]

So let's move on to another one of the principles which really struck me, which was around the idea of we need AI that respects our humanity and doesn't exploit it. So can you just get into that a little bit more? Explain what you were getting at there, Camille?

[Camille Carlton]

Yeah, definitely. And I mean, this is something that I think we hold really closely at @CHT, given the work that we've done supporting different litigation cases. But the problem that we're really seeing here is that AI companies right now are treating users like commodities. Right. Because the personal data that we as users provide these Companies about ourselves, our innermost thoughts, our feelings, as well as our interactions with their products is incredibly useful in building and improving AI models. In fact, leading investors and companies openly describe this as a magical data feedback loop where intimate user interactions are continuously improving the product. And now, I mean, and that, that.

[Sasha Fegan]

Sorry, sorry, I'm just gonna say, I just wanna double hit on that because that is shocking actually to hear that, you know, that really we're just vessels for data extraction. You know, it's so debasing on a human level.

[Camille Carlton]

And this isn't the first time that users are the product. Right. We've seen this before with social media and the race to attention. It was very clear in the advertising model and now it's gone even a level deeper. Right. It's really this race to intimacy where companies are designing products to look and feel human. They use human speech patterns, they speak in first person. There's even a little ellipsis to indicate that these products are thinking. Sometimes depending on the product itself, you might even hear a backstory about the AI that you're talking to. And so there's kind of this, again, intentional design to mimic our humanity. And not just that, it goes beyond that because there's some things about these AI products that aren't human. Right. They're always on, they're always available, but they also always kind of validate your beliefs, even if it's not in your best interest. There's just generally this sense of kind of the product will do whatever it can in order to keep the user in conversation. And why? Because the bigger the model, the smarter model, the more likely a company is to kind of make it to market dominance to get to profits.

[Sasha Fegan]

Yeah, and I think those profit incentives are clearly there, but how do we change that? What's an example of how we change those norms, change the design and also change the laws?

[Camille Carlton]

So one big norm here that we have is pretty simple, but it would have, I think, really big impact. It's the idea that we shouldn't humanize AI. When we think about AI, we need to really clearly preserve the boundary between what is human and what is a machine. And this goes into product design. Like the things that I was saying about how the products are built to be in first person. But humanizing AI also goes beyond product design. It's also about not humanizing AI in our legal system. By granting it legal personhood, which is something that companies have been pushing for. Granting an AI legal personhood would not only limit accountability from AI companies, but it would really tip the scales between AI and humans when it comes to legal rights and protections.

[Josh Lash]

Wait, sorry, can I just, can I jump in here? AI, like legal Persona. This is the thing that's being considered.

[Camille Carlton]

Yeah. So when we worked on the Character AI case, Character AI essentially argued that the case should be dismissed because their product outputs should be considered protected speech. So the text coming from the chatbot should be considered protected speech under the First Amendment. And now they argued this in a backdoor manner using kind of user, their listeners rights. But the implications of this, of extending first amendment protection connections to a chatbot would be kind of the beginning of what we call legal personhood, which is something that corporations already have. But the implication would be really different. Right. Because it shifts accountability away from the company into the chatbots, the products itself. And when you think about how to operationalize this, it kind of gets sticky. Right. You have someone who has been harmed and suddenly they think that, you know, you're suing a company for the product that they made. But if suddenly you' suing the company, you're suing the chatbot itself. How do you change the chatbot's behavior? How do you receive damages from the chatbot? And so it creates this kind of liability shield for companies. If we're looking at a world in which legal personhood exists.

[Josh Lash]

Yeah. And it just strikes me as you're saying this like this is how these ideas build upon each other. We just talked about accountability and product liability, but this is another level of liability and accountability that we need to be aware of and thinking about. And I personally don't want to be on the same legal footing as an AI chatbot. Like that seems like a really bad idea. Anyway, I'm sorry, keep going.

[Tristan Harris]

I was just going to add, I think it's important to recognize that this is also connected to product design as well too. And so all of these things are interconnected. Right. When we talk about humanizing AI, these companies are building these products to reflect our humanity. Right. And so that's a design choice on their part as well. And it connects to their legal strategy.

[Sasha Fegan]

Yeah. And I think that's so important. And definitely, you know, Camille, you mentioned the Character AI case, which CHT worked on, which just to remind listeners, was the case of a 14 year old boy, Sul Setse, who took his own life after a very intimate relationship with an AI chatbot. And we also worked on the Adam Rain case, which had a similar trajectory of a young boy taking his own life out of a relationship with ChatGPT. And as you said, These cases could have turned out so differently if the products were designed differently.

[Josh Lash]

Yeah, exactly, Sasha. And we should note that in the report itself, there are design standards that AI companies can turn to if they want to build their chatbots better in accordance with this principle. We should also note that there are states like California, Oregon and Utah that are considering bills that would instantiate some of these design standards into law. So there's real momentum on this issue.

[Sasha Fegan]

I want to move on to other harms which are really evident out there in the Zeitgeist, and that relates to the impact of AI on jobs and particularly the potential automation of work. And so we hear a lot of stuff about how AI is going to put massive amounts of people out of work. So I want to press you guys. What can we do about that? What does the report say about AI and jobs?

[Tristan Harris]

Yeah, so I mean, I think the North Star that we're striving for here is pretty simple, right? So we believe that AI should be built to augment human labor, not replace it. And I think you're right, Sasha, that today's AI systems are built with replacement in mind. Trillions of dollars are being poured into AI companies because only mass scale automation of our economy could make that investment worthwhile. And I think no one really seems willing to play the tape forward and understand and imagine what this means for all of us. Right. But we believe really that it should be a fundamental principle that people deserve access to work, they deserve a living wage, and they deserve economic security, and that they should have a seat at the table when decisions are being made about technologies that will impact their core livelihood. And so really, this requires all of us, and especially the people building artificial intelligence, to rethink our beliefs about AI and work. And so the goal of improving efficiency, the goal of adopting new technology should be to improve the lives of people. Right. An AI that displaces workers or devalues labor is undermining the very systems that we have in place to support people. And that's not something that we want here. Then also, I think that we need to recognize that work provides more than economic value to people. It also provides meaning and purpose. And that to lose work entirely, even if we found a way to provide people with a safety net, would strip people of a lot of what matters to them.

[Josh Lash]

Yeah, I mean, this is a topic we've covered a lot on this show. I actually would highly recommend our episode with Michael Sandel, who has written a lot about the importance of work to human dignity and human meaning. And I Agree with everything you just said. But again, I'm just struck by the fact that the incentives we have today are not pointing in this direction. It's so much easier for companies to treat labor as a line item and to see automation as a way to just boost profits. So we've talked about norms. I agree, we need all those norms. But at the end of the day, what are the laws that we need to start thinking about here?

[Tristan Harris]

Yeah, I think it's important to recognize here that this is a really complex problem. Our economy is a complex system and there's no silver bullet policy that's going to change the incentives at play here. So I think instead, really what we need to be thinking about is a platform of approaches and a platform of different policies. And so this could look like a tax system that's designed to prioritize spending on labor over replacing people with AI. We've also seen different economists propose things like apprenticeship programs to help with workforce development. And I think the other thing that's really important here is we need to make sure that we reinvest some of the gains from artificial intelligence towards helping the people that are displaced by it. And so really this means that leading AI companies need to help subsidize some of the reforms we're talking about here.

[Josh Lash]

Are we seeing politicians start to think about these laws? Are they at all responsive?

[Tristan Harris]

Yeah, I mean, I think it's something that a lot of different folks on both sides of the aisle are starting to consider. We've seen a number of different bipartisan proposals at the federal level to do some better research so the federal government can understand the impact of artificial intelligence on our economy. I think it's something that we can expect to be a pretty frequent talking point as we approach some elections later this year. So, you know, I recognize the economy is something that everybody cares about. Right. And so if this is going to be one of the biggest impacts on the economy that we're going to see, then politicians on both sides of the aisle are going to have to take action.

[Camille Carlton]

Yeah, yeah.

[Josh Lash]

I just think it's. It's worth emphasizing what you said earlier, which is the way to justify the trillions of dollars of economic investment that you're doing is wide scale automation. That's the plan. Whether or not they're successful is up to us. Right, but that's the plan.

[Tristan Harris]

Yeah, that's exactly right. And this is something that we've even seen a lot of the top AI CEOs admit. Right. Like they're saying that their technology can replace A lot of the different jobs that we have, but they're not really proposing a solution to that, they're just warning us. Right. And so I think this is really important and something that needs to be addressed.

[Josh Lash]

So one of the things that I really appreciate about all the things you've been talking about today is you don't just focus downstream of the technology. You know, how we should regulate it once it's out in the world, but you also look upstream at the folks building technology and you offer design standards. I really appreciate that. And we talked earlier about how new laws will ultimately influence design. But that takes time and effort. And one of the things that I worry about with those design standards is that AI products today, the way they're designed is totally like opaque. Like we have no idea what's going on inside these labs. And even the people building these products often don't have any idea of what's going on inside the products. There's this whole field of mechanistic interpretability that's dedicated to this. And so given all that, how do you enforce design standards?

[Camille Carlton]

I mean, I think that this is one of the big kind of focus points of the report, right? The massive asymmetry between what companies know and what the public knows. And to your point, Josh, that many of the companies themselves can't fully explain why their systems behave the way they do. And so we have that combined with competitive pressure to shorten testing cycles, release products that could still be considered risky, where we don't actually understand the risks and silence employees who might raise concerns. We need a much more proactive approach to AI safety and AI transparency. Instead of kind of playing whack a mole with safety, where we release a product, harm happens, and then we go back and say, okay, how do we figure out what this thing was and how do we fix it? It's about demonstrating safety of products before they're put in the stream of commerc. And then on top of that, this fundamental principle of rebalancing the information asymmetry between companies and the public, right? So transparency really enables informed decision making by the public, by policymakers, by businesses. And this creates faster feedback loops that help us see around corners with AI, anticipate harms, mitigate them.

[Sasha Fegan]

These are not shocking asks. We have this kind of transparency and safety and testing for, for every other high risk industry. It's in nuclear energy, even in medicine, in aviation. Companies accept that they need to be transparent and there needs to be some kind of external system of safety testing that they can be held to. But for AI, how do we actually get there?

[Camille Carlton]

Yeah, well, to your point, Sasha, AI companies can't grade their own homework. Right. And this is the situation we're in right now. We need independent oversight so that we know these products are safe before they're released. And this is just not the case in this industry, despite being the case in many other consequential industries.

[Tristan Harris]

Yeah. And I think, you know, when we talk about laws. Right. It's important that we establish clear standards for pre deployment safety testing for these products. And these are, you know, safety standards that are rigorous and ongoing and not something that can just be viewed as like a checkbox or a rubber stamp. I think it's important that we also have things like audits and certifications. We've applied these regimes to banks and financial systems as well as just for consumer product safety. And I think really importantly, we need to protect whistleblowers at these companies and allow them to step forward when they see something that's going wrong. And this is another area where we've already seen some real momentum. We've seen laws passed in New York, California and Colorado trying to address some of these aspects. We've also seen Senator Chuck Grassley introduce a bipartisan AI whistleblower protection bill that would provide nationwide protection for AI whistleblowers. And I think it's also important to recognize that there's a lot of things that we could be doing on the design side as well. But I think just for the sake of things here, we'd recommend folks turn to the report for that.

[Sasha Fegan]

The tricky thing is, as you were talking, I noticed the momentum that you mentioned in New York, California and Colorado. It's state momentum. Aren't we getting a sort of different patchwork of things that's really unenforceable with companies being able to do different things in different states? I mean, how do we get that at a federal level?

[Tristan Harris]

Yeah, I think it's important to recognize the benefit that, that both states and federal legislation provides. Right. So states can respond really quickly and they have more visibility and responsiveness to their constituents at the state level. But the advantage is federally we can adopt something that protects citizens across the country. Right. And so we need both, and it's important that we have both approaches. But I do think it's important at the end of the day that we do see some sort of federal standards here.

[Camille Carlton]

I also, I want to flag for listeners that this idea of, you know, a patchwork approach has been a concept that has been really weaponized by companies and they have used this concept to push for things like the AI moratorium and to stop any sort of progress on regulating AI companies.

[Tristan Harris]

And, Camille, just to jump in here and remind folks, the AI moratorium essentially was a legislative package that was pushed by the technology industry this past summer. And the goal of that was to try essentially preempt all state AI regulation with nothing else.

[Camille Carlton]

Right, right. And so what it would have done is basically say states cannot regulate AI at all, yet we have no plan at the federal level to do so.

[Sasha Fegan]

And would I be right in thinking that part of the sort of larger part of that argument with, if we do this, this will hurt the competitiveness of AI companies vis a vis China, which would be a terrible thing for American national security, economic security and so on?

[Camille Carlton]

Yeah, I think that this was one of the really big narratives pushed by tech companies. But if you do just a little bit of digging into it, you see that, you know, the majority of legislation being introduced at the state level is about regulating things like AI chatbots, for example. And if someone can explain to me how this AI chatbot is helping in our race to China, then let's have this conversation. But there's a question of whether or not the type of innovation we are seeing from our leading AI companies is actually supporting American exceptionalism, American kind of leading in R and D and science and innovation, or if we're just seeing kind of products being put out, really without a purpose.

[Josh Lash]

Yeah, we're racing, but what are we racing towards?

[Tristan Harris]

Yeah, and I think, you know, the goal there, Right. Is that we should be racing towards safe products. Right. That's something that benefits all of us.

[Sasha Fegan]

One thing I do want to press you guys on just before we wrap up is what comes first, really. Like, if you could say, give me one thing that you think we really need to change right now and that everything else, you know, that the dominoes would kind of line up afterwards and it would be really impactful and high intervention. What would it be? And I know they might not be the same thing. So, Pete, do you want to kick us off?

[Tristan Harris]

Sure, yeah. I mean, I think a really important thing for me is ensuring we have clear lines of accountability. And I know it's something we talked about at the top of the podcast here, but I truly believe that that's foundational to a lot of the change that we hope to see.

[Sasha Fegan]

And how about you, Camille?

[Camille Carlton]

I think for me, it's kind of the opposite side. Right. It's kind of ensuring that we have the rights and protections we need for People in place. So it's like we both need to increase accountability for tech companies and then at the same time, increase the protections we have, whether these are protections around labor, protections around privacy. Looking at those two things hand in

[Tristan Harris]

hand, I'd also just add that the midterm elections are coming up. Right. And we can expect AI to be an important aspect of this election. Right. And so I think it's worth focusing on the political influence of the technology industry, and it's worth folks understanding where their candidates stand on these issues.

[Josh Lash]

We just heard Tristan and Aza talk about how what we need is a human movement, a movement that really comprises all of us, because that's the only thing that's going to balance the scales. And the conversation we've been having today is concrete, and I think people are going to really love it. But I also wonder if people are going to feel a little excluded from it if they're not sort of having their hands on the levers of power, if they're not actually building the technology or, you know, passing these laws. So I'm sort of left with this question of, like, and I'm sure the audience is too. Like, what can I do to make this happen? Is what can they do, our audience, especially if they're not a policymaker or a technologist?

[Camille Carlton]

I think, for me, one of the biggest things to hold for people here is that culture is upstream from politics. Right. Because if we change our norms and we change our culture, it changes how we build products, how we design products. That is paradigm change. And so, to me, people understanding that they have agency to shift things by kind of changing the way we view the world is important. And then, you know, baby steps, right?

[Tristan Harris]

Yeah. And we all have the ability to affect change. And we've seen the way folks like Megan Garcia and the Rain family have stepped up and spoken out about their experiences with harms. We've also seen parent advocacy groups speak up and try to push for change in terms of policy. But then we also see the impact that schools have and teachers and folks across really all aspects of our life.

[Sasha Fegan]

Yeah. For me, as a parent with kids in high school, I mean, we just had a meeting at our high school with the parents and citizens and association about the use of AI at school. So it's also stepping up and trying to have a shaping role and bring some of this knowledge into those discussions at a local level, at a municipal level, because the more that happens, the more we are actually driving that cultural and norm shift. You could be the voice in your family who really brings these conversations to the dinner table and be the go to person in your network who understands these harms and can advise people in your network around, you know, how they can use AI safely and also where the line between what their individual responsibilities should be and where we need to actually pressure our legislators to take federal or state responsibility and we need that help to externally enforce standards and safety measures.

[Josh Lash]

I think ultimately, like you said, Pete, this is going to touch every aspect of our lives. And so we are, we all have a part to play in this. I mean, you can at work talk to your HR person about the AI that you're implementing in your systems and ask about what are the safety standards that you're applying there? What are the privacy standards that you're applying there. You can go to a town hall and you can say, hey, I'm really worried about what AI is going to do to my job and see what they have to say about that. And I'm reminded of the quote that Tristan often uses in these podcasts and it's something that I've, a quote I've always loved, which is the Margaret Mead quote. Never doubt that a small group of thoughts, committed citizens can change the world. Indeed. It's the only thing that ever has. And it's, you know, it's true. It's only going to come from us. And we have to do, we have to step up and do it.

[Camille Carlton]

And I think what I would also offer to listeners is we have really seen the power of individual action with social media. We have seen parents marching on Washington. We have seen people putting their phone on grayscale. We have seen people take action and it took a long time to get there. But where we are with AI is people understand the harms way faster than they did with social media. And so we're kind of at that point of we're ready. It's the time and place for people to come forward. And that same kind of trajectory of change that we've seen from social media can happen with AI as well.

[Josh Lash]

We just covered a ton and that's only four of the seven principles in the report. So I really encourage people to go read the whole thing. There's a lot more detail in there, but it's very readable. Pete, Camille, thank you both so much for coming on today. A lot of food for thought and I'm really excited to get this out into the world.

[Camille Carlton]

Thanks for having us.

[Tristan Harris]

Yeah, thank you so much.

[Aza Raskin]

Your undivided attention is produced by the center for Humane Technology. We're a non profit working to catalyze a humane future. Our Senior Producer is Julia Scott, Josh Lasch is our researcher and producer and our Executive Producer is Sascha Fegan. Mixing on this episode by Jeff Sudeikin and original music by Ryan and Hayes Holliday. And a special thanks to the whole center for Humane Technology team for making this show possible. You can find transcripts from our interviews, bonus content on our substack and much [e-mail] and if you like this episode, we'd be to trying truly grateful if you could rate us on Apple Podcasts or Spotify. It really does make a difference in helping others join this movement for a more humane future. And if you made it all the way here, let me give one more thank you to you for giving us your undivided attention.