So that is fundamentally a different way to aggregate opinions than polls. Because when you poll people individually, they’re going to be quite extreme in their positions. But in a conversation, people read the air, and they negotiate with each other. So I think this is polling plus reading the ...

Right, so you can, as I mentioned, we literally sent text messages to 200,000 people, right? So they all have very good ideas. And then in online deliberation, you can work through those ideas. And what modern-day language models can do is that they can accurately reflect back the group ...

So it is not for me to say when it comes to immigration, what is that creative bridge? What I’m saying is that there needs to be a system of broad listening to allow that bridge to emerge.

So when Taiwan legalized marriage equality, we legalized only the individual part, but their families do not form a kinship. And so this is a creative solution that makes both sides actually quite happy, and nobody very unhappy. But if you do not have a broad listening system, you may ...

Well, in TBS Future Card, I used the example of marriage equality, which is also a topic here. So in Taiwan, we have two different words, one for a wedding between individuals and one for marriage between families. And so the creative bridge was to see that most people who ...

But that was the Hutchins Commission insight, that if you can make the bridging narrative strong enough so people can get behind it, then it has a coalescing effect. So even people who were radicalized are attracted by the bridging narrative, so they become more into the middle again. So ...

I think that speaks to, and that’s a symptom of, the lack of a bridging cause. Because if you don’t have a strong bridging narrative, then any balancing looks unbalanced because you’re always going to be accused of catering to the extremes or excluding voices.

Yeah, sensemaking. Yeah, this is, there’s a specific word. It’s called sensemaking technologies. And broad listening, I think, can incorporate a lot of sense-making into it.

And so again, I think narrative needs to be done with the help of AI to accurately do both the bridging and balancing.

And so the narrative has two parts. One is the bridging part, which is to ensure that people see what everybody agrees on as basic facts or as the general sentiment people can get behind are accurately presented as bridging. So that’s one narrative. Another is the balancing narrative. That ...

So the point I was making was that… think about a newspaper, like Nikkei. On A1, on the front page, you have the news. That is to say, whatever your political opinion is, you probably agree that these things happened, that this is the front page. And once you flip ...

So the important thing to remember is that open source is not the goal in itself. It is instrumental. It means only that people who have very different worldviews can use the same tool to propose their thoughts that can also cross the aisle and become the uncommon ground that ...

So it’s not about open source in the abstract. It is about supporting the ideas coming from the young people that they care about. So this is intergenerational solidarity.

That’s a great question. So in Taiwan, as I mentioned, the 17-year-olds and the 70-year-olds are the most active on those broad listening platforms. And the 70-year-olds are not there to support open source or anything vague, right? They’re here to support maybe their grandchildren. When their grandchildren start an ...

Because it means that if you are from a different background as the digital democracy and the city people, you are not just users of their system. You can find people who share a similar background and fork their system. It’s a little bit like how Bluesky being decentralized and ...

Yeah, I think one of the ideas of digital democracy is that these open source methods are not party-specific. So other parties are also free to use the broad listening systems. And the public good that it creates needs to be interpreted in various different fashions. And by being open ...

In social systems, once you solve a problem, people work around the solution and cause new problems. And so I think that is why we need to work with the people, not just for the people. So techno-solutionism thinks that, oh, elites solve problems for the people. But a social ...

Yeah, I think one of the main ideas in social science is that of double hermeneutic. Right, so as you offer interpretations to society, once the society becomes aware of that interpretation, then the society also changes in how it sees itself. And so it also interprets back. So it ...

Yeah, definitely. Because if you do not prioritize this relational health, then what happens is that you align humans to AI. You have to then interact in a way that AI expects. And then we become very constrained. But the Asian mindset is that if you are a newcomer, like ...

Yeah, to survive. Because my old skill is not marketable anymore.

But in other situations, for example, when we talk about facilitating conversations, providing this kind of mutual care, civic muscle, then the AI is very far from being able to read the air. So a facilitator basically reads the air. It’s like broad listening. And so currently you need to ...

Well, that depends on the area of work, right? In terms of coding, which was my main skill, it’s already there. The AI systems today are like top 200 in competitive coding. So if you’re just talking about translating specification into working code, then it’s already AGI. It has been ...

So for the human coordination, I’m quite optimistic. I think we all intrinsically have the incentive to avert coordination failure. But for multi-agent security, this is much more speculative and therefore requires much more research in order to say whether we’re optimistic or not.

But once the AI systems become much more autonomous, then you would also need the sort of multi-agent alignment. Like when, I don’t know, Waymo and other self-driving cars, if the street is mostly robotic cars now, they will have to coordinate in a different fashion than human drivers coordinating. ...

I think it is important to distinguish between the current AI systems fostering human cooperation and the future stage where the AI agents cooperate by themselves. The first one is quite mature. You can easily see like broad listening, Polis, and so on, many systems already doing this.

Because we must not make the mistake of social media 10 years ago, that thinks optimizing for engagement will connect humanity. It turns out we have the reverse effect. So this time, we need to solve multi-agent cooperation and use those agents to foster human cooperation as well. So this ...

Well, I mean, if you look for papers on multi-agent systems, you will see that this kind of cooperative AI is a very promising direction. I’m on the board, a trustee of a Cooperative AI Foundation. And we have the chief scientist of Microsoft. We have a director at DeepMind. ...

Right, right, exactly. So that’s the distinction between RLHF to have individuals align transformers and RLCF, which is for communities to co-domesticate with AI agents, including transformers.

So what I’m saying is that instead of one huge model that just freezes itself and becomes kind of the epistemic norm for everybody else, this is more horizontally aligned. So it continuously learns from experience. And the experiential rewards are not the whim of a single human or a ...

What I’m saying is that the transformer is technologically based on just one model. And when you say it’s like a Sakana AI model, that means… it’s like a community of small transformers, but they together form an ecosystem. So it’s like permaculture, right? You have many species, each playing ...

I think that is the bet of cooperative AI. It means that these systems, such as Community Notes, that foster human coordination, can get exponentially stronger once AI capacity becomes exponentially stronger. And it’s not just, as you say, the kind of dominating view of AI 2027, but rather, something ...

But the evolution pressure means that dogs learned a little bit on how humans socialize. So if I look somewhere, the dog also looks somewhere. And the human gaze system also co-domesticated with the dog. So we also evolved a little bit toward the wolves. And so the two different ...

Well, I mean, Sakana AI also uses transformers, but they use it in a very different way. They fish for evolution to fit the relational health of an ecosystem, so that they make all sorts of different transformers evolve and swap their kind of genetic materials. And this means that ...

Which means both opportunities—it means that if we vaccinate ourselves, we don’t have to suffer as much. But also maybe it means we don’t have a strong enough immune system. So if a truly powerful variant emerges, maybe we’re not as wary as the Western democracies. So I think it ...

Yeah, so conversely, I think because of this emphasis on relational health, we become more resilient to the polarization virus. So in a sense, we did not succumb to the first wave of polarization. But it also means that we may not be yet over peak polarization. Right? So whereas ...

And so this idea is very familiar to Asian people. I mean, I use a Shinto word, but a similar idea exists in Taoism and in folk Buddhism and many other religions around Asia. And so I think this way of thinking does not need that much translation for Asian ...

So when I say, “Oh, let’s train an AI system that takes care of a specific place or a specific ecosystem or a specific county and so on,” and when I explain, “Oh, it’s like a kami, a spirit, that cares for the community and nothing else.” So you can ...

Yes. I think in Asia, we already see that personal relationships and the health of such relationships is an important cultural value. So we don’t have this kind of, I would say, radical individualism that defines many of the Western conversations.

And we should take that, yes, and the way to accelerate this democratic defense is for everybody to be aware that alternative systems already exist. So like Nikkei can play a large role in making sure people become aware.

Yeah, everybody feels very tired now. Right now, it’s ‘25, and no matter which part of the US public you ask, they are very tired of polarization. They’re ready to move on. So I think the point I’m making is not that we have found the cure for everything at ...

So again, this is because they do not have meaningful competition. Once they reach the network effect, once they dominate the network, it becomes almost impossible for a new network to compete meaningfully. But with social portability, then it becomes possible. It’s like if you build a highway, if you ...

This is like when you’re switching a new telecom; if you must have a new phone number, then not many people will switch, even when the service was bad. But if you can keep your number, number portability, then people can switch. And so the telecom will compete for quality. ...

Yeah, and that’s why in my talk, I talked about the Digital Choices Act. Starting next July, you’re a Utah citizen. Once you make the move, then Elon’s platform has to continuously interoperate to forward new likes, new posts, new replies, new complaints to your Bluesky account. So you lose ...

Which is why there needs to be a competition. So it’s not just Grok writing those community notes. X.com must open its API so you can use Gemini or use ChatGPT or whatever to compete with Grok. And this is what they have done. X.com has opened up that API. ...

Yes, and once this flywheel starts operating, then you can see more and more competition among AI systems that post better first drafts that pull people together.

So the kind of “reinforcement learning by community feedback” trains AI systems not to align vertically to a human individual but rather they align horizontally to human relationships. So if they can post the note that heals the divide, then they get rewarded. And so that way of training AI ...

So once that is done, I believe we can reach a place of what the researchers call reinforcement learning by community feedback or RLCF, so that you can train AI systems to take care of the relational health between the previously polarized groups on social media. So the old AI ...

The problem was the conspiracy theories went trending on X.com, and then after six hours, you see Community Notes correcting it. So it’s not that Community Notes is bad, it’s that it’s not fast enough. And so we’re now working with researchers to make Community Notes AI-written. So you can ...

Well, I think all the trending social media companies in the US, including X.com, YouTube, Facebook and Threads and so on, have implemented Community Notes, which is a bridging platform. The design of Community Notes was heavily inspired by Polis in Taiwan, and we know the team; basically, it’s a ...

And so Takahiro Anno has been running on this platform. He literally said “broad listening” as his platform, and he also gained a seat.