Balaji and Taylor Lorenz on AI and Media

**Balaji Srinivasan** (0:00)
I think the media guys think the tech guys started it, and the tech guys think the media guys started it. I think the media guys think the tech guys started it by economically disrupting them.

**Taylor Lorenz** (0:07)
I think this is why we're seeing such a resurgence in live streaming and interest in these sort of like, communal experiences, because like, live is something that is so hard to fit, it is such a like, a human thing.

**Balaji Srinivasan** (0:17)
We actually need to have decentralized cryptographic truth that's not behind a paywall, that anybody can verify, no matter how poor they are, no matter what. I think just like you should not be subject non-consensually to government surveillance, you shouldn't be subject non-consensually to corporate surveillance.

**Taylor Lorenz** (0:33)
Okay, but what about an independent media reporter? Is that okay?

**Theo Jaffee** (0:38)
What happens when anyone or anything can generate information at scale?
AI is making it easier than ever to create content, but much harder to verify it. As agents generate text, images, and even identities, the systems we've relied on for trust, from media institutions to social networks, start to break down. In response, new ideas are emerging. Cryptographic verification, decentralized identity, and new forms of social coordination that aim to prove what's real, rather than simply assert it. But these shifts also raise deeper questions about privacy, accountability, and the role of journalism in an AI-driven world. To understand and debate what comes next, Theo Jaffee speaks with Balaji Srinivasan and Taylor Lorenz.

**Balaji Srinivasan** (1:26)
And so, I think as much as I like AI within the digital tribe, it accelerates coding, it's great for search, all this kind of stuff. Between digital tribes, it's often bad because it's just, you know, AI agents spamming 50 different people with a resume or a sales email or something like that and just breaks the commons. And so, we're going to need to have, I think, a whole new generation of human-only social networks.

**Theo Jaffee** (1:51)
I don't know how verifiable that would be. Like, you can assume some kind of biometric method of proving that you are a human. And so, you have your account that says, I'm Theo, I'm a human. But then on my account, I can just post stuff that I generated with ChatGPT, you know, maybe with some savvy prompts to get around Pangram.

**Balaji Srinivasan** (2:08)
But here's the thing. Yeah, well, here's Web3 of Trust, right? So, you would have the way, so there's a whole just gold cat and mouse here, but just to give you a sense, Web3 of Trust is A asserts that B is trustworthy, who asserts C is trustworthy, who asserts D is trustworthy, and then the trust drops off, right? You trust your friend and maybe trust your friend's friend, but probably not your friend's friend's friend's friend's friend, right? And so, there's a way of modeling that mathematically, and you can have not just one proof point, not just A trust B, but also, you know, X trust B and Y trust B and Z trust B, and they trust them for a bunch of reasons, all of which is expressed in the metadata on the edges of nodes. And then you can do a calculation and inference of what is a probability that somebody continues to be human. And then you also have not just automatic, pan-gram style reporting, but you have manual flagging of something.
There's a certain set of signals people can look at.
And I think if you establish the culture as being human only, and you also take away some of the payoff for pasting just reams of AI text, I think it's possible to do it. It's a little bit like Snapchat, where, you know, Snapchat is disappearing messages, and yes, of course, in theory, you can take a photograph of the thing, but in practice, it did deter people from doing it. So you can set the culture in such a way that I think you can deter it.

**Taylor Lorenz** (3:31)
I think, instead of, like, I agree with all of that. I think that people will probably just gravitate towards formats that reward, I think this is why we're seeing such a resurgence in live streaming and interest in these sort of, like, communal experiences, because, like, live is something that is so hard to fit, it is such a, like, a human thing, and so I think people are just gravitating towards those formats that sort of prioritize these, like, human communal experiences.

**Balaji Srinivasan** (3:57)
So that's why we're doing Network School, for the human part of things and having people meet up in person.