00:16:22 · Jaron Lanier
[00:16:22] S7: Well, so there... There's a couple of things to say about this. The image I always get about the towns with data centers is like human sacrifice. It's like people being dragged to the top of the pyramid in Mesoamerica or something. It's sort of like, we've decided our god is so awesome. We must present it with humans or something. But then as far as getting to the future of abundance, the problem with it is there's this sort of magical thinking that you can make every little decision on the step towards something counter to that destination, and then somehow at the very, very last step, it'll turn around. And the thing is within Silicon Valley thought, you might have a startup that loses money and loses money and loses money. And then it hits its moment of strategic relevance, and it might be acquired by one of the big companies for a lot of money or something. So when employees at tech companies say, hey, we're being more productive now because we're using this model. And then they'll say, can we work less? Oh, no. You cannot work less. You must work more. And we've seen that interaction at Meta, for instance. Mhmm. So Meta for a while was just asking people to use as much AI as possible, but then would not allow them to reduce their work hours. And so the question is, well, like, if people even inside the industry aren't able to, what's the magic event where that turns around? Now the question of, like, why are we doing this? Why are we doing this? I've puzzled over it for many years. Part of it is that there were some people who really wanted us to do this, and it's been a pretty explicit agenda for decades and decades. Going back twenty or thirty years at least and really longer, there was this realization that the structure of code, because it has so much impact on people, because it it not only addicts people, but it also creates the the maze within which they can operate. It creates the the field of available actions to them. Like, you know, if you're using a software interface to to access products or government services or whatever, you can only work within the structure of that software, you know?
00:18:21 · Jaron Lanier, Danny Fortson, Katie Prescott
There was this realization that software design would be the new laws, the new culture, the new everything, and that government and culture and all that stuff were just temporary irrelevancies that we would just wipe away, which is what we're doing. We we treat all that stuff as... We treat government and Hollywood and journalism and everything as just kind of transient bullshit we can, you know, override. And so The question is what to do with that. And there were many schools of thought going back, like, in the eighties, certainly, of, like, well, we should do some kind of new golden age of democracy with better participation. But then a lot of people... And some of the famous ones are people like Peter Thiel, but there were a lot of others who were saying, you know what? We can get stuff this way. We could never get through democracy, and we should just get our way on this. And these are people I know. They've been acquaintances and, in some cases, friends for years. And they have a sort of a sensibility which, if it were just one of many, would be interesting, but when it becomes dominant, becomes really, problematic. [00:19:28] S10: Today's episode of the Times Tech podcast is sponsored by ServiceNow. [00:19:32] S11: ServiceNow describes itself as an AI control tower for business reinvention, connecting people, systems, data, and AI so work flows more smoothly across an organization. [00:19:43] S10: The platform integrates with different clouds, models, and data sources, bringing them together in one place to help your team.
00:19:43 · Danny Fortson, Katie Prescott, S0, S1, S2, S3, S4, S5, S6, Jaron Lanier, S8, S12
[00:19:43] S10: The platform integrates with different clouds, models, and data sources, bringing them together in one place to help your team. [00:19:50] S11: To learn more about how ServiceNow puts AI to work for people, visit servicenow.com. [00:19:57] S0: People are disappearing again just like before. [00:20:03] S1: Nocturne. Now streaming on Apple TV. Lief Schreiber. [00:20:09] S2: Walter has a way of getting to people. When he does, they don't come [00:20:12] S3: back. Steven Graham. The world [00:20:14] S4: is full of dark places. Zarcee Beats. [00:20:17] S5: How's he getting messages out? [00:20:18] S6: He's locked under six feet of concrete. [00:20:20] S7: She's still alive. [00:20:21] S6: I'm gonna [00:20:21] S8: find her. [00:20:22] S1: Nocturne, now streaming on Apple TV. Subscription required. [00:20:28] S12: When something significant happens in British politics, stories are always unfolding behind closed doors. The State of It podcast from The Times and The Sunday Times takes you inside the room where it happens. I'm Stephen Swinford, the political editor of The Times, and with me are Patrick Maguire, Lara Spirit, and Ben Riley Smith. We will bring you scoops and analysis about what is really going on in Westminster. Listen to The State of It twice a week wherever you get your podcasts. [00:21:04] S10: So it's 2026, end of twenty twenty six. I now endow you, Jaron, with a magic wand. When we think about how this is being built, how it is being deployed, how would you remake it, and is there any possibility that, like, there is a remake
00:21:04 · Danny Fortson, Jaron Lanier
[00:21:04] S10: So it's 2026, end of twenty twenty six. I now endow you, Jaron, with a magic wand. When we think about how this is being built, how it is being deployed, how would you remake it, and is there any possibility that, like, there is a remake [00:21:24] S7: Yeah. So possible. Alright. So I've said that I think the core idea of doing giant statistical correlations of stored human data to do better searching and extrapolation and collaboration is a great idea. I'm into that. So the next question is, if I don't like agents and I don't like these addicting chatbots, is there something else to do with it? And, I mean, I can tell you about something I've been experimenting with lately that I think is better. [00:21:51] S10: And Okay. [00:21:52] S7: So... Look. Right now, let's say you wanna get something out of AI. You want some result. And just for the hell of it, I'll say you want a synthesized video clip of something. [00:22:02] S10: Mhmm.
00:22:03 · Jaron Lanier
[00:22:03] S7: And I'm gonna presume that you have a good reason for it. It's for education, and it's not for deception, and it's not... That you're some horrible thing. Alright? I'm just gonna presume it's a great thing. Like, I want a a demonstration of how annealing works in a... Or I don't know. Whatever it is. Okay. So, right now, you prompt for that, and now you get something. But in most domains, the description itself is gonna be imperfect because that's the nature of description. But furthermore, the act of making is an exploration in which you learn more. And one of the problems with prompting is that you deny yourself that learning. You're just supposed to get this thing. And what actually happens in real human creativity and invention is you get close to the thing, and then you start tweaking and experimenting, and then you learn more and more and more, and then you get somewhere. So my thought was a better way to do this is instead of prompting for a result, I prompt for an editor for results in the neighborhood of what I want. So let me explain what that might look like. If I wanted to prompt for this short video, what I would say is I wanna have an editor for two minute clips that introduce annealing using video. I wanna have six sliders in order to explore variations on the video. One of the sliders is for degree of visual detail. Another is for degree of historical reference. Another is for degree of technical accuracy. Another is for... Well, I don't know. Right. You you come up with these things. And then you get this thing and you start playing with the sliders. And now the interesting thing about playing with the sliders is that you start learning. You develop your intuition for what you're doing. So instead of cognitively offloading, you're cognitively enhancing. Two is the question of authorship becomes clear. You're the author of what you choose. Three is you're getting what you actually want. Whether this particular method is the right one, I can't say it's too early, but the thing is what it does is it gives definite human authorship, definite human role. It gives human documentation. It gives human exploration. It gives human intuition expansion. It gives more accurate and better results, I think, at least so far. So can that happen, or is that inadequately worshipful of the new AI god so that it would be rest as heresy?
00:24:23 · Danny Fortson, Jaron Lanier
[00:24:23] S10: And Right. Because in that, it is secondary. Right? It is in service to you as opposed to vastly superior to you, and therefore, you are like a supplicant. [00:24:37] S7: Yeah. So the question is, do we want the Oracle at Delphi or the library at Alexandria? You know, like, which which model is better for civilization? [00:24:48] S10: So just stepping back, are you an optimist here late in 2026? [00:24:54] S7: Well, look. Okay. So first of all, just to be clear, I'm a heretic, but I haven't been expelled from the temple. I'm still Right. Called it, you know, unifying prime scientists at Microsoft, one of the places selling agents. [00:25:05] S10: I By the way, what is a unifying prime scientist? I think that might be the coolest title anybody who's [00:25:12] S7: got on this pod. I used to study cephalopod cognition, and it was a joke because I'm in the office of the chief technology officer, so it overall spells out octopus. [00:25:20] S10: Gotcha.