How To Re-think News in the AI Era

0:00 Welcome to this enter life Alex. You know, great to have you on the pod today, and you know, the visionary founder. I think of other web you know and the like really ground blacking and cool platform that's helping us rethink what news can be and what what information can be online, and so I was excited to get in touch with you to think about this and basically how we can rethink how we consume information online and what is our responsibility both as creators and as consumers. So, first off, welcome to the program, and great to have you. Thank you so much. It's great to be on this kind of open up with this idea, why start caring about digital joke? You know, when you said it and I heard about it, I was like, okay, this is this is the thing that matters. You know. How did you find yourself asking these questions around joke? Well, I think I was primed to care about it from my childhood a little bit because I was born on the Soviet Union and I kind of saw what a society looks like if nobody has any idea what's going on interesting, and everybody just makes the wrong assumptions or they're pretending to know something, but they're kind of ninety percent sure it's not true. And I have these vivid memories of my and slocking themselves in the closet or in the bathroom or someplace where the neighbors won't hear, and listening to the radio to hear a voice of America at four am. Wow. Interesting to get at least some idea of something that might be true, even though it's foreign propaganda. Right, But it was foreign propaganda in the country that had its own propaganda that was worse. So I kind of thought that knowing stuff is important and it probably leads to better actions. And I thought that my entire life. And so when at some point I had this crisis of conscience a few years ago and thought about what I want to care about next, what I want to

1:32 work on next, that seemed like a good idea. Right, the stuff we're all consuming is becoming worse. Yeah, nobody seems to be talking about it, or if they're talking about it, they're all trying to come up with some villain to blame for this, which is typically not why bad stuff happens in the entire world all at once. It's usually not a villain, it's something and the evolution of content has gone wrong essentially. Yeah, that's that's actually really interesting, and so I guess, yeah, the one head, it's like our brains wanted to jump to and say, oh, it's it's this person or this country's or this idea's fault. But but you're kind of saying that we're seeing at the same time just the rise and I'm like visualizing in my head, right, just the writhing piles of paper or trash, right, that just kind of like piles around us. But it's funny that digitally we we yes, like people may not think about that idea, right, like that there's so much that's kind of around us all the time.

2:21 But you know, I think people might we definitely recognize, like do we all feel busier all the time? And I think part of it too, is like our attention is always grabbed, being pulled towards different little you know, whatever blips and blaps of our phone or emails. But most of the time, I think, to your point, it's a lot of junk, right, like the reason we have a spammer junk filter in our email. But beyond that too, like how do we know what we're consuming? So uh, I'm curious to you have to kind of get get your perspective on this too, because like, as we've gone in like deeper deeper into the digital realm, and we're not going to come out of that like back to back to paper or something else that's more analog entirely. You know, has as we see have you seen like people's kind of perception about this like shift in terms of like do they feel like they're getting more junk now than we had before? Like is it something qualitatively different? I guess about like the kind of junk that we're seeing than twenty years ago. I mean, you can both quantify it and look at it qualitatively, right, So we tried to quantify it recently by hiring the Harris Polling Company to do a poll.

3:14 And one of the questions they asked is are you spending more time than you did five years ago reading the news? And more than eighty percent of people said yes. Interesting, And they asked, okay, do you have more confidence than you did five years ago that you know what is true? And most people said no. Then, so people are spending more time and they know less and they are certain of less, and they find it harder to figure out what is true. So quantitatively, that's happening all around us now. Qualitatively we are noticing this. Right when you see CNN publish an article with a title like stop what you're doing and watch your slefant play with bubbles, that's an actual see in an article, right you realize in your childhood this wasn't the thing, and see that stuff pass editorial review in the you know, Cayble News Network in the nineties. So something is new, something is happening here. It's happening gradually, but it's now reached this kind of monstrous proportion. Where by the way, you mentioned spam filter. One of the questions we asked was do you think there's a need for a spam filter on the endternet? And eighty nine percent said yes, I would agree with that. Yeah, that's an interesting question. So it's like part of it is we might have a filter problem. But then I think you know, as you know there too, like what used to not pass editorial content walls now seems to do that, right? Is that part because we've seen like I don't know, business model shift, you know, from from tech advertising and things like that in terms of like what or like why we're getting so much content, Like like why in your experience have we seen that shift

4:46 happening, like in terms of we're getting more stuff that wouldn't pass, you know, twenty years ago. So there's a few reasons, but I think the big one it's not that the business model changed. It's that we actually became better at implementing the business model we already had. So starting from let's say two thousand and three or so, we became really really good at tracking how ads perform. We can now track every impression, every click, every single thing. And there's no longer this consumption of a packaged good called and daily issue of something where you have a whole bunch of articles at once, every article fence for itself, and it's all judged by this perfect tracking on how ads on that article perform. And once you have that combination, now suddenly there is just no incentive to produce anything other than clicks and views.

5:32 So you have a single selective pressure. You're an evolution guy, so you understand what that leads to, right. It all leads towards all content evolving over time towards that thing, regardless of what the intentions of the people creating it are so if the intentions are good that it doesn't matter. The ones who have bad intentions probably outperformed the ones who have good intentions in the long run. For as to say, for a better offit worse, we're probably just for worse, right, Yep, that's but yes, I think I think that's a great point too, in a great view of like the incentive structure of just the business model getting better, we're going to see than the pressure kind of push us in one direction. So as you think about that, like, I think there's I mean, I think a ton of directions that I want to explore here, but like to keep us like moving in this one for now, like thinking about this idea of like, as we're seeing this explosion of this kind of content and we have this pressure that's basically just trying to feed this one algorithm, Like how can we I guess in one hand, like think about sort of shifting that model, right, you know, and this could be kind of work you're doing with other web but just also thinking that just like how do we I guess? Are like in addition to yourself, are we seeing other people kind of ask this question and say, hey, hold on, like, there's just a lot coming at me all the time. We should ask about how we think about sources and like what's what's actually moving in this way, like what it looks like to you. So there's a lot of people ask him the same question, and they are all coming up with different solutions. So I have some reasons why I think mine is best, right, But in reality, you have a lot of companies like use Guard that are basically saying which sources are good, and all they do is kind of the JD Power approach which works in automotive.

7:05 They apply it here. Just the rank sources, give them some number of stars, publish annual rankings, things like that. The problem I see with that approach as it's basically spreadsheet level filtering. Right, So first of all, you're assuming that all sources are consistent. But what is substack? Is substack good or bad? Question? It's both. There's a huge variance there, right, But Okay, what is the Washington Examiner? Is it good or bad? Seems to me like the news articles are good, the op eds kind of suck, right, So there's a lot of variance even within that in itself. So that's one approach and I have my columns with it, but it's good that it exists that people are working on it. Then there's the Tristan Harris approach of just going to Facebook and saying please be nice. And I'm sure that there's some value in that. It's creating this sort of public pressure to not be evil, to use a Google slogan for years past, right, But I don't know that that works when it collides with the c Corps fiduciary duty to maximize the older value. It seems like being nice if you're a company that makes money from ads is kind of it goes against what makes you money and what you're supposed to do as an executive.

8:16 So I'm not sure that's going to work in the long run. So our approach has been for as long as this is the ecosystem we are in. We want to create some sort of penalty for bad content, so we want to help people select good content. And when people select good content, the secondary consequence is that they're not selecting bad content, and therefore people creating bad content get penalized less people see them. Now, this will only become really meaningful when we become really large, or if one hundred more other webs come up and do the same thing, and then all the people who consume content through something like this will basically filter the bad stuff out. Bad stuff gets pinalized, air go less incentive to produce it. Now it could be less binary. So I see a future in which it's not just filtered out or not filtered out, but in which we can go to ad networks or advertisers and say, here's how you evaluate how each article would score. Give that to advertisers, or if you're an advertiser, yourself scale how much you're willing to pay for an ad or for a click or for a view on this content, right, and that would create a real kind of sliding scale incentive for people to produce better content than they otherwise would have. It's like like provide And that's the interesting idea though, because it's like providing a scale of like what would be worth for them monetary value of based on like how how I guess? I mean. The question that naturally comes to mind then is like, how are we thinking about what makes good and bad content?

9:48 Right? Like if it's a one handed filter? But then also like how can we determine these ideas like beyond a qualitative opinion, like a clickbait comes to mind, is like a topic that doesn't actually tell you anything article itself, you know, But like what makes something good or bad in this context? It's a tough question. I've talked to a bunch of people with degrees in philosophy and they don't agree with each other, right, But yeah, in general, I would say that good content is content that serves its stated purpose. To the degree that something does, it's good, right, And you can basically rank content along how well does it serve the purpose. So when I look at news, it's supposed to inform you about what happened, right, So to the degree that it informs you, it's good. To the degree that it tries to persuade you without actually giving you new information, it's probably not so good. Right. So, if you look at how we rank content, it tends to track pretty well with your impression of how informative versus opinionated this thing is interesting, okay, Right, But then if you're looking at opinion content, obviously it's not supposed to be purely informative.

10:50 It's supposed to be opinionated and controversial in all those things. So You're probably going to grade it based on how interesting it is or how much it stimulates your gray matter, that kind of thing. So every type of content is going to have its own criteria. Now how do you rank it? That in itself is a hard question. Even once you know what the criteria are, how exactly do you rank content? Our approach to it has been, at least in the news department, we basically say, what are all the bad things we know how to detect? Your score is going to be one hundred minus adding up all the bad things. A clickbait is an example you mentioned. That's one of the things that we detect, and if the headline has clickbait, you lose something like five points, and then over time we just add up all the penalties. Cool is that? Is that that list of bad things? Is this kind of an open source list or is this kind of a trade trade? Each one of those models is source available, so which basically means you can look at it, you can test that, you can't reuse it at open source and in general, you can see a nutrition label next to each article in our platform, which includes most of these outputs. Some of them are not their row outputs, but with some additional processing. There's also source available, right, But that was the general idea that you can see kind of what we ran. In fact, you can see some things there that don't actually end up in the big score. So yeah, if the article has affiliate links, I don't know whether I should penalize it or not, but I think you want to know about it,

12:22 yeah, because if you're using it basically as a product endorsement, you should probably take it with a grain of salt. If you're just looking at it to figure out which new laptops came out this year, then you don't care that it has affiliate lengths. It's still good for you, right, So it depends on your purpose. It seems like that's the kind of part of the work of kind of retraining or thinking around around getting rid of Junker. Being smarter or mindful about how you consume. Is understanding kind of user intent also, or like you're helping users recognize what their intent is. We're looking for for some content, right, Because if I you're right, if I'm looking for the best laptops I came out this year, I'm actually happy to have links, right because I can go there and find where to buy them versus you know, if it doesn't show me so is that kind of part of the model. But if you're trying to select which one is the best one, then that's probably a bad article for you, right because all I did was copypaste the marketing materials from the manufacturers. That's a good point too.

13:09 Yeah, So I guess do you do you write that kind of or do you kind of check for that that type of thing, or you can see the articles actually just doing that, like pulling press releases. Well, so we definitely see that. I wouldn't even think that we need to penalize for that because at that point we don't know the users intent. So what we can do is we can help users kind of structure their feed the way they want. And here I don't know that I can define how to even ask the user a direct question what do you want and then adjust their feed based on that. So I just try to give the user as many knobs as possible. So actually, if you go to our advanced customizations, you're going to see a lot of things that kind of look bizarre. We even classify every article based on which emotion it's most likely to evoken the reader.

13:54 And then allow you to customize how much of each emotion you'd like to get from your feet interesting, and we try to detect that automatically and adjusted, but then you can go and override everything we detected automatically because we don't believe in black boxes. Yeah, I think like that's the question of transparency. I think is has become so important right as we to go back to your hair's poll point above, like that we read more, but we like trust less right that the more kind of we consume, and some part of that too is recognizing what's coming at us. But then also to this point of like can we see how and why it's coming at us right now? Can I what role of control do I have? And that I think it's really interesting point. I'm curious like as you think about like both data, like do you see like patterns of behavior emerge that are interesting, Like in terms of you see a lot of people pre selecting for happiness or like they're they're like are they are? They are they not selecting for emotion? But then it turns out we see like a you know, a likelihood or a preponderance of of like I don't know slightly enraging articles pop up as people click through or something. You know. Yeah, I think the sad thing that I'm seeing for the most part is the most most people, even if they find the configurations, don't use them. They just use it default. So, you know, I wish I could change that, but it's really hard to get users to change the default. So we have this parallel track in our mind where we want to give users all the controls that they might ever want to have, but at the same time, we have to spend most of our efforts tuning the defaults because that's what most users are going to end up using. Now, I wanted to mention one other thing based on what you said earlier, which is that there is probably a nefarious element here of what

15:28 you call the single algorithm. Right, The vast majority of social media and other media companies out there right now are essentially tuning everything for maximum engagement. Right. They want to get you more engaged, they want you to spend more time on site, they want to share more, to reply more, etc. Now, engagement is something they get out of you, it's not value that they give to you, right, And so if users are feeling like they're spending more time and they're getting less in return. It's not accidental. That's exactly what the algorithm has been tuned for to get as much as possible out of you, and how much it gives you in return. This kind of beside the point, right, and therefore it kind of gets kewed in one direction. So I think as a user, you always have to be cognizant that this thing wants something from you, but you're not here to give the thing what it wants. You're here to get value, right, and you're optimizing for something that is the opposite of the algorithm. From that perspective, any algorithm that is a black box is already bad for you, right. You want an algorithm that's maximally tunable because then you at least have a chance to get some value out of it. If it's not tunable at all, then you've lost the battle already. That's a super important point.

16:41 And it is always like one of those back and forth challenges like working in user experience. Right, in an experience design that you want to give the user a sense of both control in terms of like what they what parameters they may want to use. But then you know this is a good example where they either only use so much ago for the default, but then also but this fundamental point is great where it's like, engagement is not about me as the user, right, it's about me serving an organization which feels weird. And I mean that's a great way to like define this idea. I was talking with a documentarian David Donnelly a few episodes ago about kind of the price of like convenience rather the cost of convenience for this kind of like algorithmic software, and this is a it's a good one here where it's like there's the the emotional social media challenge point, but then there's other side here that that you're saying to which is really important to recognize that like what I'm getting out of my typical news media consumption is incidental to what they're actually doing getting out of me, which is you know, my engagement, my clicks looking through ads and things like that. That's that's a that's a great point too to think about. And so as as you approach that is this like when we're kind of giving users between those two, its like of like you know, as many options as they might ever need versus like tuning that that default you know, I've got thinking about this, I guess in in the of the broader question of like how do we move towards what we feel is kind of like ethical technology right now? Theical technology development, you know, because it sounds on one hand like there's the Tristan Harris model and all tech is human kind of approach, which sounds nice and humanistic because on one hand it is right. But then there's this other side here of like, okay, but how are we actually making and deploying ethical technology or ethics into our technology itself

18:17 and for people to access? And so I'm curious, like how you think about this idea of like and I regize I'm putting the word ethics into this conversation, but just like, I'm curious how you approach that idea of developing technology for people. I mean, if you see the wall behind me and the bookshelf behind me, you see the word ethics appear many times in many places. I care about the subject deeply. I don't know that you can put that as a parallel track. I mean, we tried in some sounds, we registered ourselves as a public benefit corporation to have this parallel track of we have a mission that we're trying to maximize and we're trying to make money, and we are not forced to choose just one and not the other. Right, we can maximize both, But most companies aren't like that. So I guess my first answer would be, let's try to maximize the number of public benefit corporations in the US instead of just sea corps, because a sea corp is a very limited structure. If even if an executive really wants to be ethical, sometimes it goes against their fiduciary duty and they might get sued by doing the ethical thing. So that's one answer. The other one, which I guess is more higher level abstract, is that incentives drive everything, and every time you try to regulate something against the incentives of the population, regulation fails. In some sense, it becomes a corrupt system because now all you need to do is maximize your incentives, and they then buy the regulators with the money you just made. So that's what we see in a lot of different industries, and I think the solution to that is to just think through the incentives, think through the selective pressures that we are creating for this population of people and population of information. Meames for lack of a better term,

19:52 and try to optimize that because ultimately that's what's going to happen, whether you'll legislate against it or not. Yeah, that's true. I guess here, like the social often will structure, but then follow the incentives, right and then and then whether or not you like set up rules in that place in front of those, it's going to then either find a way around. And people are ultimately really good at convincing themselves that they're doing the right thing when they're doing what benefits them, right, And so nobody just or at least very few people set out with I'm going to do the bad thing and make a lot a lot of money, right. No, yeah, hopefully that they first they're following the path that seems to make a lot of money for them, right, and then time up they come up with the reason of why this is amazing and it's actually the good thing and the ethical thing, right, don't do evil connecting the world. We see that with every company, right, they all have good missions and then they just make a bunch of money and yeah, but they still believe in the mission. It's not like they just scratched that and throw it out. It's just somehow the mission morphs into whatever happens to make the most money. Yeah, that's interesting, I mean, and so how are you thinking about that? I guess like as other web is growing, I think you have over four million users now, right, and like how are you getting close to ten? See my name is that to day? So there you go. So that's amazing, you know. And so it's like, how do you think about that as you scale, like both having the mission in play and then and then kind of keeping that So one way as again the public benefit corporation, right, the other one is the source available right. Both of these are essentially ways to bind our future selves and two so that if in the future we

21:26 have the incentive to more for mission into something slightly less beneficial, it's going to be harder for us. Right. So that's I guess the best I can do at the company level. Now. One other thing to kind of consider here is that everything that we discussed so far, and I'm sorry if this is going to explode the discussion, right, but everything we discussed so far maybe temporary because we're getting really close to this inflection point where AI models are as good at writing as the best humans. Yeah. Right, it's basically like chess circa nineteen ninety seven. Right, Deep Blue is just about to beat casparav And the moment that happens, all the incentives that we just discussed they changed a lot, and it's probably going to be pretty binary.

22:14 It's not going to be gradual, right, there's just a magical moment in time at which the work of sitting down and writing an article becomes worth zero dollars. A scary prospect, I think, but that's interesting, Yeah, it is. Right now, it's still really hard to find facts to write about, and it's still really hard to figure out what will people care about that I should actually write about. Right, both of these decisions are probably still human for a while, right, AI models can't go to a garage and talk to Deep Throat and figure out what our gate, Right, it has to be humans. But once you have a set of fact, it doesn't need to be written down by humans anymore. It can be just documented in shorthand or filled out in a spreadsheet somewhere, right. Yeah, And then after that, the act of writing itself seems like a very well defined, well bound task. So once that happens, a lot of what we just discussed might change a lot, because do you really need this many people writing stuff? Do you really need publications that package many written articles together and call it a daily issue? That already seems questionable even since the Internet started, because nobody's reading daily issues anymore. People are consuming one article at a time, so the whole idea of a publication is kind of pass a already.

23:26 People are just picking specific articles from Twitter. Right, But do you need Twitter in this world? Right? In a world where writing is free, Why can't something just be written for you on demand with a target audience of n equals one? Why do you need a bunch of written things that have each been read by eighty eighty thousand different people, right, and you just need an algorithm that selects the ones that you might like. Why not just have it written for you? It costs zero dollars to do that? Right? And so the this is why you asked me before we started about our new news concierge. That's the first kind of prototype towards doing something like this, writing for you on demand whilstill you know, being trustful about the facts and not just inventing stuff you might like like some other companies might do.

24:15 Yeah, but that's the general direction. And I don't know how this affects the incentives of everybody here. I can only guess. Yeah, that's a great question too. Yeah, And it's it's like we are at that interesting inflection point right where we're we've seen like now we've been you know, a year and a half with like CHATGBT in consumer mindset, you know, as a as a consumer facing product, And it's like, it's to your point because we have not seen the hallucination question go away at all, right, in terms of like it still tends to make up answers we've seen, like you know, there are products trying to rectify some of that like perplexity right to like add in like their sources as part of the search engine. But you make a good point too in terms of like as a generative product, you know, how do we both think about what content is created news already? Then? Also yet, like when we get to a quality level of production, what might that look like? So this is interesting. I mean, so in this case are you talking about like, on the one hand, like there's the we can talk about like the capacity to be able to chat with the news, right, is kind of the news concierge.

25:12 But then there's the other side of that, there's a content creation side to that that journalists are like, I mean, could I guess questions, could anybody generate quote unquote the news from other sources? Like when you think about that, the idea of making something or talking with it. In some sense, I think journalists are serving two different functions, right, They're trying to find things worth writing about and trying to figure out which things are true and not true and which things should be packaged together in a single story or not right, And then they are writing, And we are selecting as our journalists people who are in the intersection of the Van diagram of these two skills that are completely different. Right, one is basically a PI and the other one is a fiction writer. But we are demanding that their journalists be both.

25:56 Interuestion, should we or can we make this job much easier by just hiring pis for the job of a journalist, right and saying, yeah, but your writing can be completely incoherent, it can be dyslexic, it doesn't matter. As long as you can find the facts, you're going to be a great journalist. And then there's this magical black box which, when you feed the facts into it, is going to write it really well and not hallucinate. Now, hallucination is an interesting topic because it happens on two levels. Right. There's the level of the larger language model itself, which basically, we train the system that looks at sentences with a missing word and guesses the missing word. Right, That's what we did, right, And then once you ask it to guess one thousand words in a row and produce a thousand word article for you. The problem is that the error compounds, and basically the level of error it makes in the one thousands word is much larger because it's just assuming that all the previous nine hundred ninety nine are correct, but each one of them had some sort of error chance, right, So it's built in them allel itself. Now. The other problem is we then train this system on the entire Internet, and most of the Internet is junk.

27:06 We kind of start also fair, right, So it learned a bunch of things that are just not true. And I've caught Chadgipt giving me answers that are basically a part of somebody is April's fool's joke right, which, Okay, one person said it, zero person said the opposite. Therefore it's true that's how LOLM has learned. But obviously that's not what you want from your news articles. So all of these problems exist. But then the question is what if we start stop thinking about it as generation, and we just started thinking about it as synthesis. Right, here's the data, now write it up in the best way without adding anything of your own. It seems like we already have the tech to do this. In fact, we already have the tech to do this. It's just not launched yet, and so maybe it's still not as good as the best journalists at writing, but give it a year. The scary but also helpful part, right, is that these things learn fast, right, The technology adopts very quickly to that point.

28:02 That's interesting too, like just being so, is it kind of like getting a well put together like you know, retrieval augmented generation search tool like that just says like, just stick with this data only, do not let go. That's what concierge is. Yeah, there you go. It is a RAG. There's a few more steps in there beyond the RAG because one of the problems with just a basic rag for the news is that it wouldn't know what's important. Yeah, right, So if you just ask it to summarize the news and AI research over the past two months, it doesn't know which of the news items or the topics are important. So you need a few additional steps to figure out this was actually more important than all the stuff that came after it. So don't sort by recency, sort by something else, right, But other than that, Yes, that is the basics, right of that last step, the personalization. Now the first step I'm talking about is that's a bigger step, right, Yeah. Should AI be createyating most of the content to begin with from facts that were curated by humans in some way and we're working on something new that hasn't been released yet. There cool?

29:08 I don't know if, yeah, but in a broad sense then, but it sounds like that is a direction that that you feel shows promise rights as a thing to think about as it's inevitable. Also it could be inevitable. Is it just seems like one of those things that maybe the industry is still undnial about it, right, but it is completely inevitable. I just don't see another way. It's just the question is who does it? Does it asks or somebody else? And whoever does it actually? Like are they going to do what I said, which is make it actually write things that are true? Just have AI do the writing, or will it have AI write whatever you want to hear, which is probably going to result in more clicks but might not be very good for the world. Yeah, it's an interesting question too in terms of like if I pick it abat, if I if I'm a reporter, I mean organ as anthropologist, right, I mean I do interviews with folks and do you know, surveys and if I'm collecting a bunch of data observational out in the field and blah blah blah, like come back and I dumped my notebook into into a tool and say help me summarize and like bring out you know, the top four themes or whatever, like you know, say help me write a story about something that we saw in the data. Like there's also the interesting question too on the on the editorial side, in terms of like fact checking and making sure that it's doing it's not to your point, making anything up. And then on top of that, like is it telling a story that is like helpful to humans?

30:33 Right? To think about that. That's an interesting question. Like I'm curious with on that too, because it's like there's a couple levels where human in the loop would would be necessary. I mean, I can see how this can get mitigator automated at some time over time, but like, how do we think about that too in terms of like who who might or when? In what scenarios does do something? Check what's get written before gets published? You know, well, I think in general, if we just use another industry as kind of an analogy of how this might go. Right, think about the fact that initially computer was a profession. A human was computing. It was using some sort of a calculator as an aid. Right. Well, before that there was no calculator. Then the calculation part was automated with a calculator. The computer was still doing the rest. Right. Then we started creating digital computers that replaced those humans, right, but they still had programmers who would program everything, single thing, one command at a time.

31:27 Right, and fast forward to today. You might be clicking some button in a big piece of software. Somewhere underneath there are multiple abstraction layers. You are not expected to know what commands run on what core on your computer, right, So generally speaking, the human is always in the loop. The question is how many layers underneath are obstructed the way, And so we're just getting to the point where the writing level is going to be abstracted. The editorial level is probably still not going to be for a while, but then eventually that might go and we'll see how far this gets at some point. I mean, not all technologies scale exponentially all the time, right, Some things reach a plateau and get stuck there. I mean, we haven't had a faster airplane since nineteen sixty seven, so you can't expect all the condor I'm talking about commercial air flights, like, I'm not talking about military.

32:22 Yes, there's some advances there, but in general, yeah, not all technologies progress all the time. At some point, all the smartest humans just say, Okay, progress here is really difficult, let's switch to this field, right, and they start working on something else. So I don't know at which point this generative AI trend might just reach its apex, and unless there's a big kind of change coming afterwards, we're just going to be stuck there for a while, But then breakthrough might happen. Again, I mentioned just before. Sorry if I'm going on tangents, right, that's good. Nineteen ninety seven the Blue Beats cast part of Right, the next big progress in chess is two thousand thirteen. If you look at the strength of chess programs between nineteen ninety seven and twenty thirteen, it's basically flat, even though it was progressing the entire time until nineteen ninety seven. Right, that's for sixteen years, and then from twenty thirteen onwards. Humans are nowhere in the picture. Right, They're not even necessary in the loop playing in tandem with the computer. They're just too slow to make a difference. Yeah, which is that's why we just play in the park, you know, after work, because otherwise it makes it sad that a computer can beat us so quickly.

33:29 Yeah. I mean the reality is if you look at high level chess players as well, Right, they themselves play in their own kind of park. Right. They're not even allowed to wear a watch, because you know they might be cheating using any device. That's a good point. Yeah, I guess it's again there's there's always ways to evolve. We how we do it, you know, I'm curious you're thinking about this as as we're like, you know, society we're wrestling with with a lot of these kind of changes in terms of, you know, how we use technology, what role technology plays in different parts of our work lives, you know, and writing is an interesting area. And then obviously around journalism too, it's like do you I'm curious, like how have you spoken with or getting like what are reactions from journalists or like news corps about these ideas? Right? You know, in terms of that if you kind of chat chat with them about like developing this kind of tech that can help in the in the creation process of not at scale, not yet so and even if you go beyond the idea of using technology to do that. Right now, there's a pretty big fight going on between most news corporations and journalists themselves, right, because news corporations are trying to basically use humans to reuse what other humans did. You're seeing companies like old like Gonnet kind of buying up small newspapers, right, and then some of those newspapers they just get rid of all the journalists and borrow content from other newspapers, right, yep, Because again the incentives are to make that happen, but journalists typically unionize, go and strike, fight against

35:00 that, et cetera. Again, understandably, so so when we're talking about and now it's not even going to be that all the efficiency comes from reducing redundancy between humans. Now just this entire group of humans becomes redundant because AI can do their work right, and you only need the actual investigative guys. There's going to be a lot of resistance towards that, right. I'm not even sure that we would get good press if I just kept talking about that part over and over. You asked about it, so I talked about it, but most of the time I talk about reducing the junk, and I try to avoid the part about yeh, and I'm not sure how your profession is going to still be there, of course. Yeah, if it does, then it's probably going to be about ten percent of the size that is now in terms of number of people engaged in it. Again, I love historic parallels, as you notice, right, agriculture In the nineteen twenties and nineteen twenty it's thirty percent of people in the US working in agriculture, and in nineteen thirty it's three percent. Yeah, it totally changed, right, I think we're in a similar kind of decade for anything that involves words as output. Yeah, I mean that's interesting. Yeah, yeah, it's it's and it's a fair question. I mean the part of it too is like we can't shy away from the challenge of the question, right, And so that's like people that put their head in the sand are going to get buried first, you know, and not that and to be negative, but it's just like it's it's we have to be willing to ask the questions, right of like how how might our work change in our outputs? Yeah, it's like and we can imagine a future that the creation of words, like you can do it for fun, but like as a as a job or something

36:32 that it's it's automated you know, in many ways like that. And then it's one of those two like you know, farming is automated. It did, it did change a lot of like like cultural landscapes. But we also still need food, right, like how that happens. So it's like in the same kind of way, like I mean, even they have digital junk also, right, it's like we need we need i mean more than everything good information, right, we need information that we can trust and feel and feel safe with, and so like whether written by a person or a computer. Like on the one hand, like and that level that question, it's like, either way, how do we get to the answer of like, what's what's trustworthy information that can help, you know, disseminate knowledge in a way that we can we can work with. Where there's risk, there's also opportunity. Right, So if the model that is writing it is actually taking facts from a source you can trust, right, And if the model of or the model itself and the data sets it was trained on is at least partially open to you so you can trust that it's doing it well, that is much more trustworthy than anything we have in the ecosystem right now. So we could lament that the current ecosystem, you know, good people are losing their jobs, is very lamentable, right, But that ecosystem is what's producing the junk right now, and so if we can replace it with something that produces a higher signal to noise ratio, that's ultimately good for us. Sort of in the same way as the mechanization of agriculture resulted more food being produced, right, we got more food, but obviously an entire region got ninety percent on the pointment and the big out migration from it and to other regions.

38:02 Right, So I don't know how that works for white collar workers, but I guess we'll see. Yeah, I mean knowledge worker is it's an interesting it's an interesting point of what that's going to be, right, And and it is in you're right, like, and we're talking about writing a lot here too, obviously because we're approaching this from from news media, but like creative industries in general, right, because both visual and video creation like you know, are also in this space as well. Like there's a lot of you know, generative image that's a little more difficult, right, So, so it is progressing, but it's a few years behind in a sense. Yeah, essentially if you use the same method that I described as alarms our train, just a missing thing that doesn't work in video. So video requires a little bit extra work to try to generate something useful. But yeah, yeah, it's only a few years behind probably. Yeah. I think you're right there too. It's in like but even to that point too, like we're seeing the early implementations, like in in mainstream software like Adobe's putting it in through Firefly and and other you know, there's what's it called SOA or sona from open air eye, you know. Yeah, Like I think there's some interesting, interesting things that are that are at play there. So I'm curious too, Like as we think about the h I guess we talked to I guess a lot of but don't think about like the kind of tech challenges that we're facing in terms of as we see these these shifts happen, like how do you approach trying to you know, build something new or break you know, kind of new kind of breakthrough technologies in the space. It's like super rapidly advancing. Uh. And there's again a lot of like you know, social buzz because it's like what it is that we're potentially making or how we're changing conversations around digital clutter, Like how do you think about the

39:36 technical challenges that you're facing as you're putting the other platform syndicating content and then potentially like putting the concierge in place and like having people chat Like what's I guess, what's been the toughest thing to kind of help or not to crack as you're trying to put the tech stack together to make this thing work. Yeah, I think generally speaking, both I and all the people that's gravitated towards me in this project are better at building stuff than we are getting eyeballs to stuff. So generally speaking, if you ask me what are our biggest challenges, I will list ten things, and none of them will be a tech challenge. Organ Yeah, the tech challenges are the easiest thing for us, again just because of the kind of people that the project attracted early on, right, we tend to be tech is the biggest challenges. How do you build a community of people that actually talk to each other. That's something where I'm incompetent and I can't even stay in touch with my best friends, right, and so getting me to build a community that's completely foreign to me.

40:35 So it kind of comes out of the personality of me and the rest of the team. But in general, yeah, that tech landscape is evolving a lot, and that means that I always have to watch what happens, and everybody else has to watch what happens, and we have to constantly try to adjust. And it's a little difficult for some team members because you know, they were something for six months and then that's something that was supposed to be on the main tab and the app has been moved to the fourth tab because three more more important things came out. Yeah, and they're upset, right, and I understand them. Right. They were working on something that was supposed to be a part of the flagship feature, the main flow that the all users go through, and if it's in the fourth tab, then maybe only fifteen percent of users even get there and know what's there. But there's three cooler things that happened just because now the technology allows them. Yeah, it's a good point too, right. It seems like it's the especially like if you're working in a modular development environment, you know, it's like you can't we can't always know as I build this thing when it'll get down downstream and they get out and by the time it gets out, like what new has popped up elsewhere? That would change. That's interesting too, that I mean, like, how do we think about like the as an online platform too, you know, like we've got ways of being able to select topics and emotions even if if I want, like what I'm looking for in stories, Like how do you think about competing with like a CNN or BBC.

42:01 Obviously those are individual publishers, right, and so part of it might be the syndication question, but like, how do you how do you kind of try to position other web as a way of like being in competition but conversation with these others lublishers. Yeah, I'm not trying to compete with them, right. Essentially, I'm trying to stay within the guidlands of fair use. I try to add something they don't have, which has summaries and nutrition labels and better ways to select an order content. Right, and then if somebody wants the original content that they created, I have a link back to CNN or BBC. Yeah. So I'm basically strictly in the aggregator space of let's say, the Google News and Apple News and Flipboard of the world, not the CNNs of the world. Right. But again this is up until March. Yeah, and now I'm gradually getting into a completely different space, which we'll see how that works. Right. Where Again, I still don't want to compete with CNN or BBC, right, especially not with BBC.

42:59 They have endless funding that we will never have right in government, but even within organizations of that caliber, still we want to always partner up with them. We want to even when we have a model that writes really well, we're going to go to Gannett and Alden and McClatchy and all these guys and say, hey, here's this school thing that can save you a lot of time, and it proved the quality of what you guys are producing. It probably doesn't make sense to compete with the guys who are the most trusted names in news. We should try to improve them because that's good for everybody, or just help them and whatever way we can. And it's worth noting that all these companies are losing money crisis the industry. Yeah yeah, yeah, I mean Gannett is probably they're the biggest, the biggest company in the print industry essentially. Right. Their revenue went down from three point four billion dollars four years ago to two point six last year, right, And they're cutting employees, cutting essentially their expenses every single year. But the cuts are not going as fast as the revenue declines, right. And if you look at their market gap right now, it's something like three hundred million on almost three billion of revenue. Right, So basically the market is betting that they go chapter eleven. They say in every quarterly call. They won't, right, But yeah, so they're in a tough situation. But that's three hundred different newspapers, including USA Today, and a lot of people read them and trust

44:31 them. They don't want to go in and compete with them. I want to go in and try to help them. They need the help, yes, and the readers need good information that's refreshing to hear then too, because yeah, it's not a like zero sum game of information, because that's its own challenge, their own problem potentially too. Right of being a singular source of truth, I think is part of the issue that we're discussing around in a philosophical sense. Yeah, yeah, and that in itself I think is a part of Maybe it's the ethos of the profession that generates that to some extent, right, But I haven't seen that many journalists who would like openly say I'm the equivalent of the line cock at McDonald's. Right. All they do is just do the same thing that my neighbors do in the most standardized way possible. No, every single journalist, thanks their Emichelin Starshift, right, they are creating something unique and if you ask them, is your version of the story better than every other version of the same story out there.

45:30 They're obviously going to say yes. Now, the problem is there's more than fifty versions of every single story out there, even within the same set of fact published in the same hour, and so they can't all be right. But it's a part of the ethos of the profession, and I understand why it exists because then they take pride in their work. They're actually trying to produce something really good. Right. But when I look at this as an entire ecosystem, obviously that's a part of the reason why the industry is losing money all the time, right, because you can't have every single restaurant in the world operating as if at some Michelin Star restaurant. They have to kind of pick their lane. And right now, everybody's trying to be the best, and in part because that's that's to our other part before of like following them, the incentive structure of like you capture the most eyeballs slash advertising dollars and then you do I guess, is there like I mean, or do you envision in terms of like the future of the industry, like both either ways or models you've seen of different kinds of incentives, like and like could services platforms like other web in terms of whether it's producing content or like, how we can engage with it and get, you know, a better sense of why I am consuming, presuming in what it means like to shift some of those models, either away from like the chokehold of advertising or something else like you know, do do do we see anything else emerging as potential contenders for that? In theory, yes, but then practice trying to innovate and business models as a very dangerous proposition. And so do I want the industry

47:01 to shift away from advertising? Yes? Do I want to be one of the companies that tries? Not really, because that usually ends badly, right, And so we're trying to innovate and the tech side trying to produce better experiences for our readers. Right, We're not trying to innovate in the business model side, but somebody should. Yeah. Yeah, I just don't think that we want to be it. And the other reality is that not all experiments in business models have been good for the ecosystem at all as well. Right, you can argue that the iTunes experiment basically kill the ability of most musicians to make money, and so I think generally Near did the study on that, the father of the art right, but he's also a musician, and so he did a study on this and basically showing that the curve of how much money musicians make has become much much steeper. Interesting we've been able to buy songs for one cent each separately instead of buying entire albums, and the result is that the number of musicians that can make a living for music is much much smaller than it was even twenty years ago. And so that's a business model innovation. It looked great when it happened because it was a solution to the problem of piracy in some sense, but in reality it actually made everybody's life in that industry worse probably, And so again I believe that we need to try to innovate this. And it would be great if everybody paid for the content they want to pay for, as opposed to being monetized

48:36 in this backhanded way by somebody trying to extract their attention. But I'm not equipped to innovate in this field. Neither is anybody else in the company, I think, so they'll leave that to others. We'll just focus on good content. Yeah. Cool, No, that makes sense. Yeah too. And I appreciate the honest answer too, because it's like, you know, you talk to people like, oh yeah, we could do something else. It's like okay, yeah, I mean, like what could it be? Is the question? You know, that's not but that's really helpful to to kind of think about too, because it's like and part of it as folks think about, like as we're building what the future is from content creation, production, consumption, you know, we have to think about to your point, like what can you be good at as a business, as a as a as a researcher, as a writer, as a as a creator, as as a developer, you know, and then create in that area, right, and like and not trying to necessarily change everything at the same time, because it's like it feels nice to be able to do that, but like also that that's a hard call to be able to do in the first place. I think I would say, just as a kind of wrap up question, if folks are thinking about the wanting to be more mindful of how they consume content, you know, like whether it's like practices that you have in other way or other things that you've seen in terms of helping us have a better diet, media diet and not consume so much junk, Like what are some strategies that you you share like or you thought about you're built into the platform for like how to be more effective at like being smarter about my consumption of media, or you know, making sure that I'm knowing what it is that I'm consuming. And why let me start at a higher level, because the platform only covers a part of what you could do. But if

50:07 you go to a higher level, if you want to consume good stuff most of the time, then you should actually plan what you're going to consume. I think most people don't actually if you ask them, even how much time you're spending right now on Instagram versus reading books, most people can't answer that question. But I think you should have a plan of how many hours per week are you going to spend on Instagram? How many hours per week are you going to spend reading books? The minute you come up with that plan, even if you can't stick to it most of the time, it's still going to be better than if you had never had the plan. We see the same thing with regular dieting as well. Right the moment people start taking photos of their food, they start eating better. They don't even need to start planning their diet. Just taking photos is typically enough, but if they also plan their diet, it becomes even better. So that's my first piece of advice to everybody. Just try to plan this thing. And then once you notice how much time you're spending on recent versus that are trying to extract your attention, chances are you're going to want to change that. Now, how much up to you? Right? Some people like their Instagram because they're already hooked. It's okay, But the question is how much right? Even drugs are you know, some of them are okay some of the time they're not okay, multiple times per day for very long time, being strung out right, Yes, sorry, I'm not at what they're advocating for drugs anyone.

51:27 But let's say alcohol, Okay, one drink per night seems to actually extend your life even though it's clearly unhealthy. Why because I guess moderations okay, right, but seven drinks three times a day probably not even that's great? Yeah, So basically, try to plan what you think is the right level of consumption for you for every particular drug, and information that produces dopamine is a drug, just like chemicals that produce dopamine. That's a great points and something that I'm curious to hear what listener's viewers think about there. It's like, like, have you ever planned your media consumption? Because I have not been, Like, let me, let me make sure I only consume fifteen minutes of media news today or something whatever it is, like, but that's that's a really great point actually to be aware of, like what it is that you're choosing to expose yourself to. And I think the most ironic thing that happened to me when when I got small kids, right, is I start planning like, Okay, she's only allowed to watch cartoons for fifteen minutes in the morning and fifteen minutes in the evening. And then I noticed, okay, but my wife is looking at Instagram for the past hour.

52:29 You're like, wait, yeah, I'm not supposed to say anything. Yeah, yeah, exactly. And I'm thinking with different standards. Somebody is planning it for the kids, but for us adults, nobody is planning it. We're kind of waning it, right, And so how about we start planning for ourselves too. Yeah, that's a great idea, right, we need a media planner to help us out here. You do awesome? Cool, Well, Alex Like this has been great to chat with you. I appreciate you taking the time out and excited you know about the work, about the work that you're doing and raising I think a ton of really important questions for media consumption and how we can be smarter about that. How do we like tack all the challenges facing journalism and media creation too? You know, I think it's a it's an interesting challenge space that you've doven into and so I'm excited for folks to check out the site that they haven't already and to kind of share some thoughts on this idea of how can we be smarter about media consumption? Sounds good. It's been great, It's awesome, Thank you much.

53:21 And it was easy.