Instagram’s Founder On Why All Social Media Looks The Same — With Kevin Systrom

Kevin Systrom is the co-founder of Instagram and co-founder of Artifact, a news app that uses AI to determine your preferences and show stories you might be interested in. Systrom joins Big Technology Podcast to discuss the implications of all social media — Facebook, Instagram, TikTok, YouTube, Twitter — starting to look like each other. We speak about how the rise of AI recommendation feeds impacts the future of competition among these apps, creativity upon them, and distribution for people looking to get a message across. Tune in for a fun, in-depth discussion about social media's future in a new era. --- Enjoying Big Technology Podcast? Please rate us five stars ⭐⭐⭐⭐⭐ in your podcast app of choice. For weekly updates on the show, sign up for the pod newsletter on LinkedIn: https://www.linkedin.com/newsletters/6901970121829801984/ Questions? Feedback? Write to: [email protected] Learn more about your ad choices. Visit megaphone.fm/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Alex Kantrowitz?

  LinkedIn Presents.

• 0:14Alex Kantrowitz?

  Welcome to Big Technology Podcast, a show for cool-headed, nuanced conversation of the tech world and beyond. Kevin Systrom is our guest today. He's the founder of Instagram, and he's currently building a news app called Artifact, which uses AI to determine your preferences, and then it shows you stories it thinks you might be interested in. Systrom and I spoke while we were both in town in Austin, when we were speaking at South by Southwest, and I was super eager to hear his perspective on the implications of the fact that all social media, Facebook and Instagram, TikTok and YouTube, and even Twitter, are starting to look like each other. Systrom should know better than anyone else what this means for the future of competition among these apps, what it means for creativity upon them, and of course, for the future of everyone's ability to find distribution

• 0:59Alex Kantrowitz?

  online. I think you're really going to enjoy hearing from Systrom. I know that I walked away from our conversation with a much deeper understanding of the state of play in social media today, and I hope you will too. My conversation with Kevin Systrom, coming up right after this. This episode is brought to you by Genesis. What does it actually take to put Agentic AI to work across an entire enterprise? I recently spoke with Genesis Chairman and CEO Tony Bates about why orchestration is emerging as a competitive advantage in customer experience, and what companies need to get right in the AI era. Then, I sat down with Adam Mitchell, Head of Enterprise Business Solutions at Voya Financial, to go inside

• 1:41Alex Kantrowitz?

  a large-scale Agentic CX transformation, including the business decisions, trade-offs, and lessons along the way. You can watch both conversations now on my YouTube channel today. It's never been more challenging to get frontier compute. How do you know where to look, who to trust, or how much to pay? Akash is an open cloud that provides easy access, flexibility, and peace of mind. That's how companies like Razer were able to cut their inference cost by 15 times. Visit akash.network/alex for a free consultation. That's akash.network/alex for a free consultation.

• 2:20Alex Kantrowitz?

  Hey Kevin, welcome to the show.

• 2:21Speaker 01

  Thank you very much.

• 2:22Alex Kantrowitz?

  Excited to be here. Yeah, it's great to see you in person. We don't get to do these in person too often.

• 2:25Speaker 01

  No.

• 2:26Alex Kantrowitz?

  I don't want to get too far ahead, so let's just start with Artifact. You know, just do it quickly, but like, what is it? And what was the inspiration here?

• 2:35Speaker 01

  It's a hyper personalized newsfeed. The idea is that you should be able to open up our app and get exactly the news and written content that you want immediately, with no pain, no effort.

• 2:51Speaker 01

  And that sounds relatively easy, or you might say, "Well, I already do that. I open up Twitter and I get all the content I want." And I would challenge you to use Artifact for a couple of weeks and see if that's actually true. Typically, what people report is they open up Artifact and they select some interests. So they'll say "architecture," they'll say "recipes," they'll say "technology." And within about a couple of weeks of usage, you start getting served very specific stories that are along your interests. So for instance, I love Japanese modern architecture. I love Mexican cooking. I also particularly like following along with, you know, everything that's happening at Meta, not only because I'm a shareholder, but because I used to work there. What's happening with Instagram, Instagram product launches,

• 3:36Speaker 01

  anything in the news space. And it figures that out, and my newsfeed is that. Now, you might say, "Okay, I use Twitter or I use Facebook for that now." But my experience, and the reason why we started the company, was because if you open up any of these social platforms, you very quickly realize what you're being served. You're being served because someone else decided to post about it. And I think that's wrong in a bunch of ways. One, people are incentivized to post when they are excited or angry about something. So it self-selects for content that is naturally a bit more controversial. Not necessarily interesting and not necessarily relevant to you.

• 4:20Alex Kantrowitz?

  When it sparks an emotion.

• 4:21Speaker 01

  Yeah, so what we decided was we were going to break that chain. And instead of articles or news being served to you because someone else decided to post about it. We just find it because it was relevant to you. So the reason why this is possible now is because machine learning took a turn in. You know, twenty seventeen, twenty eighteen, I'll say. Um, a bunch of things were invented, especially around text. Uh, that allowed you to analyze text in a way that you couldn't before. And it allowed us to get to a deeper meaning of an article or or something written. And form a profile on the user that allows us to serve them better. Um, and in our prototype of this, you know, it took about a year and a half to get to where we are.

• 5:05Speaker 01

  Um, it was really surprising and really fun and really differentiated. So, um, so that's what artifact is. It's a it's a hyper personalized newsfeed.

• 5:13Alex Kantrowitz?

  So I I'm using it and I like it so far. And one thing I'm thinking about is I look at artifact. And then I look at TikTok and I look at the new Spotify and I look at Instagram and I look at YouTube and Twitter to some extent. And every single what used to be social media or media or online media, whatever you want to call it, every platform like this looks a lot like TikTok. I wonder what you think about this homogeneity that we're starting to see because like now you're part of it, right? And of course, it's a different form of content than TikTok, but.

• 5:45Alex Kantrowitz?

  One of my concerns is that we start to lose the creative parts of the internet when everything starts to use AI to serve you content that you might be interested in. And there are all these for you feeds. What do you think about that?

• 5:55Speaker 01

  Well, I challenge the premise, which is that everything's converging. Um, or rather that that's a bad thing. So remember when Facebook launched the newsfeed? When was that? Like two thousand and I don't know, five, six, something like that.

• 6:08Alex Kantrowitz?

  You're in a better position than I.

• 6:10Speaker 01

  No, I don't really. I just remember the protests down in, uh, yeah, I remember the.

• 6:14Alex Kantrowitz?

  I was part of those. I was in my dorm room. I mean, I wasn't like holding a sign in front of Facebook headquarters.

• 6:19Speaker 01

  Yeah.

• 6:19Alex Kantrowitz?

  I was in one of those like, you know, thirty thousand strong against the newsfeed.

• 6:22Speaker 01

  Yeah.

• 6:23Alex Kantrowitz?

  Back then in social media days, seemed like a lot of people.

• 6:25Speaker 01

  But, um, remember that a newsfeed was a a fairly new thing for products back then. Like no one, no one had a feed, not really. Um, we all take it for granted now, but you then saw. LinkedIn, you then saw Twitter, you saw all these services adopt effectively a feed. I mean Instagram, Twitter, et cetera, it wouldn't exist if the feed weren't the dominant way to serve information at the time. Um, and it just so turns out you could use that to serve people very efficiently. Now, what I would argue is at that time, the best way to figure out what was relevant to you was to let you choose.

• 7:05Speaker 01

  So you would follow, um, you would friend people and your, your social network became your filter for relevant content. If I follow you, you post something, I see it. These networks grew to be slightly too large for that to be manageable. I'll, I'll give an example at, um, Instagram. If we, if we simply just sorted it chronologically, sorted your feed chronologically. Uh, the people that posted the most would get the most attention.

• 7:35Alex Kantrowitz?

  Yeah.

• 7:35Speaker 01

  And that tended not to be the best for people. Like people would self-report seeing too much of one person, or they would see, self-report missing other people.

• 7:47Alex Kantrowitz?

  And it's pretty stark, like you even look at like the, now Twitter has the for you and the following feed side by side. For you, I'm getting actually interesting tweets.

• 7:54Speaker 01

  Yeah.

• 7:54Alex Kantrowitz?

  Following, I'm getting like a thousand tweets from Bloomberg.

• 7:57Speaker 01

  No, it's a mess.

• 7:58Alex Kantrowitz?

  Sorry Bloomberg, but enough with the tweeting.

• 8:00Speaker 01

  Yeah, so, so there's a volume issue, there's a quality issue, there's all sorts of, my point was more, the feed was a very good way of serving content when the follow and friend graph were fairly sparse. When people hadn't figured out how to gain getting followers and distribution. But in general, the system is suboptimal if what you do is you just simply let people with large followings be the single source of information in your feed, which is what happens when you go chronological. So anyway, someone smart figured out, we could use machine learning to take that content that everyone's posting, sift through it and drop anything that's irrelevant and focus on the things that you'd be most excited about.

• 8:41Speaker 01

  That worked fairly well. Facebook became worth many billions of dollars because of it. But that also had a problem in that we kind of forgot that what we were sorting was stuff that people posted. I'm going to come back to this point time and time again. Because there was enough of that stuff, it was exciting, but it turns out that like, that's fairly limiting. Why is it that the only articles that I can consume come from a handful of people who decided to post about them? I mean, there are, you know, many cases, tens of thousands of articles from high quality publishers, published every single day, at least in English. It's very hard to find all, like, the good stuff in all of those.

• 9:20Speaker 01

  So what I was gonna say on, on everything converging to a for you feed is actually, this is just the next version of a feed. This is us figuring out, there's no reason why we should just serve you what other people decided to post. We should just go out and find things for you. One of the beautiful things about TikTok is that literally anyone can become famous.

• 9:38Alex Kantrowitz?

  Okay, I have questions about that, and I'm gonna definitely ask those, so.

• 9:41Speaker 01

  Yeah, but anyone can become famous, you can, it is the most democratic distribution system because it's all about the merit of the content, not whether or not that person had built up a huge following beforehand.

• 9:54Alex Kantrowitz?

  Right, right.

• 9:54Speaker 01

  And I think that's really special, and I think what you're seeing is every service deciding, hey, wait, that model works, the content-based model, does this content work or not? Rather than, did someone influential post about this?

• 10:06Alex Kantrowitz?

  By the way, when I.

• 10:07Speaker 01

  And that's important.

• 10:08Alex Kantrowitz?

  And I'm hearing you talk, it does seem like, we're gonna get to some of these questions about the feed, but it does seem like you're directly positioning your new product against Facebook, which is still that old model of what people share.

• 10:19Speaker 01

  I mean, it's certainly good for.

• 10:22Alex Kantrowitz?

  You're allowed to.

• 10:23Speaker 01

  That's certainly good for podcast ratings, but like.

• 10:25Alex Kantrowitz?

  But that's why I'm asking you about it.

• 10:26Speaker 01

  I'll push you on this, which is, um, I think you said yourself, Facebook and Twitter have figured this out. It's why when you log on to Twitter now, you see so much unconnected content. I mean, I had, some team ran a test in Instagram the other week, I don't know. I logged on to Instagram and every fourth. Image is some celebrity I don't care about. It's like, do you want to follow this celebrity? Do you want to follow this? Like some partnerships person decided we had to go get a bunch of followers for for celebrities or something. And I think a big part of that is the realization that who you followed initially on a product is not who you want to follow now. Fun story, okay? I have a friend who works in banking and he's an investor.

• 11:08Speaker 01

  And he signed up for the product. He said, okay, I'm going to use this for stocks and investing. And I'm going to, I'm going to use this for stock tips, basically. And in realization, in reality, it's what this person likes is amazing architecture, great restaurant openings, San Francisco drama and politics. None of the stated preferences match the revealed preferences. And I think what I'm realizing about social media is that there's this huge divide between stated and revealed preferences. And I think Facebook, Twitter, et cetera, have all realized that to be true. So now, as part of your feed experience, you're seeing that more and more. So everyone's figuring this out.

• 11:52Speaker 01

  So rather than positioning against Facebook, I'd say we're all riding the same wave. It's just who can capture it first.

• 11:58Alex Kantrowitz?

  Okay, good to have you talk that through. Let me ask you, though, because when you talk about the stated preference, right? It wasn't just one stated preference. It wasn't just follow your friends, right? There were different ways we would build our follow graphs. Facebook and Facebook was basically friends and family centric. Instagram, a little bit of friends and family, but also interests and people you want to follow. Twitter, interests, right? So, and I mean, to move it all toward AI, I wonder, you know, because, you know, are we going to go from having those distinct platforms with their distinct type of content that you follow? Do all platforms that are machine learning based, starting to recommend the same stuff to people? And in which case, what's the differentiator there?

• 12:39Speaker 01

  It might. I mean, there's a world, like if you look at, if you look at the history of tech, like social media in the United States, these platforms tend to be single use, like. Twitter is for text, Instagram is for images, TikToks for funny videos, YouTube's for videos. You don't see a lot of convergence and often when you do, it doesn't work, right? Like everyone tries to be someone else and it only kinda works. Whereas in Asia, I think you see a lot of these super apps, specifically in China. The super apps that do everything, they do banking, they do chat, they do social media. And there's a very real possibility that using artificial intelligence, some or one of,

• 13:22Speaker 01

  generally one of these apps or companies will walk away with kind of the everything app.

• 13:29Speaker 01

  Mostly because I would argue the the benefit you get of having a large user base, of having the best artificial intelligence for recommendations is enormous. It's the same as if, you know, like Instagram is so great because you get on and literally every celebrity and company exists and you can see what they're posting. The network effects exists there, but there's actually a network effect in data as well. Which is to say, if you have enough data, your recommendations are so much better than the next company that you could never catch up. And it's possible. I, I, I don't. History would not say that typically happens in the United States. But it's possible.

• 14:13Alex Kantrowitz?

  It's interesting that you're even open to the possibility. And one of the things I definitely wanted to ask you was TikTok started this way. Your company is, or your former company, Instagram, still consider it your company?

• 14:24Speaker 01

  Instagram? Yeah, sure, sure.

• 14:26Alex Kantrowitz?

  I mean, they came late to the game and obviously they have the machine learning and the user base of Facebook, but they're still not fully committed to that TikTok model. It seems like they're gonna go there. But if they give TikTok this large head start, how are they gonna compete? I mean, talking about the way that you talked about data and, you know, having this advantage that compounds. Instagram seems like, you know, listening to you, that it might be in some trouble.

• 14:53Speaker 01

  People forget that TikTok didn't come out of nowhere. Musically existed. I mean, Musically was fairly popular with the younger crowd in the United States for a while. And when we looked at them, I met with them. I think I was in Shanghai for a board meeting for a different company. And I went into the office and Musically's office. There were probably like twenty five kids who didn't look like a day over the age of eighteen. All in a room hacking away on computers, building this amazing product where, you know, people would effectively just post short videos with music in the background, right?

• 15:29Speaker 01

  Everyone kind of wrote them off.

• 15:30Alex Kantrowitz?

  Yeah, I just, I mean, I remember like being told by, we, we met with Matt Honan, who was the bureau chief at Buzzfeed. He's like, look into Musically. I wrote it off. I mean, I feel like I should have been more curious about it. It was easy to discount, but sorry, go ahead.

• 15:43Speaker 01

  No, you had the right.

• 15:46Speaker 01

  You were right to write them off.

• 15:49Speaker 01

  Because it wasn't working and they had to sell. Now, could we have predicted that one of the world's leaders in AI would spot an opportunity and say, hmm, if we buy this thing and we take all we've learned on all of our other products using machine learning and just layer it on top of Musically, we can create Doyen and TikTok, Doyen being the Chinese version of TikTok. Wow, what a bet, right? And did that work? Absolutely. So what they were able to do is basically use the initial enormous amount of engagement that had been bootstrapped on Musically to then layer machine learning on and then run away with it.

• 16:32Speaker 01

  The reason I mention this is because Reels is pretty good. I mean, a lot of people knock it as kind of like a, you know, there's a wannabe TikTok or whatever, but it's pretty good.

• 16:42Alex Kantrowitz?

  And getting better.

• 16:43Speaker 01

  And it's getting better. And why is it getting better?

• 16:46Alex Kantrowitz?

  More data.

• 16:46Speaker 01

  More data. All I, you said two point something billion. I have lost track of how many users Instagram has.

• 16:51Alex Kantrowitz?

  Two point three billion.

• 16:52Speaker 01

  Like lots of people using it every single day. If you can just hang on long enough and collect enough data, you can go from like. Remember when Apple Maps launched, everyone was like, oh, this is terrible. Like,

• 17:04Alex Kantrowitz?

  Yeah.

• 17:04Speaker 01

  It's pretty good now. Like you just you refine things and things aren't great overnight. Um, but you can kind of, you can get there. I mean, Android for the longest time lagged behind iOS. And now, like, you talk to people and it's unclear. There's an, maybe there's some difference, but like, there's, people report being just as happy on both platforms. I think those tend to go away over time as long as the company that's trying to attack has enough data or has enough users. And I like.

• 17:34Alex Kantrowitz?

  When you were, sorry, go ahead.

• 17:35Speaker 01

  No, that's it.

• 17:36Alex Kantrowitz?

  When you were on Instagram, did you try to acquire Musically?

• 17:38Speaker 01

  Uh, I did not. Um.

• 17:40Alex Kantrowitz?

  Mark.

• 17:40Speaker 01

  We were excited about them, but there was no like, there was no overture that I remember.

• 17:45Alex Kantrowitz?

  Was that a mistake?

• 17:47Speaker 01

  Um, no, because I don't think, I mean, listen. It's easy to, you know, like, what, what is it called decisioning? When you like judge, judge a decision in the past based on information you didn't have at the time, like no one knew ByteDance was going to come in and layer what they had on on top of it and run away with it. Um. But yes, I mean, like, if Facebook or Instagram had acquired Musically at the time, TikTok would not exist. And that is net, I think, positive for all these other companies that are now competing with TikTok. But could if anyone, could anyone have predicted that would happen? Absolutely not.

• 18:24Alex Kantrowitz?

  I just want to ask you one more question about this quickly. The United States is much more cautious now in terms of approving mergers and acquisitions in the US. Do you think it's competitive, uh, competitively an issue that they seem to be, the FTC in particular seems to be interested in, and the Justice Department, interested in blocking more mergers of small companies with bigger companies? Does that give an edge to Chinese companies who might have less of a blocker? It's kind of interesting for you because you are now a startup entrepreneur, but you've also sold a company to Facebook, so.

• 18:58Speaker 01

  Yeah, but I'm also a startup entrepreneur, probably is like the least likely to join a large company at this point, right?

• 19:05Alex Kantrowitz?

  Been there, done that?

• 19:06Speaker 01

  Yeah. Yeah, had some experiences. Um.

• 19:12Speaker 01

  A couple of things on this. One is, I do wish that there were some more clear guidelines stated a priori about what types of transactions would be okay and what aren't. It feels a little bit like you're playing roulette right now when you try to acquire a company. Like, I'm sure Facebook internally is just like, we literally can't acquire companies. Right. I mean, they tried to acquire, what, like, some VR gaming thing? I can't even remember the name of the company. Um, and these things effectively get blocked.

• 19:45Speaker 01

  What is, what are the principles you can use as an operator, whether you're Facebook, Meta, whatever, Twitter, to know what you can do and what you can't do? Because it doesn't seem right that a company just can't acquire other companies. That seems wrong. But on the China part in particular, do you think there's a competitive disadvantage there?

• 20:06Speaker 01

  I don't know. Uh, I'm not sure. Okay.

• 20:11Speaker 01

  If, if Facebook or Instagram had tried to acquire Musically, that probably would have gone through.

• 20:19Speaker 01

  I don't know. Uh, I mean, I'm watching the, you know, the Figma Adobe thing is super interesting to watch. Yeah. Um, when they announced that, I thought to myself, I said, like, good luck, right? Yeah. Everyone acted like it would be fine, and here we are, how many months later? Um, we'll see. But I, I think there's a balance here, which is to say, you can't cut off all acquisitions, because honestly, the amount of investment and innovation behind venture capital, like, from venture capital, comes because people believe there can be exits. If you decide that the only exits you can have are going public, there's, like, that doesn't make the system work, right?

• 21:00Speaker 01

  That takes off like a very important part of the feedback in the system. Um, and I think that can be ruinous. Um, now, uh, everyone is losing their deposits in banks. Can that be more ruinous? Probably. So. Yeah, exactly. But there are a lot of forces and headwinds against US startup culture right now that probably don't exist outside and in China. So is there an advantage to being an outside player? Possibly.

• 21:27Speaker 01

  But at the same time, I don't know if if you're if you're ByteDance and you're trying to do TikTok in the United States, I mean, literally right now, it's existential. Can we operate in one of the world's largest ad markets with one of the highest average revenues per user?

• 21:41Alex Kantrowitz?

  Should they be allowed to?

• 21:42Speaker 01

  That's not for me to figure out.

• 21:44Alex Kantrowitz?

  Okay, but what do you think, though? It's not you're not gonna say it on the show and then it will happen, but I'm curious what you think.

• 21:50Speaker 01

  I think it is completely reasonable to use the same logic the Chinese use to not letting American apps operate in China with without impunity, the other way around, which is to say that, especially by the way, if that app is one of the foremost ways people consume media and information. I worry actually very little about if someone's looking at what funny videos I watch, like very, very little. I I I don't care where that dude is.

• 22:20Alex Kantrowitz?

  It's it's more the ability to manipulate what funny videos you watch.

• 22:24Speaker 01

  A hundred percent, and I'm not saying that that is happening. But I think the argument typically is Snowden, et cetera, not like, is this actively happening, but is there a door that allows someone to do it if they so choose? Because the context now, everyone's fine, everything's going well. But in the future, I don't know, like, is there a world where another world power has a very large app inside of another large inside of a, you know, inside of a country that they deem competitive? And and someone could control what you consume. You know, like, throwing an election on Facebook is hard. You gotta you gotta set up all these fake accounts. You gotta,

• 23:07Speaker 01

  you you gotta like form groups and then change the topic of the group. You've got to hide. But like, if you just control what people consume, I I see like, I'm not saying this is happening, but don't you think that someone should pay attention to that threat? I think so.

• 23:21Alex Kantrowitz?

  Most definitely. Yeah, no, I think that's spot on, and I think you're identifying exactly the problem here.

• 23:26Speaker 01

  A hundred percent. I think it would be illogical to not pay attention to the problem. Now, does that mean that I think that we should shut down TikTok? No. But like, I think there are some real conversations to be had with the leaders of the company to figure out how to make it work. And honestly, TikTok should want to make it work, too, because they're enormously successful in the United States and. So there should be some outcome. I don't think it's intractable.

• 23:52Alex Kantrowitz?

  Yeah. So I want to talk to you now about something that you mentioned, which is that this type of feed, the AI feed is the most democratic possible feed that you can have. I thought about this before we spoke and I wondered if this is really the case. Here's what I'm thinking, right? If you're in a follow graph, right? That means average users, I'm just spitballing here. You have the actual data behind it, but average users probably have a better chance of getting their posts seen than if they're in the one AI feed where you only have a few videos or articles coming to the top. So I'm kind of curious like what you think the distribution of content is when it comes to this. Like to me, it would seem that yes, anyone can go viral, but it's just the content that

• 24:37Alex Kantrowitz?

  got seen instead of this long tail of content that is seen, that is created by lots of people, becomes this highly concentrated bit of content and the algorithm just picks from the best. Now I'm curious what you think about about that and what has, what actually has more equal distribution.

• 24:54Speaker 01

  It's funny. You started asking this question. I was like, I totally disagree. I'm gonna fight you on this. And then I was like, actually, I think you have a point. So I think you're both right and wrong and I will both fight you and agree with you.

• 25:05Alex Kantrowitz?

  All right.

• 25:05Speaker 01

  So here's how I agree with you. It is true that generally speaking, you're gonna have the Pareto distribution. You're gonna have, you know, 80% of views are gonna be on 20% of the content. By the way, that is also true on Instagram. That is also true on Facebook. I would claim that generally speaking, the long tail is dead in social media. It's very, very difficult to get views on unpopular content. Okay. So the counterfactual without AI is, I think, just as bad, which is what I challenge you on, which is like generally speaking, I'm not sure your Twitter experience is the long tail. Now.

• 25:42Alex Kantrowitz?

  I mean, I'm not sure we want the democratic version that I talked about, which is the follow model.

• 25:46Speaker 01

  I mean, yeah. So here's, here's what I want to say.

• 25:51Speaker 01

  I my my point in saying it's more democratic is that uh generally this I'm gonna summarize uh uh I'm gonna I'm gonna very overly simplify how TikTok works, okay? They basically take content without much information, they preflight it to a small number of people and then they basically it's a very small lab test on that content. Yeah. They have enough users that they can collect enough of these lab tests to then decide who they wanna if they wanna show that content to more people. In most cases, it's a dud, but in some cases it can be good and they can give it to an extra thousand people and try a little bit more. And then they collect basically a larger lab experiment on that content. And then they do that again and then again until they are fairly confident who this content's going to resonate with.

• 26:37Speaker 01

  I think that is more democratic than gaming your way to more engagement by either buying followers or just being famous or like the other part is I I don't love the idea that people with lots of natural distribution, meaning they have lots of followers, can just decide to tweet about, I don't know, the efficacy of masks or something. And now their word becomes, you know, uh the state the the record. And that to me feels broken. Um and instead I'd rather a world where we can engage with content more on this experimental basis. So for instance, um there's this whole world of what are called bridging algorithms.

• 27:22Speaker 01

  And the idea is that you you put content out there and you know, let's take sides of a a political spectrum. You can find out who's a Democrat, who's a Republican. And you can see what content tends to resonate with both sides rather than just resonate with one side or the other, and you can promote that content. That is much easier to do in an algorithmic world than it is to do in a follower, because I choose to follow, I don't know, Joe Rogan, or I choose to follow some super liberal. I'm trying to like come up. I don't use Twitter that much personally, so um.

• 27:57Speaker 01

  Thinking through this, I think the world in which you can use algorithms to dictate what gets distributed is much more powerful and fair, potentially, as long as the people in charge of the algorithm have the right intentions, the right objectives, et cetera.

• 28:14Speaker 01

  And that's a topic, I think, for the other half. But anyway, that's my long-winded way of saying I think it is more democratic, and I think that's a good thing.

• 28:22Alex Kantrowitz?

  Okay. Instagram founder Kevin Systrom is here with us. He's also the co-founder of Artifact. You can find it at artifact.news. It's available to everyone on the App Store. I just downloaded it. I'm enjoying it. Maybe you will too. On the other side of this break, we're going to talk a little bit more about content and what actually gets promoted by the AI. And then, actually, we're going to go deeper into the machine learning side of things, which I think you're going to find interesting. Back right after this. This episode is brought to you by Avpoint. Everyone's racing to roll out AI right now. Co-pilots, chatbots, agents doing real work. But here's the part nobody loves talking about. All that AI runs on your data, and most teams have no single way to see it, secure it,

• 29:02Alex Kantrowitz?

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• 29:46Alex Kantrowitz?

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• 30:52Alex Kantrowitz?

  And we're back here on Big Technology Podcast with Kevin Systrom, founder of Instagram. He's also got a new app. You might have heard about it, especially if you listened to the first half of the show. It's called Artifact. You can find it artifact.news. So I'm actually curious now about the type of content. You talked about stated preferences and revealed preferences. Stated what you want, revealed what you say you want, revealed what you actually want. And I'm wondering what, you know, it's kind of interesting because like where, we like to think that we're all interested in like high minded news. And when I went through like the signup flows, like you're interested in stocks and you're interested in stocks and technology and all that. But, but then like there was also like dating and romance. And I'm like, oh yeah, I'm definitely clicking that. And I'm fairly certain that

• 31:36Alex Kantrowitz?

  like, my feed is going to be all like, you know, kind of soap opera stuff. And, you know, I also think like, when Instagram started, you know, especially looking at like the way that you you framed it when you began, it was like literally like, here's a way to take your photos and then make them look a little bit better because your camera isn't as great as it could be on your phone. And it was awesome for that. But as it evolved, you know, a lot of it became about bodies and TikTok was, you know, maybe started with lip syncing, but a lot of it became about bodies and, you know, and I'm wondering where you think people's revealed preferences are going to go with Artifact and whether we're going to end up in a place that like, again, goes to like the, I mean, maybe, you know,

• 32:19Alex Kantrowitz?

  it's okay to give people what they want, but like the lurid versus the thoughtful stories that, you know, I don't know, might make us a more informed society.

• 32:29Speaker 01

  I think it doesn't have to be either or.

• 32:31Alex Kantrowitz?

  Okay.

• 32:31Speaker 01

  Like, let's get out of news for a second. Just, let's go to Netflix or something. Yes, there are amazing documentaries and I've heard this. I don't know how true it is, but I've heard this internally that. People love adding to their watch later list. What is it called? Is it like the watch list or like? I think it's I don't really use it that often, but I know there's a plus button. Yeah, people love adding like super heavy documentaries to it and. These like thoughtful movies that win all these awards at Sundance and. Um, and then when they log on, would they actually watch? It's like. Okay, I'm gonna watch reruns of X, Y, or Z and. To me, um.

• 33:15Speaker 01

  That's okay. Like, a lot of people often ask, shouldn't we force people to read more intellectual stuff? Shouldn't we? Make these, this content. Higher quality. It's like, okay, sure, you can do that, but. At a certain point, how much are we getting in the way of what people just wanna do? And you were talking about bodies. I laugh only because, you know, some of my friends have signed up for Artifact and they do get really good tech news from it and they do get. Um, like they'll be like, I don't know, a healthcare investor and they get great news about new healthcare startups. Um, but also they really like Daily Mail.

• 33:57Speaker 01

  And they like the celebrity section and like maybe they're really interested in following along with Kanye drama or something and. One of the things I think that Artifact does better than anything else right now is it doesn't judge. Like you can both be a great investor and also be really interested in, I don't know, a specific celebrity or. Or musician. It might make you a better investor. Maybe, right? But the way I look at this is. People don't fit the archetypes that we all have in our heads. They fit other archetypes that exist in reality and I think to try to work against that. Does people a disservice in the long run? Now, there are certain lines I don't want to cross as a company.

• 34:38Speaker 01

  We try very hard not to carry publishers, when I say carry, distribute in the, in the algorithm. Uh, using the algorithm, publishers that have a history of bad behavior or misinformation. Um, so we work very hard on drawing the line somewhere with quality that means what we're building is responsible. Cause I truly believe AI is like super powering what you would do as a company anyway. You need to be very, very careful what you put in the machine. Um, and we're seeing some of that with these chatbots, like it takes an enormous amount of time and effort to get them to do safe things only.

• 35:20Speaker 01

  Um, and I, I see that as a fundamental challenge, but I don't think that, um, we should place a judgment on entertainment. Like, I think it's okay to be entertained by a wide, like a very wide spectrum of topics and, and artifact clearly does that. Like if you want funny dating advice alongside your super intellectual, you know, Atlantic article on, on education, go for it. I think that's great. And the nice thing is machine learning doesn't, um, it doesn't judge. You can be that person. I think that's special.

• 35:54Alex Kantrowitz?

  Yeah, but it also can have compounding effects where it starts, you know, it clouds out the other stuff.

• 35:59Speaker 01

  A hundred percent.

• 36:00Alex Kantrowitz?

  Feeding you just the dating stuff, maybe.

• 36:02Speaker 01

  Can I address that?

• 36:03Alex Kantrowitz?

  Yeah.

• 36:03Speaker 01

  Cause I think it's super interesting. You want to talk a little bit about the AI.

• 36:06Alex Kantrowitz?

  Yeah.

• 36:07Speaker 01

  The first question I get when I tell people the idea, you know, when we pre-launch, I said, this is what we're doing. Or even, you know, here at South by Southwest, I'm walking around, uh, and people say, oh, you're doing this new thing. But doesn't it have this problem with filter models? The idea that you only read articles that support your point of view confirmation bias. Um, and that puts you in this loop that basically it makes you only see the stuff you want to see.

• 36:38Speaker 01

  Wouldn't it be healthy to see other stuff, other points of view? And this isn't just politics, this is advice on parenting, or schooling, or, or exercise, or nutrition. And I think the answer is yes. So, you know, people who study machine learning, this will be not that interesting, but I found it really interesting that generally speaking, the optimal strategy with any machine learning system is some portion of the time, most of the time, to do what you think the user's gonna want. And then you set aside some smaller portion of time to kind of randomize the behavior. Because that random exploration turns out allows you to discover things you wouldn't have known otherwise.

• 37:20Speaker 01

  It's also a very effective way to not what we call tunnel vision. So if you're reading a ton on a specific, you know, uh, I don't know, issue in San Francisco politics, it's important that we explore potentially other publishers or, or other points of view, not just the one that you're reading about. And that exploration that I think turns out to be like all of the value in these systems, because it's easy to serve people what they want. It's a lot harder to discover the things that will be helpful in the margins.

• 37:53Alex Kantrowitz?

  And it's something so thrilling when you're like on a TikTok, for instance, and you just kind of die, you randomly get served up that test part of some community that you didn't know existed, and you just dive into it, and that's what makes the app, I think you're right, it's what makes the app so thrilling. So I just want to ask one follow-up about the bodies on Instagram, because I feel like you're here and we should talk about it. I mean, the, the biggest complaint that people have had, I think about Facebook or Instagram that I've heard is that it harms, you know, teens' mental health and puts these unrealistic standards of beauty in front of them. Jonathan Haidt has this, um, you know, new piece out talking about how like you can definitively track the decline in teens' mental health with social media. I mean, looking back, I'm curious, A, like what you think about it, and B, any regrets or anything you would have done differently?

• 38:37Speaker 01

  I spend an enormous amount of time internally working.

• 38:42Speaker 01

  On specifically these issues. Trying to figure out what resources we could surface within the app when you were searching for a specific topic. Like we had all these early on tags around whether it was self harm or eating disorders or mental health issues. And people would do searches on them to try to find content and then people would form these. These accounts to talk about this. This type of these types of issues. And the question is, what would you do about it? You know, in some cases, uh, we would. Try to pop up, you know, resources, whether it was suicide hotline or eating disorder information. We would try to take down self harm accounts and then there was. It's interesting, there's always this, um.

• 39:26Speaker 01

  There's a lot of, a lot of information that backs up the idea that if you simply take all of it down. People can't find their communities and then they can't find help. So there's always this balance. But we worked a lot on it internally. It wasn't like a thing we kind of thought about once a year. It was like an ever present issue. I wouldn't say we solved it, obviously, because clearly the data supports that social media can be difficult in particularly vulnerable populations.

• 39:55Speaker 01

  But as we grew. I think maybe, maybe the biggest regret I have is that, um. You know, as founders, we just cared about photography. Like we just wanted people to take great photos and. And the commercialization of Instagram is not something I got excited about over time. It's not something I'm particularly proud of. The idea that you have these beautiful influencers and, and people that. That show, I think, like a non realistic version of the world and that there's an incentive for them to become this and show this because then they can get famous and get these deals and. The influencer culture is something I've struggled with because it wasn't the vision for Instagram. The vision for Instagram was that the every person.

• 40:38Speaker 01

  Could be a photographer and show the world through their perspective. But what it ended up being because of a lot of reasons. Is that the power of distribution was funneled into the hand into a small handful of beautiful influential, et cetera, people. Part of why I'm working on what I'm working on now is that. I hope it would be very difficult for that to be true in publishing. With a machine learning algorithm, because imagine a world where we opened up to self publishers. I actually love the idea that we can incentivize a lot of people to become creators in publishing,

• 41:19Speaker 01

  where they can publish on topics that wouldn't have been economical to publish on in the past. Maybe niche topics, like I don't know if you're into like specific type of gardening or Japanese hi-fi audio systems or something really niche. Can you create a creator ecosystem that unlocks good for the world rather than maybe just envy? And that's super interesting to me, but yeah, like

• 41:48Speaker 01

  I do think basically there's this race to the bottom on a lot of these social media platforms now of like who can get creators and who can get the most influential creators and started on YouTube basically.

• 41:59Alex Kantrowitz?

  They can't basically popularize the term creator account.

• 42:01Speaker 01

  Yeah, yeah, but on YouTube it feels different because it's a little bit more substantial. Like I study, I don't know, music production, there are these amazing creators that feels like I'm going back to school. And that feels very different than like travel influencers or fashion influencers, I think, who dominate the Instagram world. So listen, I don't want to pick on any particular group. It's more just that the balance, I think, of content in the long run leaned towards this unsustainable vision of what a, you know, a perfect person was or a perfect life. I was with someone last night and they just said, everyone's posting on Instagram back in New York City and I now live in the Bay Area and I feel like they're just all living their best lives. And I'm like, can I just tell you like?

• 42:42Alex Kantrowitz?

  They are not.

• 42:43Speaker 01

  Yeah, how many times do people have to tell you that like your Instagram life is not your actual life? People don't believe it. So listen, not working there now, I'm not sure I have much say in the matter, but we always believed that focusing on people and their personal connections rather than popular influencers or celebrities would be the right direction. You know, and they announced, I don't know, I think it was a year ago, that they were just gonna focus on creators now. That was the main focus. I just feel like that is, um, I understand why the game theory leads them to do that. But I wish, and I hope internally, there's still, there's still like a firm belief that the people you know and your family and your friends are the core of what makes Instagram Instagram.

• 43:28Alex Kantrowitz?

  Yeah, there's, it's like a reverse network effect now because the creators are so dominant on the feed. Like I've noticed with my posts and maybe my generation is moving off of Instagram, but like stuff that used to be, you know, filled with comments and engagement is now dropped off. And I know where that engagement is going. It's to the professionals.

• 43:44Speaker 01

  Yeah.

• 43:45Alex Kantrowitz?

  So it is very interesting. We have just a few minutes left. Um, one interesting thing about your new company that you've sort of mentioned or hinted at, but I don't think has really been explored too deeply unless I missed it, was that you have ambitions beyond news. You've talked about how news is just a beachhead for you and what you're really excited about is the machine learning technology. We have just a few minutes left and I wanted to ask you about that. I'm curious what the beachhead, okay, so that's the beachhead. Well, where's the rest of the land and where are you thinking you might go with this?

• 44:17Speaker 01

  I want to be clear upfront that news is super exciting to me and I think probably, you know, if you think about taking a bet, you want to have an edge. And I think, I think the news world and social media is oversold. Meaning people discount it because there have been a bunch of people who've tried it in the past and haven't done well or, or rather they've been around a while and they're not TikTok or something. That was also true with photos when Instagram came out. I remember countless people telling me there's no money in photos. You'll never do anything. And obviously that didn't become true. So you might ask, okay, what's different this time around?

• 44:58Speaker 01

  The reason why I call it a beachhead is because I feel like I care so deeply about machine learning in the long run. The way that like, I don't know. Mark Zuckerberg might care about computing when he started or the internet when he started Facebook back in the day. It's not that we don't care about the beachhead, it's just that wow, this can be so much more in the long run. If you just see that personalization and machine learning is the thing that's going to turn every industry on its head in the next five years. So to me, when I see written content, I see so much more than news. It's not just what's breaking that day, but it's articles on how to be healthier or it's information about a musician that you really love.

• 45:43Speaker 01

  Or, or you know, a critique on a piece of art that you may not have seen in the past. And that to me doesn't feel like news and that's why whenever someone calls us a news app and don't, don't get me wrong, like I use that too. Yeah. I kind of cringe because I think it's like calling Instagram a photo app. It's like we ended up being so much more than just pretty photos. And I think if you're going to start one of these companies, I like to remind myself, it's like, okay. If Apple started and just said, we're just gonna like sell a computer. They wouldn't be what they are today. They have to build beautiful, build and design beautiful products and delight people. And I believe what we're doing is saying, we are first and foremost a personalization company.

• 46:26Speaker 01

  And we are going to spend the next five to 10 years focused on news, but man, wouldn't it be cool if you could do, use exactly this technology and go outside? So like shopping's super interesting, right? Or, yeah, let's just take shopping. The, the number of articles that are served on, on artifacts today. That are full of products that people want to buy, whether it's fashion or electronics, whatever. Like you can find ways where this could become something more than just articles by looking into those articles and saying, oh, actually there are recommendations on products. Um, that's just an example. I'm not sure we'll go that way, but for the foreseeable future, I am focused on how people consume news, but I am excited about personalization in general.

• 47:11Alex Kantrowitz?

  I'm hearing this and I'm like, is this gonna be like an enterprise thing where like you get the data and you have the engine and you might like license that type of technology out to others?

• 47:19Speaker 01

  I wish I could tell you. Everyone asked me at the beginning of Instagram, did we know where we were going? It's like you have a map and a compass and it kind of points north and you go that direction. Um, but part of the fun of this game is figuring out how you can evolve along the way and not knowing in the moment.

• 47:35Alex Kantrowitz?

  It is interesting. We've talked a lot about like TikTok and stuff, but I'm curious if you've spent some time researching, I think the app's called Tuitao, right?

• 47:42Speaker 01

  Toutao.

• 47:43Alex Kantrowitz?

  Toutao.

• 47:43Speaker 01

  Toutao, sorry.

• 47:44Alex Kantrowitz?

  Yeah.

• 47:45Speaker 01

  Yeah.

• 47:45Alex Kantrowitz?

  And which was effectively what you're trying to do, but it was in a Chinese market.

• 47:49Speaker 01

  Of course, yeah. It was ByteDance's first hit. It's the only reason they were able to build TikTok.

• 47:55Alex Kantrowitz?

  So did you? Wow, I'm just curious, like, now that we talk about it, like, is this kind of following that same map of saying, hey, if we get this right, maybe there's other things we can do? And what did you learn when you researched how they were so successful? I mean, they did it, right? They built the news reader that's based on an AI. So it's possible. And so like all these people who are like, well, there's not going to be a news app that's going to work. Well, that's ridiculous. It's definitely possible. So yeah, I'm curious if you could tackle those two things, like, you know, is this sort of a similar ByteDance strategy? And what did you learn when you researched that app?

• 48:24Speaker 01

  I respect ByteDance a lot. I think what they've done is amazing. And I think they spotted trends well before they became mainstream. Um, in the US, machine learning now is so focused on generative AI, which I think is wonderful and exciting and a great demo, by the way. And beyond just a great demo, I mean, ChatGPT is now like a permanent tab in my browser and I use it like I

• 48:47Alex Kantrowitz?

  What do you use it for?

• 48:48Speaker 01

  I ask it machine learning questions. I'll say like, oh, we're working on this problem and like, how would we tackle this thing? And don't get me wrong, 30% of the time it's just wrong, but it's very confident. And that's what's fascinating is like, you're like, oh, this is probably the right answer. And you think about it for a while and you're like, wait, this isn't the right answer. And then you go back to it and you're like, it's not the right answer. Think again. And then it gives you the right answer and you're like, couldn't you have just given me that the first time? Well, what's cool about the process is it feels like you have a sparring partner, like a mental sparring partner, and it keeps you on your toes. So I like it for that.

• 49:21Speaker 01

  Outside, my point is more that we focus a lot on generative AI in the United States. I think my experience has been in China, they focus mostly on personalization and mostly on social AI.

• 49:35Speaker 01

  All the papers that come out that I've read at least are really focused on how do we personalize these enormous user bases? How do we make sure people are seeing the right content? And I think they're just ahead in the personalization game. And I think news apps should work anywhere, not just China. I mean, there are things that make it unique to the United States. Particularly the publishers in the United States and the ecosystem and the history with social media companies for those, each of those publishers and how they feel about social media.

• 50:06Speaker 01

  But bottom line is, I think that, you know, your job as an investor and entrepreneurs look for patterns and trends and say, could it be different here? So certainly there's a lot of TOTIA's history that inspires what we are going after, but it's a different time. I mean, they were fun. They started a long time ago and machine learning has changed dramatically and the ecosystem has changed dramatically. So it's not as easy to say, oh, that stamp works there, just stamp it over here.

• 50:34Speaker 01

  But it's certainly exciting and inspiring about it in terms of a market opportunity. And then bottom line, I just think ByteDance, their strategy of taking what they've built and putting it in different verticals is super exciting and.

• 50:47Alex Kantrowitz?

  They use text as a beachhead.

• 50:48Speaker 01

  Yeah, yeah, they did. Yeah. And I mean, they've done this, they've purchased other companies and tried to layer machine learning on them and to varying degrees of success, but the, you know, I like, like to think about tech is kind of like making movies. It's like, if your first one's a hit, good on you. And sometimes you have to produce a few more before you get another hit. So the question is just like, do you have the volume of production that allows you to succeed eventually? And we're just trying to start where we see a, a large opportunity in the United States.

• 51:17Alex Kantrowitz?

  Okay. So just last question.

• 51:18Speaker 01

  Yeah.

• 51:19Alex Kantrowitz?

  Machine learning, uh, we, everybody here or everybody listening, myself, we're all thinking about like a couple of applications, image generation, movie generation, text generation, like generative AI, chat GPT stuff, personalization recommendations, engines.

• 51:36Alex Kantrowitz?

  When we think about where AI is going to develop now, because it seems like this image stuff and tech stuff came out of nowhere, although I'm sure the researchers like were aware that this was going on. Is there anything else that we should be thinking about? Or is it are those three areas kind of like the key areas to focus on?

• 51:50Speaker 01

  I think those are the key areas now. In general, I think so many of the

• 51:58Speaker 01

  the resources are pointed at the generative AI that I think you will see the most progress made where the resources are pointed. The productization of these cool demos, like it's cool to say three dogs or like three, three golden retrievers making sushi and get an image of it and go, wow, that's cool. But the commercialization of that technology, I think, is a different thing. The chat GPT one feels like

• 52:24Speaker 01

  there's clearly something there that needs to be more than just a chatbot in a window with a gray background.

• 52:31Speaker 01

  And there, there are teams now solely focused on this at Meta, at Google, and at Microsoft using OpenAI as effectively the head start, that something interesting is going to happen in search clearly. And I think it will surprise us all. Like, we all think this is cool. It's almost like these bank runs, you know, like you hear, you know, you hear 10% or you think there's going to be like a 10% problem and it ends up being transformational, wipes a bunch of companies out. I think that technological revolution tends to be similar in that you hear little glimmers, you think something's going to be bad, and then it's way worse than it actually is.

• 53:17Speaker 01

  AI has that property where we all saw cool demos in the last year. And I think what you're going to see in the next two years will just like defy expectations. Now, we're not working on generative AI in the way that these companies are. But I wouldn't focus elsewhere. I would just say, how could it be 10 times better than you actually think it's going to be? And that's my sense.

• 53:36Alex Kantrowitz?

  Mark Zuckerberg calls you tomorrow, offers you a billion for Artifact. You taking it?

• 53:41Speaker 01

  Uh, even if I wanted to, it wouldn't happen, right?

• 53:45Speaker 01

  We talked about that earlier.

• 53:46Alex Kantrowitz?

  Lina Khan is on the phone giving you the call.

• 53:48Speaker 01

  So I'm not going to answer the question because I reject the premise. I don't think it's possible. So let's just talk about something else.

• 53:54Alex Kantrowitz?

  Sounds good. Kevin, thank you so much for joining.

• 53:56Speaker 01

  Thank you. It was fun.

• 53:56Alex Kantrowitz?

  Super fun. And that will do it for us here on Big Technology Podcast. Thank you so much, Kevin Systrom, for meeting me at a recording studio in Austin and recording what I thought was a great conversation. Really appreciate your time. Always great to connect with you. Thank you, SwayCon Studios in Austin, Ken, for hosting us and helping us with the audio. Really appreciate that. Thank you, Nick Guatini, our editor and audio master, for helping us produce this and make sure that it's ready for air. Thank you, LinkedIn, for having me as part of your podcast network. And thanks to all of you, listeners. Really appreciate you coming back week after week. And I know we have a lot of people who've come in from places like This Week in Tech and

• 54:38Alex Kantrowitz?

  the Drinking Bros Podcast and Andrew Yang's Podcast Forward. If you're just giving Big Technology a try for the first time, please hit subscribe. We do these twice a week now, a flagship interview like this on Wednesday, and then a news recap on Friday. And I promise you're going to like what we have in store. Coming up Friday, we have a reporter roundtable. We try to bring a few reporters in to talk about the news of the week, which I'm sure will include TikTok's appearance in front of US Congress to try to not get banned and all that good stuff, and plenty more, of course. And we continue to touch on the financial world and the banking system. Not something you're going to want to miss. All right, that will do it for us here, and we will see you next time on Big Technology Podcast.

• 55:28Speaker 02

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