TikTok CEO Shou Chew dives into how the trend-setting video app and cultural phenomenon works — from what distinguishes its algorithm and drives virality to the challenges of content moderation and digital addiction. In a wide-ranging conversation with head of TED Chris Anderson, he tells stories about the TikTok creators he loves and digs into thorny issues like data privacy and government manipulation — as well as speaking personally about his commitment to inspiring creativity and building community.

Let's see, first of all, congratulations.

You really pulled off something remarkable on that grilling.

You achieved something that very few people do, which was you pulled off a kind of bipartisan consensus in US politics.

The bad news was that that consensus largely seemed to be, we must ban TikTok.

I'm curious, But before we go there, we need to know about you.

I want to know a bit of your story and how you came to TikTok in the first place.

Before we do that, can I just check, I need to know my audience?

CAO HUANG'AN But there's another question, which is, how many of you here have had your lives touched through TikTok through your kids and other people in your lives.

I mean, it's basically --" KWONG-YOON CHANG-YONG It's great to see you.

CALEB KING It's basically, if you're alive, you've had some kind of contact with TikTok at this point.

KWONG-YOON CHANG-YONG So my name is Cho, and I'm from Singapore.

Roughly 10 years ago, I met with 2 engineers who were building a product, and the idea behind this was to build a product that recommended content to people not based on who they knew, which was, if you think about it, 10 years ago, the social graph was all in the rage.

And the idea was your content and the feed that you saw should be based on people that you knew.

But 10 years ago, these 2 engineers thought about something different, which is instead of showing you what you, Instead of showing you people you knew, why don't we show you content that you liked?

And that's sort of the genesis and the birth of the early iterations of TikTok.

And about 5 years ago, with the advent of 4G, short video, mobile phone penetration, TikTok was born.

And a couple of years ago, I had the opportunity to run this company, and it still excites me every single day.

CAWTHONER-LONG, MD So I want to dig in a little

more into this, about what was it that made this takeoff so explosive?

Because the language I hear from people who spent time on it, it's sort of like, I mean, it is a different level of addiction to other media out there.

And I don't necessarily mean this in a good way.

There's good and bad things about this type of addiction.

But it's the feeling that within a couple days of experience of TikTok, it knows you, and it surprises you with things that you didn't know you were going to be interested in, but you are.

Is it really just instead of the social graph?

I think to describe this, to begin to answer your question, we have to talk about the mission of the company.

Now, the mission is to inspire creativity and to bring joy.

And I think missions for companies like ours is really important because you have product managers working on a product every single day, and they need to have a North Star, something to sort of work towards together.

Now based on this mission, our vision is to provide 3 things to our users.

We want to provide a window to discover, and I'll talk about discovery, you talked about this in a second.

We want to give them a canvas to create, which is going to be really exciting with new technologies in AI that's going to help people create new things.

And the final thing is bridges for people to connect.

So that's sort of the vision of what we're trying to build.

Now, what really makes TikTok very unique and very different is the whole discovery engine behind this.

So there are earlier apps that I have a lot of respect for, but they were built for a different purpose.

You know, for example, in the era of search, you know, there was an app that was built for people who wanted to search things that was so that it's more easily found.

And then in the era of social graphs, it was about connecting people and their followers.

Now, what we have done is that we are, based on our machine learning algorithms, we're showing people what they liked.

And what this means is that we have given the everyday person a platform to be discovered.

If you have talent, it is very, very easy to get discovered on TikTok.

And I'll just give you 1 example of this.

The biggest creator on TikTok is a guy called Kabi.

He, for the longest time, didn't even speak in any of his videos.

But what he did was, you know, he had talent, he was funny, he had a good expression, He had creativity, so he kept posting, and today he has 160 million followers on our platform.

So every single day, we hear stories like that.

Businesses, people with talent, and I think it's very freeing to have a platform where as long as you have talent, you're going to be heard and you have the chance to succeed.

And that's what we're providing to our users.

Like, most of us have grown up with, say, network television, where for decades, you've had thousands of brilliant, creative people toiling in the trenches, trying to imagine stuff that will be amazing for an audience.

And none of them ever, remotely, came up with anything that looked like many of your creators.

So these algorithms, just by observing people's behavior and what they look like, have discovered things that thousands of brilliant humans never discovered.

Tell me some of the things that it is looking at.

So obvious things like if someone presses like or stays on a video for a long time, that gives you a clue more like that.

What are the array of things that you have noticed that you can actually track that provide useful clues?

HWKWUIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWIHWI I'm not going to simplify this a lot, but the machine learning, the recommendation algorithm, is really just math.

So for example, if you liked videos 123 and 4, and I liked videos 123 and 5, maybe he liked videos 123 and 6, now what's going to happen is, because we like 123 at the same time, he's going to be shown 456, and so are we.

And you can think about this repeated at scale in real time across more than a billion people.

And of course, AI and machine learning has allowed this to be done at a very, very big scale.

And what we have seen, the result of this, is that it learns the interest signals that people exhibit very quickly and shows you content that's really relevant for you in a very quick way.

So it's a form of collaborative filtering,

The theory behind it is that these humans are weird people, we don't really know what they're interested in, but if we see that 1 human is interested with an overlap of someone else, chances are, you know, you can make use of the other pieces that are in that overlapped human's repertoire to feed them, and they'll be surprised.

But the reason they like it is because their pal also liked it.

It's pattern recognition based on your interest signals.

And I think the other thing here is that we don't actually ask you 20 questions on whether you like a piece of content, you know, what are your interests, we don't do that.

We build that experience organically into the app experience.

You know, by watching a video, you know, by swiping it, by liking it, by sharing it, you are basically exhibiting interest signals.

And what it does mathematically is to take those signals, put it in a formula, and then matches it through pattern recognition.

CAWTHONER-JOHNSON I mean, lots of startups have tried to use these types of techniques.

I'm wondering what else played a role early on.

How big a deal was it that from the get-go, you were optimizing for smartphones, so that videos were shot in portrait format, and they were short.

Was that an early distinguishing thing that mattered?

I think we were the first to really try this at scale.

You know, the recommendation algorithm is a very important reason as to why the platform is so popular among so many people.

But beyond that, you mentioned the format itself.

So we talked about the vision of the company, which is to have a window to discover.

And if you just open that for the first time, you'll see that it takes up your whole screen.

You can imagine a lot of people using that window to discover new things in their lives.

Then, through this recommendation algorithm, we have found that it connects people together.

And I've heard so many stories of people who have found their communities because of the content that they're posting.

I was in DC recently, and I met with a bunch of creators.

And so 1 of them was sitting next to me at a dinner.

He runs a restaurant in Phoenix, Arizona, and it's a taco restaurant.

He told me he has never done this before, first venture.

He started posting all his content on TikTok, and I saw his content, I was hungry after looking at it.

And he's generated so much interest in his business that last year, he made something like a million dollars in revenue, just via TikTok, 1 restaurant.

And again and again, I hear these stories.

By connecting people together, by giving people the window to discover, we have given many small businesses and many people, your common person, a voice that they would never otherwise have.

And I think that's the power of the platform.

So you definitely have identified early just how we're social creatures, we need affirmation.

I've heard a story, and you can tell me whether true or not, that 1 of the keys to your early liftoff was that you wanted to persuade creators who were trying out TikTok that this was a platform where they would get response.

Early on, when you're trying to grow something, the numbers aren't there for response.

So you had the brilliant idea of goosing those numbers a bit, basically finding ways to give people a bigger sense, like more likes, more engagement, than was actually the case by using AI agents somehow in the process.

Is that a brilliant idea, or is that just a myth?

PhD, Global Business Studies, MIT I would describe it in a different way.

So there are other platforms that exist, before TikTok.

And if you think about those platforms, you sort of have to be famous already in order to get followers.

Because the way it's built is that people come and follow people.

And if you aren't already famous, the chances that you get discovered are very, very low.

Now, what we have done, again, because of the difference in the way we're recommending content, is that we've given anyone, any single person, with enough talent, a stage to be able to be discovered.

And I think that actually is the single, probably the most important thing, contributing to the growth of the platform.

And again and again, you will hear stories from people who use the platform, who post regularly on it, that if they have something they want to say, the platform gives them the chance and the stage to connect with the audience in a way that I think no other product in the past has ever offered them.

So I'm just trying to play back what you said there.

You said you were describing it a different way, what I said.

Is it then the case that to give someone a decent chance, someone who's brilliant but doesn't come with any followers initially, that you've got some technique to identify talent and that you will almost encourage them, you will give them some kind of artificially increased number of followers or likes or whatever that they have, so that others are encouraged to go, wow, there's something there and so forth.

Like, it's this idea of critical mass that kind of every entrepreneur, every party planner kind of knows about, of, no, no, this is the hot place in town, everyone come, and that That is how you actually gain critical mass?

We want to make sure that every person who posts a video is given an equal chance to be able to have some audience to begin with.

But this idea that you are maybe alluding to, that we can get people to like something, It doesn't really work like that.

CAWTHONER-JOHNSON But could you get AI agents to like something?

Could you seed the network with extra AI agents that could give someone early encouragement?

Ultimately, what the machine does is it recognizes people's interests.

So if you post something that's not interesting to a lot of people, even if you gave it a lot of exposure, you're not going to get the virality that you want.

Whereas, so it's a lot of, you know, there's no push here, you know?

It's not like you can go and push something, because I like Chris, and I'm going to push your content, it doesn't work like that.

You've got to have a message that resonates with people, and if it does, then it will automatically just have the virality itself.

That's the beauty of user-generated content.

It's not something that can be engineered or overthought.

It really is something that has to resonate with the audience.

CAO HUANG'I, Ph.D., Professor of Business Administration, University of Toronto I was speaking privately with an investor who knows your company quite well, who said that actually the level of sophistication of the algorithms you have going is just another order of magnitude to what competitors like Facebook or YouTube have going.

Is that just hype, or do you really believe you Like, how complex are these algorithms?

Well, I think in terms of complexity, there are many companies with a lot of resources and a lot of talent.

They will figure out even the most complex algorithms.

I think what is very different is your mission of your company, how you started the company.

Like I said, we started with this idea that this was the main use case.

The most important use case is you come and you get to see recommended content.

Now, for some other apps out there that are very significant and have a lot of users, they're built for a different original purpose.

And if you're built for something different, then your users are used to that, because the community comes in and they expect that sort of experience.

So I think to pivot away from that, it's not really just a matter of engineering and algorithms.

It's a matter of what your company is built to begin with, which is why I started this by saying, you need to have a vision, you need to have a mission.

And that's the north star of what you do.

And is it fair to say that because your start point has been interest algorithms rather than social graph algorithms, you've been able to avoid some of the worst of the filter bubbles that have happened in other social media, where you have tribes declaring war on each other effectively, and so much of the noise and energy is around that.

Do you believe that you've largely avoided that on TikTok?

The diversity of content that our users see is very key, you know, in order for the discovery and the mission is to discover.

So in order to facilitate that, it is very important to us that what the users see is a diversity of content.

Now, generally speaking, you know, there are certain issues that you mentioned that the industry faces.

You know, There are some bad actors who come on the internet, they post bad content.

Now, our approach is that we have very clear community guidelines, we're very transparent about what is allowed and what is not allowed on our platform.

And based on that, we have built a team that is tens of thousands of people, plus machines, in order to identify content that is bad and proactively remove it from the platform.

JR.: Talk about what some of those key guidelines are.

In March, we just iterated a new version to make it more readable.

So there are many things, like, for example, no pornography, clearly no child sexual abuse material, and other bad things, no violence, for example.

We also make it clear that it's a differentiated experience if you're below 18 years old.

So if you're below 18 years old, for example, your entire app experience is actually more restricted.

We don't allow, as an example, users below

we don't allow you to use the instant messaging feature in-app.

If you're below 18, we don't allow you to use the live streaming features.

And of course, we give parents a whole set of tools to control their teenagers' experience as well.

CAWTHONER-LONG, JR.: But how do you know the age of your users?

In our industry, we rely mainly on something called age gating, which is when you sign up for the app for the first time, and we ask you for the age.

Now, beyond that, we also have built tools to go through your public profile, for example, when you post a video, we try and match what the age that you said with the video that you just posted.

Now, there are questions of can we do more?

And that question is always, for every company, by the way, in our industry, has to be balanced with privacy.

Now, if, for example, we scan the faces of every single user, then we will significantly increase the ability to tell your age, but we will also significantly increase the amount of data that we collect on you.

Now, we don't want to collect data, we don't want to scan data on your face to collect that.

And it's a challenge that we are working through together with industry, together with the regulators as well.

CAWTHONS So look, 1 thing that is unquestionable is that you have created a platform for literally millions of people who never thought they were going to be a content creator.

I'd actually like to hear from you 1 other favorite example of someone who TikTok has given an audience to that never had that before?

I think, you know, so again, when I travel around the world, I meet a whole bunch of creators on our platform.

I was in South Korea just yesterday, and before that, you know, I met with a bunch of people I don't expect.

There is an English teacher from Arkansas.

She uses our platform to reach out to students.

There is another teacher called Chemical Kim.

What she does is she uses our platform to reach out to a much broader student base than she has in her classroom.

In fact, what we have realized is that STEM content has over 116 billion views on our platform, globally.

It's so significant that in the US, we have started testing creating a feed just for STEM content.

I've been using it for a while, and I learned something new.

Apparently, if you flip an egg on your tray, the egg will last longer.

CAO QIUNG You want to know something else about an egg?

If you put it in just 1 hand and squeeze it as hard as you can, It will never break.

But look, here's the flip side to all this amazingness.

And it's really, honestly, this is the key thing that I want to have an honest conversation with you, because it's such an important issue, this question of human addiction.

You know, we are animals with a prefrontal cortex.

We have these addictive instincts that go back millions of years, and we often are in the mode of trying to modulate our own behavior.

It turns out that the internet is incredibly good at activating our animal selves and getting them so damn excited.

And your company, the company you've built, is better at it than any other company on the planet, I think.

I mean, how From a company point of view, for example, it's in your interest to have people on there as long as possible.

So someone would say, as a first pass, you want people to be addicted as long as possible.

That's how advertising money will flow and so forth, and that's how your creators will be delighted.

As a company, our goal is not to optimize and maximize time spent.

In fact, in order to address people spending too much time on our platform, we have done a number of things.

I was just speaking with some of your colleagues backstage.

1 of them told me she has encountered this as well.

If you spend too much time on our platform, we will proactively send you videos to tell you to get off the platform.

And depending on the time of the day, if it's late at night, it will come sooner.

We have also built in tools to limit, if you're below 18 years old, by default, we set a 60-minute default time limit.

And we've given parents tools and yourself tools.

If you go to Settings, you can set your own time limit.

We've given parents tools so that you can pair, for the parents who don't know this, go to Settings, Family Pairing.

You can pair your phone with your teenager's phone and set the time limit.

And we really encourage parents to have these conversations with their teenagers on what is the right amount of screen time.

I think that's a healthy relationship that you should have with your screen.

And as a business, we believe that that balance needs to be met.

So it's not true that we just want to maximize time spent.

CAWTHON, if you were advising parents here what time they should actually recommend to their teenagers, what do you think is the right setting?

Well, 60 Minutes, we did not come up with it ourselves.

So I went to the digital wellness lab at the Boston Children's Hospital, and we had this conversation with them, and 60 Minutes was the recommendation that they gave to us, which is why we built this into the app.

So 60 Minutes, take it for what it is, it's something that we've had some discussions with experts.

But I think for all parents here, it is very important to have these conversations with your teenage children and help them develop a healthy relationship with screens.

I think we live in an age where it's completely inevitable that we're going to interact with screens and digital content, but I think we should develop healthy habits early on in life, and that's something I would encourage.

Curious to ask the audience, which of you here have ever had that video on TikTok appear, saying, come off?

I mean, OK, so maybe a third of the audience seem to be active TikTok users, and about 20 people maybe put their hands up there.

So are you sure that --" Like, it feels to me like this is a great thing to have.

But isn't there always going to be a temptation in any given quarter or whatever to just push it a bit at the boundary and just dial back a bit on that so that you can hit revenue goals, et cetera, et cetera.

See all Shou Chew transcripts on Tedtalk

TikTok's CEO on its future -- and what makes its algorithm different