An inside look at X’s Community Notes | Keith Coleman (VP of Product) and Jay Baxter (ML Lead)｜Lenny's Podcast: Product | Career

The work that you guys do has had such a tremendous impact on the way the world works.

I want to start with just giving people a brief understanding of what is community notes.

Someone on X can see a post.

If they think it's misleading, they can propose a note that they think other people might find informative.

Other people can then rate that note.

We actually look for agreement from people who have disagreed in the past.

And what we see is when people actually have that sort of surprising agreement, And that's what makes the notes so neutral and accurate and well written really overall.

There's many people that are very polarized.

How do you deal with people that are like super anti -vax, super Jancic?

One philosophical thing that's important is that we want all of humanity to participate.

And sometimes people are surprised by that.

We have all of humanity.

We then have the data to understand what notes will be helpful to actual humanity.

Every post is eligible for notes.

We shouldn't exempt Elon.

We shouldn't exempt government figures.

We should be like everyone even advertisers can get notes.

There have been external studies, you know, run by people totally independent of us who have found that if you take a post with or without a community note, that actually people's agreement with the core claims in the post does change if they see it with the note versus without.

Is there anything else along the lines of just working for Elan within an org Elan runs that might surprise people?

If I were to start a company in a company, it would be even leaner than I would have made it before.

I've been amazed with just how much the team is able to accomplish with a small group and I think because of a small group.

Today, my guests are Keith Coleman, product lead for Community Notes, and Jay Baxter, founding ML engineer and researcher for Community Notes.

This conversation may be my newest favorite podcast episode so far.

Community Notes is one of the most impactful and clever and also underappreciated products in the world right now.

If you ever use X slash Twitter and you see a note underneath a tweet correcting the misinformation in that tweet, that is community notes.

I've never heard a deep dive into the story behind the product and the team that built it, and I'm excited to bring you just that.

We get into the surprising origin story of the product, how the algorithm actually works, how the algorithm emerged out of an internal contest within Twitter, the principles behind community notes and why staying true to them has been so key to its success.

also how it survived four different leaders including Elon and Jack and why it's now a big part of the solution to solving misinformation on the internet including recently being adopted by Meta as their main fact -checking tool.

This is an incredibly special episode and I'm so excited to bring it to you.

If you enjoy this podcast don't forget to subscribe and follow it in your favorite podcasting app or YouTube.

Also if you become a subscriber of my newsletter you now get And a year free of Notion and Superhuman and Granola and Linear and Perplexity Pro.

Check that out at lenysnewsletter .com.

With that, I bring you Keith Coleman and Jay Baxter.

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Keith and Jay, thank you so much for being here.

Welcome to the podcast.

It's great to be here.

Thanks, Lenny. Thanks for having us on.

It's so my pleasure.

I'm so thrilled to be having this conversation.

The work that you guys do has had such a tremendous impact on the way the world works.

So many product teams are always talking about driving impact.

I want to drive impact.

Like you guys have actually built things that have changed the world in meaningful ways and continue to do that.

And I've never really heard the backstory of how CommunityNuts came to be and how it works and all these things.

So I'm really appreciative of you guys making time to chat.

But yeah, first, you know, thanks for saying that.

That's why we built this thing is to help people.

And it's great to hear it.

it's great to see people enjoying it and finding it useful.

I want to start with just giving people a brief understanding of what is Community Notes.

I think a lot of people may have kind of heard about it, kind of maybe see it on X as they scroll through, they see these notes, but they're like, I don't actually know what this is.

So can you just kind of briefly describe what is Community Notes?

Community Notes is a way for the people, like the public, to add context to posts that might be misleading.

The basic way it works is that someone on X can see a post.

If they think it's misleading, they can propose a note that they think other people might find informative.

Other people can then rate that note.

And if the note is found helpful by people who normally disagree with each other, indicating that it's probably accurate, it's probably really neutrally worded, it's probably informative, then it will show to everyone on X.

And the goal is just to get people more information about what they're seeing so they can make better decisions in their lives.

Amazing. And I think like hearing this, it's like absurd that this works.

I think when people originally heard this idea, like no way this is gonna work.

And so just to dive a little bit deeper, can you give us a sense, a deeper understanding of how it actually works?

Because I think it's the algorithm that you guys designed that is so clever that allowed this to work.

So talk a little bit about that algorithm.

Yeah, so I think a key misunderstanding a lot of people have, if they haven't really dived into details, is they kind of just think that maybe someone can write a note and it appears immediately, or we're just taking a majority rules vote of who thinks the note's good.

I think both of those approaches would probably lead to biased or inaccurate notes.

I think the key thing, really, that we do is we actually look for agreement from people who have disagreed in the past.

And what we see is when people actually have that sort of surprising agreement, that's what makes the notes so neutral and accurate and well written really overall is just that people who are very polarized overall often can't find agreement when things aren't accurate, right?

I think it also provides some good anti -manipulation properties.

I think people are often, you know, if you said, I think like back in 2020, before we started building anything here, whether this could work at all, I think a room of ML engineers would say, oh, you have to keep it closed source.

You know, people are going to be manipulating this all the time.

You have to use ground truth labels from fact checkers.

There's no way that you could like bootstrap the system without external labels.

But it turns out that you can do that with this kind of bridging based agreement algorithm is what we call it.

okay so just to summarize and make it is super clear it's basically people someone writes a note this information is full what's like a good example just as we talk about this like a classic example really really classic example is an ai generated image or an out of context image like look what's happening

here but it's actually from like five years ago in a different country and different topic oh man i've seen those so many times where it's like look what's happening in san francisco like no this is a whole different city and that's not totally yeah okay okay so someone posts this ai image someone writes

a note and this is actually five years ago in a different city and this algorithm helps understand if this is a real if this is true this note is true and it's just people regular people doing this yep yep regular people uh who have signed up to be community notes contributors so you know there are a few

checks like you do have to have a verified phone number for instance um but yeah at the end of the day these are regular people uh not necessarily professional fact checkers or anything like that.

And, you know, that was like, that was really important to us too.

Like there was a question at the beginning to the point Jay was making of like, what did did anyone think this was going to work?

Obviously, it was kind of a crazy idea.

We didn't know if regular people were going to be able to do this task.

And certainly, you know, people had concerns about whether they would do it do it effectively.

Initially, some people inside the company were suggesting like, hey, why don't you have journalists or, you know, some some select group be the first participants.

But very specifically, we're like, no, that's like, we're trying to move away from the idea of curated editorial decisions being made around this.

This is supposed to be open to everyone.

So this is very, we very intentionally try to allow all humans in there.

People are randomly selected.

And that's important to it.

You know, feeling fair, feeling open, feeling trustable.

Yeah. And again, it's just like, this sounds like the holy grail of understanding what is true, and it actually works and works so well that Meta recently, as you all know, decided to adopt this exact system for them instead of having tens of thousands of fact -checkers reviewing things.

One distinction that I would make, which maybe can come off as nitpicky, but I think is important, is community notes adds additional context.

It's not fact -checking necessarily, right?

So there are cases where the post could be true, but maybe it's just misleading because there's there's no context uh or there's missing context uh and you know we cover those cases and i think that's that's kind of an important distinction we also we just have the philosophy that users should be able

to make up their own minds right like here here's the here's extra context take it or leave it right yeah what i think about it you shared this with me this example of a uh a picture with a with a with a cat and somebody's community you know is just that's a dog or is it the other way around or that's

a yeah yeah it was a Palestinian boy shares his bread with a dog was the post and it's a picture of this cat right so like obviously this particular node is not super necessary because it just says that's a cat and links to Wikipedia for cat it's kind of a good example that that like the system is this is not something

a professional fact check or whatever, right?

Or I think would need fact checking, but it's proof that the system is really run by the users at the end of the day and adds some comic relief, I guess.

The note is correct.

And I can, you know, it's important.

When does a post get triggered to even be considered for a community note?

Is there like a threshold or is it just you can write a community note on anything and people decide what they want to vote on?

How does that work?

So every post is eligible for notes.

And that was, again, another really important principle.

It's like, we shouldn't exempt Elon, we shouldn't exempt government figures, we should be like, everyone, even advertisers can get notes.

So any posts on the platform can get a note.

And if you look in practice, you'll see notes appearing on world leaders, on Elon, on ads, on media organizations, and on obviously, like just regular people using social media.

But yeah, the idea is really that it's an even playing field for a note to be proposed the person proposing has to have earned the ability to write notes so there is there is that that aspect where you have to like earn in to be able to do this and the way you earn that ability is is through your ratings

by demonstrating the ability to help identify notes that are found helpful to a broad range of people so basically like if you have an ability to to sort of see and know recognize what's helpful to a lot of people then you have the ability to start proposing notes.

I actually signed up to be a...

What do you call these people?

Contributors. Oh, yeah.

Contributors. Yes, I've been rating.

I haven't achieved...

Can write notes yet.

Yeah, it's not super easy.

It takes some effort.

Are there stats you can share about the scale of community notes at this point, especially things that might surprise people?

Yeah. I mean, the service is growing rapidly, so there are hundreds of notes per day.

And to put that into context, I saw some stats recently from someone at UC Berkeley saying there were something like 10 fact checks, traditional fact checks a day.

So in contrast, there's hundreds of notes a day that are getting shown.

They span a huge range of topics from obviously politics, news, out to entertainment, sports, gaming, just whatever's going on that day.

In addition to there being hundreds of these individual notes, they can also be matched to multiple posts.

So if someone writes a note on an image or a video, like let's say it's AI generated or something like that, that note will automatically be matched to all posts that contain the same image.

So you can have a single note matching to thousands of posts.

And over, let's say, the last year, 2024, we had something like 95 ,000 notes that were seen about 30 billion times.

That's more than double the prior year.

prior year was something like 37k note seen 14 billion times so that rate is increasing dramatically i mean you think about like 30 billion views that's a lot of information that is getting out there that might not have been out there otherwise which is pretty cool and the part of the reason it is expanding

like that is the contributor base is expanding um there's something like 950 000 contributors around the world that's you know nearing a million people making this happen which is amazing.

And I'm one of those right like I count as a contributor.

Yeah okay. You're signed up as a contributor.

Okay. Then there's more people on the waitlist too so there's plenty of headroom for more growth.

Regarding the like the matching on media and URLs I think that's a huge way to get extra coverage.

Also I do think we've been very careful to make sure that those matches are precise because i think one thing that people love about community notes compared to other types of fact checking is that actually the notes are custom written for the particular claim you're seeing right so so often a fact

check warning would just say something like you know get the facts here and then there's a link to some generic page about voting uh like information uh which is you know so so not helpful to have the information behind a click.

So pulling the context up, you know, so that you have zero clicks that you need to make and keeping it specific is so important.

One feature I love that I imagine you guys thought deeply about is if I like the post in the past, I get notified later if a community note shows up so that I'm not like remembering this false information.

Yeah, I mean, we try to make notes as fast as we can.

So we want them to appear instantly if possible.

But inevitably, there's going to be a time gap between when a post goes live and when people figure out what's going on and when they get the note out there.

And so we send those notifications to try to close that gap.

And yeah, we get a lot of love for that.

We see people take screenshots and share them, they're excited about it.

And it's also a pretty cool example of something you can do on the internet in the social media world that was difficult in kind of like a print or standard news world where you would see maybe a correction like the next day in a corner of a paper but it was hard to read here you're getting a ping about it

if you've if you've engaged with the post and note shows up at one user feedback point is i'd love the push to just tell me here's what you got wrong because i find that i actually have to go into it and like read it and i feel like the push could just be like here's information here's more context

of this thing you like we'll go take a look at that live user feedback nice okay i want to get into the origin story this whole thing but two more questions because we're on this thread one is what what's the kind of the threshold for a note to show up on a note is that information you can share just

how does that work so just because of the details of the way the algorithm works it uses this machine learning algorithm you know called matrix factorization where you know we fit it with gradient descent and whatnot, the threshold is, you know, it's 0 .4 on this, you know, made up scale.

I mean, in practice, what it means is, you know, basically a majority of people, if there is a polarized divide relevant to the notes, you know, obviously some notes are not about politics or something polarizing, but if there is, then a majority, a sizable majority people on both sides would generally

need to find the note helpful.

And then there are these, there are other rules that come into play beyond that main one.

So, you know, even if it's above that threshold, it might get filtered out if there's a separate algorithm that's looking at agreement between people's incorrect tags.

So like maybe people found the note helpful, but incorrect, right?

Like it happens. And in those cases, it doesn't matter if it's above the helpfulness threshold.

So is this .4, that's probably the wrong way to think about it, but is it 40 % of people that normally disagree agree?

No. It means nothing like that.

It's just like on some arbitrary scale.

Okay. Okay. Yeah. If we changed random other things about the algorithm, that number would also have to change to an equally, seemingly arbitrary number.

We arrived at some numbers like that by gauging user feedback.

So we could share a lot of notes with people get feedback on which ones are helpful and there's sort of just a line emerged about indicating where you know where the where things go from like questionable to pretty clearly helpful yeah and and it is set right now by the way to be really conservative

i think uh we we just are pretty particular about quality and we really want no quality to be really high i think uh i think keith and i both believe that we live or die based on the quality uh of the notes at the end of the day so so we'd rather not show a note that may be good but we didn't have enough

signal on um than the other way around that makes so much sense like i've never seen a community note that is wrong and breaking that promise is a big deal so i completely get why you guys are super conservative there uh okay two more questions along the line because i'm just curious these weren't on my

list of questions asked but i feel like people wonder this how many notes are written versus end up showing up and triggering on it?

We probably show about 8 % of notes that get proposed.

I think that's, it's been between, let's say 7 % and 10 % or 11%, something like that over time.

The number can vary a little bit.

And as Jay said, there are undoubtedly, and you can see it, there's clearly more good notes than we show.

But the goal is to hold a really high bar.

Like we want to show a note when it's going to be helpful.

when it's not going to appear, you know, bias and undermine trust in the system.

Like we want these to be neutral, informative, helpful.

And, um, you know, as Jay was saying, like we view the worst possible mistake as showing a bad note, cause that's going to undermine trust.

And the trust is, is, is why people like the product.

So, so yeah, we, the bar is there.

And, you know, like I said, there's, there's clearly some, um, some in that remaining, let's call it 90 % that are good.

And then there's a lot that are just like, not that great.

And there's some that are bad.

And if you write one of these ones that are bad, which bad being defined as people who normally disagree, find the note not helpful.

So it's like the inverse of the ones we show.

If you write one that people normally disagree, find not helpful, you actually will ultimately lose your ability to write and have to earn it back.

So that range, that other 90 % is a mix.

Sometimes people look at the number, they're like, oh, why don't you show more?

It's like, well, you probably actually don't really want us showing most of those it's the the the goal here is that the system is able to filter out the good ones that makes sense okay one other question is there's many people that are very polarized like very disagreeable with a lot of things how

do they filter into this algorithm how do you deal with people that are like super anti -vax super jan6 like all these very extreme potential views people really are so polarized uh that there there isn't agreement uh among people would typically disagree you know it's possible that this is one of those

notes that might be correct but but just wouldn't be useful contact it wouldn't be you know helpful to show uh as context maybe maybe it's about a claim that people have you know a really entrenched opinions about and they've read hundreds of things about it already uh right like probably probably this is just

uh not gonna improve people's understanding it's just not gonna be a helpful user experience So it might not be the worst thing in those cases to not show the note.

People a few years ago were pretty pessimistic that maybe fact checking never changes people's understandings about what's true.

Actually, there have been external studies run by people totally independent of us who have found that if you take a community note or post with or without a community note, that actually people's agreement with the core claims in the post does change if they see it with the note versus without.

So we are having an impact on this thing that people previously thought was maybe not so easy to do.

And so it's nice to focus on the cases where there is the bridging agreement.

I would also say there is this reputation component to the algorithm as well.

So if you consistently rate notes in a way that is counter to the bridging based consensus, then we'll stop counting your ratings right so uh you know if if you're the kind of person who constantly rates bad notes as helpful uh we we do filter you out so so there's a difference between those types of people

versus just the the good but polarized ones yeah I think you know one philosophical thing that's important is that we want all of humanity to participate and sometimes people are surprised by that they'll be like oh aren't there people who are like you know shouldn't be doing this or like there's you

know i don't they're they're thinking is so extreme or something maybe they shouldn't participate but our view is it's actually we want to have all of humanity here because if we have all of humanity we can we then have the data to understand what notes will be helpful to actual humanity you know we

can we can better model that better better understand and better show those notes so it's advantageous to have people who have all sorts of points of views And we don't expect that every note will be loved by every single person.

You know, that's kind of an impossible bar.

But we do intend to show the notes that like 80 % of people are going to, you know, read and say, wow, I'm glad I knew that.

And so, you know, in that sense, it doesn't matter how, you know, maybe extreme someone views a person's views as it's still great to have them in the program.

So, you know, no matter what your views are, please sign up and participate.

it it helps identify what's really helpful cool and we'll link to people if they want to actually sign up so they know how to do this something we didn't actually type specify these are all volunteers now i was getting paid to be doing these notes and voting right yeah it's totally based on intrinsic

motivation and and we think that's a great reason to be doing it um when you talk to the most active contributors a lot of them they just they want to have better information out in the world and that's a great motivation so yeah that's why they and you know if you if you think about like for these

people the impact they can have it's kind of nuts so uh when we first launched us -wide this was like in 2022 a note appeared on a white house tweet and the white house deleted the tweet and reissued an updated statement and like like imagine being the person who wrote that you probably have like 12

followers your your posts probably get you know a couple likes.

And here you just put a put a note on the White House and they changed their public talking points based on what you did.

Like that is an incredible amount of impact.

So it, you know, it, you can see why people are motivated to do it when they care about what's going on in the world.

It, um, you know, you don't have to be a big well -known person to shape the discourse and information flow in a way that's helpful it's insane like there's so much to love about this one is just the meritocracy of this whole operation of just anybody can that is true and correct can participate and have impact

also just shows you how much information we get that is just wrong like we had no idea how often we see things that are wrong and now we do working on this product has made me realize just how many things i used to trust kind of by default that now I look at more skeptically.

Definitely a meme these days.

Okay. Before we get to the origin story, is there anything else along these lines you guys think might be really important to share or really interesting?

Sure. I guess one other thing just is that although we don't actually use the fact that a post was noted in the core ranking algorithm, which we think is a nice property, there is a really big impact just organically meaning not from the algorithm but just from user behavior where people will like and reshare or you

know quote uh posts way less uh when when notes are applied so just I don't know for for people out there who typically run a -b tests on big uh you know platforms you may already be familiar with this but like one percent is typically an awesome effect size for any sort of algorithm change we saw more

like 30 to 40 engagement rate drops uh for likes and reposts and an a b test we were in uh when comparing uh showing a post with or without a note which is just crazy big um and then and then if you actually look that's that's just an a b test on the engagement rate so that's not the network effect

If you capture the overall network effect of how a post, you know, is spread less by that person's repost, basically if you look top line with a difference in differences approach, different, multiple different external research groups have both found consistently that there's like a 50 or 60 % drop

in total reposts, which is just nuts after a node is applied.

So it's having a really big impact on spread actually too.

that's so like that's so great to hear it's what i would want to see and it's incredible impact basically like a ai image of something false would just go crazy on twitter and did before community notes came out and now what you're saying is just adding that context not actually like you're saying the algorithm

doesn't demote it if there's something incorrect it's just people are like okay this is false why would i want to retweet this that yeah the the notes just totally take the wind out of these stories so like the thing will be going viral note appears resharing drops 50 to 60 percent and like that's it

like it just you can fit at 50 to 60 per generation this the virality quickly goes to zero and and by the way there's uh i have very mixed feelings about this next one uh but authors become 80 percent more likely to decrease or sorry to delete their post after they get noted which okay that's great because like

less less misinfo out there but i'm panned about because those are usually the best notes like if the note was so just good that you had nothing you had no other option but to delete your post those notes don't get seen by other people right because that's hard that's hard there's an there's an argument

by the way that like seeing that's just because you might see the same misleading claim elsewhere off x or somewhere else on x uh you know it might be good to actually show better to have seen the post with the note than not see it at all yeah i'm unsure about that coin that is so interesting yeah uh

yeah i could i'd be so sad if i was that community note writer and just oh man it's so good they just can't even keep the post up okay so coming back from today's world where you're this like small amount of code is changing the way people understand the world and what they believe and making the White

House rescind their announcements.

Zooming back to the beginning of how this whole project started, what I heard just briefly is, Keith, you were just kind of tired of managing PMs.

You wanted to just work on something yourself.

You wanted to work on something impactful away from corporate BS.

And you basically just started looking for something that was impactful, important, and you found this.

Talk about just how it all came to be at the beginnings of the story.

Yeah. So I mean, for me, the beginnings actually go back to why I joined was then Twitter in 2016.

I was at a startup and we were we'd had some acquisition offers.

And one of them was from company Twitter.

And it was 2016. It was the middle of the election between Donald Trump and Hillary Clinton.

And there were something like three televised debates.

But every day, there was a debate happening on Twitter.

And it was very clear, this is where people are talking about these things that matter.

Where information is being shared, where ideas are being formed.

And as a user, it was obvious that I could get good information there.

But it was also obvious that there was kind of questionable information floating around.

And I remember just looking as an outsider thinking like, wow, this is a really hard problem and it also seems really important.

So we ended up going to Twitter and the company was in a turnaround at that point.

So my first three years was just helping to get the company growing again, working on everything that was the consumer product, getting user growth, going back and people wanting to work there again, et cetera.

But a few years in, I was reflecting on what we had done.

You know, I think we had done a lot of good work getting momentum going.

And people in the us and in the industry had tried things to kind of deal with misleading information, but nothing was really working.

Like it was obvious nothing was working.

Nothing could handle the scale of the problem.

Nothing could handle the speed.

And a lot of people just didn't trust the existing approaches.

The existing approaches were either fact checkers or internal trust and safety teams making decisions about what was or was not misleading.

And like a lot of people just didn't want or trust that to be the way this was decided, which is very reasonable.

And so, you know, I'm looking at that.

I was still managing a large PM team.

You know, that's a whole story in itself.

I I felt like I would that job required a lot of energy in and I and I didn't feel like I always saw the output that I wanted to see from it like I didn't see the change in the product I wanted to see and you know I was contemplating should I go start a company uh what should I do something else and I

kept coming back to this problem like man like the how is the world going to deal with the with this information quality issue of like what we get on social media wherever we get it and like you know i'm at i'm at this company where you can make a difference on this problem like why not go and try some

crazy ideas and see if like one of them might work and so i came back i had a kid i came back from paternity leave i went to my boss cave on i was like hey cave on how about i just stop doing my job and i go work on this instead you know this being try some crazy ideas to see if we can deal with misleading info.

He was stoked, and so I went off and started working on that.

It started with just reading any research I could on the problem and existing solutions, what was or was not working, or what were the issues, and then into prototyping.

And then it ultimately led to us building and piloting this idea that became Community Notes.

Amazing. Okay. I have so many questions, and we're going to keep going through the story.

But when you joined Twitter was kind of the it was called Twitter at this point.

I'm going to try to call it X now, which I know is important to your boss.

What era of Twitter was it at that point?

Like it was Kayvon joined or and who was the CEO?

Because there's been many.

Okay. Yeah. I started I came in December 2016.

So Jack had relatively recently come back as CEO to turn the company around.

And just to give you a sense of like the state of the company, something like a third of employees were leaving every year so just imagine like a third of your team gone every year um you know the stock was in the toilet um the product was not really growing um and so uh jack was working on a turnaround

um and k -1 was there already k -1 was running periscope with a bunch of video stuff and you know that that group continued to you know jack jack was there up through the start of the the community then Birdwatch project.

And yeah. Okay. And it was called Birdwatch.

I don't think we've used that term yet, but that's an important point.

It was called Birdwatch initially.

Yeah. So it was originally called Birdwatch when we started the project, but obviously somewhat famously the name changed along the way.

Yeah. Maybe let's just tell that story real quick.

I know we're zooming in tomorrow, but just I have this Twitter thread that I saw between Jack and Elon, when they're debating what to call it.

And Elon's like, Birdwatch sounds creepy.

I want to change it.

Is there anything there you can share?

Yeah, the story there's kind of funny.

Elon came in, acquired the company, and we had just launched the product relatively recently in the US.

It had been in pilot for a year, but we had just made it available US -wide.

And I guess he'd been seeing the notes.

And um he is this soon after soon after the exhibition he dm'd me and he was like hey this community notes thing is awesome and i was like oh i'm glad you like it like let's you know talk and so we talked the next day and he kept referring to it as this community notes thing and i was like you know

it's interesting that you keep calling that calling it that because that's actually the very first thing that i called it like the very first figma mock -up i made depicting this thing was called community notes it just i don't know why it just felt really natural and so that's what we had that's the first

prototype we had tested uh you know later the project changed it changed its name to birdwatch but you know elon was like hey let's just call it that and so the next day we just changed the name and uh you know it was uh it's always uh you're notable for the team when you change the name but really

the team was excited about it i think it is a much more understandable name jack has made fun of it calling it uh like the ultimate facebook name or something like that but the most boring facebook name which is funny because they're now you know launching community notes um but uh but i think it is a very

understandable intuitive name and i think it has served the product really well there's there's a reason it was the name in the very first mock -up yeah i think descriptive names it just makes sense uh this uh connection with elon and uh i want to talk later about just how you've dealt with so many strong

personalities over and kept this alive throughout so many changes but before we get to that um you you did something that i think a lot of product leaders angel leaders just people better manage people dream of give up all this power in air quotes and career trajectory and influence and just like forget all

that i'm gonna go back to just building something awesome, small team.

Is there any advice there that you could share from that experience that you think might be helpful for other leaders to share or to hear, to help them maybe do that same jump?

Because that's really difficult in practice, easy to talk about, hard to do.

Yeah, I think it is a difficult jump.

I've done it a bunch of times in my career, and I've always been very happy with it, where I started with a small team that kind of grew into something bigger.

And then I was like, you know, this is like, we're kind of dealing with a lot of big production stuff.

Team's really big. I want to go back to doing something like crazy and new with a small team again.

And so I've kind of done that like sawtooth leap a bunch of times, but it can be hard because certainly the natural, like the classic career path is sort of, I don't know, rewards or, you know, running a large organization or being a manager, things like that.

But I think at the end of the day, you got to work on stuff you love.

You got to be having fun.

And I think people want to be having impact.

And I think there's one myth that can get in people's way is the idea that the more people you manage or something or the larger your scope is, the more impact you have.

I definitely do not think that is true.

If you just look at, I mean, look at community notes, for example, if I had stayed running a large consumer PM team, like what would I have produced?

Like 16 more pages of OKRs?

Like, I don't know, you know, a bunch of documents.

And I think building community notes has had way bigger impact on the world.

It's become the industry standard for how to deal with this now, which is super cool.

People love it. It's the first thing that is plausibly dealing with the internet scale issue of information quality.

um you know i i think it's unquestionably a bigger impact than i would have had if i were just do whatever doing some standard management track thing like i was doing before and i think that's true of so many other uh you know small companies and startups i i was just reading someone's screenshot i

think it's blake scholl's uh linkedin the other day he went from like director of coupons or something to building the first uh supersonic oh yeah from groupon yeah yeah and i you know, those stories are everywhere when you look.

And so I definitely have found that, you know, for me, I love building hands on I love trying crazy new ideas.

I love the zero to one experience.

It's fun to scale things up to and it can be fun to operate it, you know, at scale, but doesn't you, you know, this team is a good example of one that operates at a very large scale, but that is still very small.

Yeah, I think the way you guys operate is what more and more companies are trying to do remove middle management layers create small teams that just execute and build impact and just like ICs.

Whenever I say IC I have a comment on YouTube like what is IC so I'm just going to explain individual contributor non -manager is when I say the word IC.

So let me follow this thread and when I asked people about how you set up the team to operate effectively and and protect it initially there's this term thermal that came up a lot?

It was like a thermal team, if that's how you describe it.

Yeah. What is thermal?

Yeah. So anyone who's worked in a larger company probably knows that things can get kind of bureaucratic or bogged down.

Decision making can be slow.

Like there's these large planning cycles.

People can like try to like take someone from one team, move them to another, like at random arbitrary times that can disrupt a project, like all sorts of things like that.

You know, our company, this is a number of years ago when we started this project, we had a lot of founders in the company like Kayvon is an example of a founder who was helping to run the company and he had this idea like hey why don't we create this program call it Thermal where we could have teams

that were somewhat isolated from that they could run through their own process they would have like one clear owner the team would be entirely dedicated to that project and we would just sort of like repeatedly make funding decisions as to whether to continue the effort And so why was it called thermal,

by the way? What was the idea there?

I think the I think it was like an old bird analogy of like thermals lifting, you know, the birds on their wings.

Twitter, obvious through one point, obviously had a lot of bird analogies, bless its heart.

And so, you know, that was one of them.

But the, you know, the idea I love the idea as someone who, you know, liked the startup environment.

And so when we were starting this project, I was like, hey, Kayvon, why don't we make this the first thermal project?

And he was like, yeah, let's do it.

And so we started with that way of operating.

And it gave us, from day one, a lot of freedom and autonomy that I think was really important to make the product work.

So just be very specific about what makes it a thermal project.

How do you set that up?

And this is asking from perspective of if a company wants to build their own something like this.

What does that look like?

I think there's a bunch of key attributes so one key attribute is there's one clear driver of the project who's effectively like founder I guess maybe you could have two or something but it's like really clear there's like driver of the project and also there's one clear decision maker that they go

to outside of the team outside of the team and that was true back when we started and it is true now like if we need something or have a question on something I talked to Elon And, you know, it was like that from the beginning.

It's like that now.

I think that's a big reason we're able to make decisions effectively, quickly, in a simple way.

And it probably has to be someone very senior, not just a middle manager.

Yes, it needs to be someone senior who can make the decisions you need made, whatever they are.

So, I think that's really important, that clear decision -making structure.

Another was 100 % focus.

So, everyone on the project is expected to be totally focused on it.

um that at a lot of companies it can be easy to have people's attention sort of spread across a bunch of things and it makes it hard to get stuff done like you'll go to like you'll talk to who you know whoever that person is you'll ask them for help on something and they'll be like yeah i'll help you

i gotta finish this thing you know and it'll take me like a week or two and then i'll get to it and like a week or two delay totally changes the momentum of a project when you know know, we were 100 % focused.

We talk, we talk in the morning, it's like, hey, Jay, why don't we like try this thing on the algorithm?

He's like, yeah, then like, then, you know, that afternoon or the next day, we're looking at results.

And so because of that total focus, the rate of iteration goes way up.

And then, you know, beyond that, there was also just the ability to use whatever our own sort of like decision making process was, we didn't need to write OKRs, or, you know, follow others like standard practices obviously like we had to make sure we were responsive responsibly building the product

and everything but you we didn't use need to use standard um the standard practices and i think that's a another great example like okrs i understand why they can be helpful um but they can also be um you know not necessarily the right cadence i wish to set goals like i don't i think it's really unclear

that quarterly or annual goals are actually like the right pace.

Like we would set our goals for what, like we would set the goal for the next milestone that mattered and we would work on that.

And when we reached that milestone, we would have an idea of what was coming after.

And then we, after when we hit that, we'd set the next milestone, whether that was two weeks, a month, three months, like whatever it was, like we set our own pace and goals at that pace.

And that just, I think is a lot more natural for the development of something.

The whole OKR determination and planning process took longer than it would take us to pick a goal and then execute on it and finish it.

How big was the team early on that you set up?

How many engineers?

It started with just me and then when we decided to build the thing, we figured we needed about five and we wanted to be as small as we possibly could.

It was clear we needed someone on ML doing scoring.

It was clear we needed someone to do some client engineering work, someone to do backend engineering work.

There may have been like, you know, one or two other, oh, we needed a designer and a researcher to help us understand the customer base and make sure we were building the thing in a way that was actually going to resonate with people.

And so I think that was, I think it was like back end, front end, ML design research.

That was the original team from what I remember.

Amazing. So one, basically one of each function.

a question i have for jay actually is there's all this talk of small teams and uh moving fast but you know sometimes you just need more engineers to build the thing is there anything you've learned about just how to keep a team small while moving as fast as you are and not need we need to hire more

engineers we need to hire more engineers i think in the in the beginning when we were iterating uh you know what what should even the requirements be um it was it was definitely good to just have it, like one ML engineer.

But I think at some point we got clear on what the goals of the algorithm should really be.

And we tried, I think at the very beginning, it wasn't clear that we needed to build this bridging -based algorithm, right?

The actual first algorithm that I put into production was very focused on anti -manipulation.

It was this kind of page rank variant, but it didn't solve the problem of bias basically.

So if there are more users on one side, a page rank type graph algorithm can actually amplify those biases.

So I think, you know, after building that prototype and getting data from that, it was clear that, you know, the bridging based algorithm was going to be the way that we needed to solve it.

And at that point, basically, I set up a bake off, basically made, you know, this kind of like a Kaggle competition or something.

So that was like the key time where it was really important to pull in other engineers.

That is such a cool story.

I want to follow that thread before I do that.

You mentioned you guys yell thermal.

What does that mean?

Is that like YOLO, like a version of it?

Okay, we're just going to ship because we're thermal project.

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I was going to ask just what inspired this actual algorithm, and you basically did an internal competition amongst ML engineers to see who had the most successful algorithm.

Netflix, contest style, Kaggle style.

Yeah, yeah. I think this particular idea of finding content that is light by people on opposite sides of a polarized divider who typically disagree.

You know, this was not an idea out of thin air, right?

Like I think Keith had found some of Chris Bale's work he had done.

He had, you know, made this list of accounts that were often liked by people who, you know, were on both sides politically.

There is, you know, other projects like Polis out there that look for agreement among, you know, people who typically disagree.

But I think that, yeah, it wasn't obvious that our project definitely needed to use that from the very beginning.

But then, you know, when you implement it and compare it against these other type...

Like PageRank seems obviously, you know, it's designed to be kind of manipulation resistant.

It's naturally, like if you just have a voting ring of people who all vote themselves up, then PageRank can filter that out very well.

But like that just wasn't the main attack vector, I guess.

So we had to get some real data from the pilot to realize that, okay, the real thing going on here is people are polarized.

And so it was only once we got the real data from the pilot that I think it was clear that the bridging -based algorithm was the direction we really needed to go.

I want to come back to the way you operate the team.

I hear that you run the whole team off a single Google Doc.

that's like a four -year -old doc that you just keep adding goals to and bullet points.

Is that true? There is a very long -running doc that has had to be chopped and purged because it was breaking Google Docs and Chrome at various points in time.

It's sort of like a note -taking doc.

It's really where we coordinate what we're doing.

The team meets on a daily basis.

We spend whatever amount of time we need to get on the same page about what we're building.

thing that can be, you know, we might talk about anything from, you know, what's most important right now to what are, what should we work on next to what are we trying to launch right now?

And why is it not launched?

Like what's in the way of launching it.

And we might review a new modeling or scoring algorithm update and, you know, try to understand what's working in it, what's not.

Um, so we'll just cover whatever we want and, um, or whatever feels most important.

And we like, you know, as you said, we set our goals very dynamically.

So whatever seems like the most important thing for us to work on now and next is what we spend our time on.

I think that's served the project really well versus feeling attached to like some kind of quarterly goals or something like we'll look at like what is going to help people the most or like what's the biggest problem right now?

What are either one of those?

And we will go tackle it.

And we might change our roadmap multiple times in two weeks based on what we see.

So I'm hearing no JIRA, no Sauna, no Monday .com.

No. Yeah, I mean, we have to use JIRA to coordinate with some other teams.

Like sometimes when we file a request, we have to make a JIRA ticket, but no, I am not a fan of heavyweight task management.

I love like being on the same page, being able to keep most things in my head and having a really light way to write down the things that, you know, I can't, or the team can't keep in its head.

We did use Asana briefly, but my memory of it is that it spent, you spent more time in the meeting grooming a backlog of irrelevant stuff than actually, you know, talking about the proper priorities.

So I think it's nice in the Google doc that if something becomes irrelevant, it can kind of just fall off without needing explicit backlog grooming.

So just to maybe summarize a little bit of how you guys operate that might inspire other companies to set teams up like this uh so I'm going to go through a few things that you shared one is one person in charge of the team like the founder almost they're like basically the founder of the team they have one

very senior essentially sponsor slash decision maker that they interface with in your case Elon no big deal in other cases it could be the CTO CPO someone like that uh the team is focused 100 on this product and and and goal.

You keep the team very small.

So you start with one person of each function.

One front engineer, back end, ML person, designer researcher.

And then Google Docs, almost basically for your project management.

Is that roughly like, yeah, it's basically running with Google Docs.

Stop, don't use big complicated products.

I think that's a pretty good recipe.

On the Google Docs, you know, take it.

People can do what they want.

Go for it. I think those first ingredients are really are key structurally.

And then, you know, beyond that, it's a matter of having an ambitious goal that gets people fired up to go do great work.

Yeah. Awesome. I think there's a lot there that a lot of people kind of like think they should do and they set these teams up, but they don't actually do.

And it feels like each of these is just a really key ingredient to it's actually succeeding.

It definitely really helped us succeed.

I don't know that the project would be here if it was not for some of those elements.

That's a powerful statement.

Like this thing that has changed the way the world understands what is true would not have existed if you didn't set it up in this specific way yeah i think uh you know i i don't know if i would have start would have begun the project had i not known we had sort of that structure that ability to make

decisions the autonomy the the speed the ability to go fast and you know working we we started with that in 1 .0 and and it's been continued and if anything furthered in x i mean x as a whole company operates with a lot of those attributes and um i think it's it's one of the reasons the product is successful

i think it's a big those are big reasons why at least i jay can speak herself i have so much fun working on this like i i i love working on it you know it's great to wake up every day and solve these problems we get to you know we get to do them efficiently make decisions quickly build stuff that helps

a lot of people it's it's awesome yeah this this like uh whether thermal or elon way of operating is definitely more fun and and the fact that like that combined with the the awesome mission is super important for internal recruiting like i remember uh like when i was first chatting to keith about this back

in early 2020 you know i had another project i was you know working on a few but one was like personalize the number of push notifications that we send.

And it was, it drove a lot of DAU without like losing opt outs significantly.

So, you know, that, that was like setting me on track or, you know, if I had kept working on that, I could have probably gotten a promotion from that with low risk, or I could take this huge career.

I mean, it's not as big a career risk as like joining or founding an actual external startup, but there is still career risk, I guess, and joining a team like this.

So, so just, I think all of the same aspects of recruiting that apply to external startups imply internally.

And if you can have an exciting vision, that is key.

Related to that and your list, Lenny, one thing we missed that's super important is that on this project, and I think of successful projects like in startups, is that people are self -selecting to join.

we did not assign anyone to this project like people reached out to join or they applied to join the job you know i and the team interviewed every single person that joined the team and we're like we want that person on the team they want to be on the team and so people are totally bought in to the goal

mission the way the team works the other people they're going to be working So a great time to do that is at the start of one of these things.

Like if you're going to try something crazy, it's going to be tough if you're just assigning random people to it.

But if you let people opt in and self -select, you're much more likely to be successful.

And one thing that I have observed at X, which really surprised me, was that this is also possible at a large scale.

You know, one of the things Elon did when he bought the company was he basically asked people to self -select to stay.

You had to click the button.

And he sent an email out that was like, hey, Twitter 2 .0.

Fork in the road, right?

Fork in the road. Fork in the road, exactly.

It's like Twitter 2 .0, now X, it's going to be hardcore.

We're going to do ambitious things.

You're going to work your butt off.

And you had to click on the form and say, yes, I want to join.

And I think that was really important for the company because you want people to opt into that.

you want that people to be saying like, yeah, that's what I want to do.

And the company is going to be a lot more successful.

If people aren't sure it's like better for them probably to go do something else and where they're naturally more aligned and happier.

And I thought that was a great approach to taking a large company and getting it down to people who are really excited about, you know, working together on a mission.

So, you know, for us, we did it from day one, which I think is an easy way to do it, but it's possible to do it later as well.

I love that you described it as fun.

And I think a lot of people when they see Elon laying off a bunch of people being like very hardcore himself, people don't imagine it as a fun place to work.

And it's clear how much you guys love working on this, like how fun it is and how interesting it is.

And it's interesting to hear that because I think a lot of people don't feel that externally.

Is there anything else along the lines of just working for Elon within an org he'll on runs that might surprise people about just the way of working that's interesting or surprising or what you think other companies might want to think about adopting i've always liked lean teams but this has made me

my experience at x has made me change the way i would i would think about running a future or you know if i were to start a company and change the way i think about starting that company it would be even leaner than i would have made it before i've been amazed with just how much the team is able to

accomplish, um, with a small group.

And I think because of a small group, like when shortly after the acquisition, um, you know, we had this product called spaces.

Um, it was, it had been in the product before, but it was, it was pretty small scale.

And Elon wanted to run these large spaces.

I forget who the first people he was going to bring on where, but he was going to be there.

You know, ultimately these things have gone on to host politicians and things like that and he's like guys we got to scale this up i forget the numbers like we need to be able to scale like a million people or something like that i'm getting the numbers wrong you'd be able to scale way up this is the kind

of thing at 1 .0 that would have taken a year if it had ever happened and the team did it in like two or three weeks and uh it was really exciting and inspiring to see like we i didn't work on that but i watched it from the outside.

I'm like, wow, with this tiny team, motivated behind a big goal that was like, hey, guys, it's not like, are we going to do this?

We are going to do this.

They got it done in two or three weeks.

That must have felt amazing for them.

It's certainly exciting to see.

But I've definitely come to appreciate just how lean something can be and not just get by, but actually thrive because it's that lean.

I think the point you made about people opting into that is important, because I think a lot of people hearing that would be like, I would never want to be asked to build something like that in two weeks.

And I think a lot of people do and we love that kind of experience, especially working with Elon, especially shipping something of that scale.

But I think there's an important element there of just like, okay, I don't want to do that.

I have other things to do in my life other than ship spaces.

So I think that's a key point you've raised of just there's an opt -in step.

Totally. I think the opt -in is important.

And it may even be that you want to opt in one part, you know, at one point in your life and maybe at another point in your life something else is better i think you know whatever it is you're choosing to do it's nice to to be opted in to feel like it's aligned with how you want to spend your time something

on my mind and i don't know if you guys want to go here but it's something i think a lot of people think about is when elon came in he let go of 80 of folks and everyone's just like twitter is dead it's all going to fall apart there's no way they can run this thing with that small of a staff and clearly

it they were wrong clearly it's working great It's like becoming like a massive deal in the world and continues to grow.

Is there anything about that, that you were surprised by or anything about just like how it, it continues to operate so well in spite of that big shift?

I think the, the, the leaner team, the, the reduced kind of like process and bureaucracy is a big reason it does move as fast as it does.

It's easier to get stuff done faster here.

And, uh, yeah, I mean, I think that's, uh, I think, I think it's that, that shrink shrinking is actually a big reason for the increased pace of launches, the increased pace of experimentation.

organization one thing that i noticed that as a result of that is the people who are here they seem to all really feel like owners like like they take the sense of responsibility that an owner takes in the product they'll try to track down what's wrong fix whatever is needed jump into any to to help

build or fix improve any system that needs help even if it's outside of their space and there's the flip side of that too for people who've worked at big companies they may have experienced this thing where where there's like a nut you want to change some something in some other system or product and so you

reach out to that team and like maybe they're a little resist and they're maybe like oh we'll get to that next quarter they have their own goals to hit yeah yeah exactly like they don't really necessarily want to help you or they're busy here you're like hey guys we need to do this thing with that other

system you work on and they're like great here's the code here are the docs you know send us the fab if you have any questions and we'll get it in And it's just the thing.

You can just jump in and get it done.

And that kind of collaborative effort, like the sense of like shared ownership, I think from my experience came from a result, was a result of the shrinking of the team down to people who, you know, wanted to be there and work together to build this thing.

So I think that's been a really positive impact.

It's not always easy.

Certainly like a lot of people have a lot of responsibilities, but, you know, they're here because they're up for it.

Yeah, I think one other thing that's key is when you are forced to have such a small team, you know, deleting, well, this is important anyways, but deleting code is more important than writing it a lot of the time.

So, I think so often, maybe due to promotion incentives or just regular human tendency, engineers have a tendency to add these little incremental wins that actually add more of a long -term maintenance cost than is clear.

Because you just run a little one -month A -B test, you see this significant win, and you don't realize the maintenance burden you just added to your team for the rest of eternity until you turn the thing off.

So I think there's a lot to be gained.

And you get forced to do this, by the way, when you have such a small team.

It's just deleting, you know, auditing parts of your system and deleting the things where the maintenance cost is worse than the gains.

So I think we did have to do this across the company after the big layoffs.

And, you know, systems are leaner now, and they can be worked on by fewer numbers of people.

That's an amazing point.

I remember Elon's being like, here, we have to throw away the whole thing.

We have to re -architect everything.

It's stupid the way it's built.

And it sounds like that actually worked.

Yeah. Well, you don't have to rewrite everything from scratch.

I mean, some things we did, I guess, rewrite.

But I mean, just even deleting the unnecessary cruft and keeping the rest of the core system.

That's awesome. I love that we're creating kind of a formula to run these sorts of companies and teams.

There's so much here.

I want to go back to the building of the original product.

It kind of took us on a long tangent and an amazing tangent but uh i heard a story of when you launched birdwatch at that point you specifically wanted to keep expectations very low and there was like a gif in the thing and it just looked like clearly this is not uh ready for prime time talk about just

how you do that how you launched it in a way where people weren't like and it's never gonna work we were very disciplined i guess you could say about having the product prove itself at every at every given point.

When we built the first mock -ups, these were just like pictures of, you know, depicting what community notes might look like.

We showed those to people across the political spectrum.

We saw like, hey, people really like these, whether they're on the right or left.

Like they seem very open to reading these community notes, even when they are critical to people of their own side.

So we're like, all right, that gives us confidence that if we can build this, like if we can actually make this as a reality, it's going to work.

Then there's a question of like, can we make it a reality like our will people in the real world be able to write notes that are of this quality and so um you know we built we had an internal pilot test version of this where you could like write notes and we first basically ran this through like a amazon m

turk type of uh particular test just to see like if you just like put some normal people in there like will they be able to write these notes and it not they weren't all those notes weren't good but like it was clear that there were people out there who could write good notes so then like okay this is possible

like what will happen if we actually do this out in the real world and like let's write let's run a pilot and find out and so we took that pilot that you know we'd run the mturg kind of test on and we released it to at first a thousand people told you know totally out in public and we didn't know what was going

to show up like you could imagine the notes could have been terrible and uh and so we were talking like well what do we do like we're going to put this out there everyone's going to have all these questions they're probably going to be really skeptical like and we know it might be a total dumpster fire

and so like what do we do to like set expectations appropriately like we felt like we could probably get there in the end but we just didn't know it was gonna happen at first we wanted to set expectations and so we're like well why don't we just stick there's like the page where you see a post in the notes

flow like why don't we just stick a dumpster fire gif like on that page and uh you know you go there you're like hey you know anything you see below here might just be a total dumpster fire at least it would show we we were aware of that as a possible risk um we in the end we did not do that it cracked

me up um but we thought it was kind of like oh you didn't actually launch okay we had we had mock -ups of it and every time i looked at the mock -up i laughed but uh ultimately we had so much to explain on that page like what is this thing and how does it work ultimately like okay this is probably gonna like

distract from the point um so we pulled it so i somewhat i kind of wish maybe it had seen the light of day at one point but yeah ultimately we kept it simple we focused that page on explaining what was going on here but again you know we um as has happened many times with the project you know we put

the pilot out there and the notes were good like they weren't all good there's it was a mixed bag but like there was gold in there and from the very early days with just a thousand contributors it was obvious that that people could write notes that were informative that were neutral that spoke to controversial

challenging topics and that if we could just identify those from the rest this was going to work.

Like it was going to work as well as the very first mock -ups we had made.

So that became the focus that is how do we sift out the gold from the rest?

I remember there's a, I think you may have shared this with me when someone noticed you guys were testing this and they took screenshots and tweeted it.

And I think Elon replied like, this is cool.

Yeah. Yeah. So in the very early days when it was just a Figma prototype, we were running these like usertesting .com unmonerated studies.

And I guess one of the participants sent one to an NBC reporter who like wrote a bunch of stories on it anyway like that day there's a lot of chatter about it on on the service and Elon this is like this is put this back in you know time perspective this is I think 2020 so two years before any acquisition stuff

happened Elon is just a Twitter user building rockets and electric cars and other cool stuff and stumbles on this thing that depicts the prototype that we've been testing.

And he writes back, yeah, definitely worth trying IMO.

And I remember thinking that was cool back then.

And it's interesting to see, like he's obviously had a very consistent point on it.

I think the, you know, the idea was appealing and he, you know, has obviously been a big fan of it in the product and been a big support and proponent.

So, yeah, it was kind of, it was kind of cool that it came from, that support has been from the very early days before he was ever involved in the company.

I love that moment.

It must have felt really wild for Elon to be commenting on this Figma prototype retesting.

It was cool. It was cool.

Oh, man. So when we were preparing for this interview, I asked you guys, what's the main thing you want to make sure people get and understand about why Community Notes has been so effective?

And Keith, you specifically said that it was the principles behind how you wanted to approach this and how you continue to stick to this throughout and we'll talk about how you kept it alive throughout all these different co changes of leaders but just talk about these principles like what the actual

principles are and why that was so key to it working out there are a number of principles that i think when we first shared them with people at the company seemed maybe a little bit crazy um but i think they are they are the reason the product works and i think they've been very important and we do

we come back to them regularly today all the time probably the craziest one is just that this thing is going to be the voice of the people it's going to represent the voice of people it's not going to represent the company's voice so it is not a tech company deciding what shows it is the people deciding

what shows and that had a lot of implications on the design like first of all there is no we don't have a button that will change the status of the note of a note so if a note is showing because the people have rated it and found it helpful it is going to show like we can't change that and that is the kind of thing

that like when we first proposed this that's unsettling to people they're like wait so like something can go up and like we you know the company can't take it down or you know what where I can't change its status, get it to stop showing.

And we're like, yeah.

And like it has to work that well.

If it doesn't work well enough to do that, then it doesn't work.

If there's a problem with the note, there's like one of our, one of our key principles was if there's a problem with a note, it's so bad you want to do something about it.

It's a problem with the system.

Like we need to redesign the system to, to be showing good notes.

And so, so yeah, we had to, you know, get everyone comfortable with the idea that there was no button to, to change the status of a note.

But similarly, as we talked about earlier, we wanted this to represent all of humanity.

And so we didn't want to be arbiters of who can come in and be a contributor and who can't.

So we open it to everyone.

You just have to meet really basic objective criteria.

You have to have a verified phone to help reduce the likelihood of having bots or things like that participating.

But beyond that, it's random selection.

And it still is that way today.

and you know again that people took some time to get people comfortable with it but i think that the the fact that this is the voice of the people and reflects their output through an open and transparent process is so key to both why it is good like why it works but also why it's trusted so i mean that's

number one and and you it's you know well i think will forever be at the heart of the products um another one um that people thought was kind of crazy was transparency you know we're like we're this we we the previous approaches to dealing with misleading info they it felt to a lot of people like sort

of black box tech companies or media companies or leads or whatever making decisions like they people people need to get comfortable with this They need to trust this.

So the whole thing has to be out in the open.

Like the code that decides what note show has to be out in the open.

All of the data and ratings that make it happen have to be out in the open.

People should be able to take the code and data and replicate the whole service and that we have done exactly what we've said we've done.

And they should be able to audit it.

They should be able to go and look and say like, hey, I think this part could be better.

Or like if they think we're biased, they should be able to work, you know, work with the data and point it out.

And if people have good observations, that should factor back into the code.

And this is, again, something that's kind of difficult to get people comfortable with.

That everything is out there.

You can't cover anything up.

But I think that's so essential to people trusting it.

So, yeah, I mean, we set these out on day one.

We go back to them constantly because we're always evolving the product.

And we're always like, got to make sure every new change is open.

Like whenever we update the code or update the scoring system, there's an update in GitHub when the data is published daily so you can download it.

And so, yeah, I think those have been really essential to the thing working.

Yeah. And by the way, these do not come without a cost, right?

It's actually really hard from an eng perspective to actually open source the actual algorithm that's running on the actual data.

because the way large -scale services like this are usually architected does not naturally lend itself to being run as a script by someone who's downloaded a TSV.

So I actually have to take weird architectural decisions to make this possible in a way that probably wouldn't have been if we didn't start with this assumption from scratch.

We would have had to maybe rewrite the system to make it like this.

What's an example of that?

For instance, there's a matrix factorization that we train.

right? Usually, you would train a matrix factorization, you would train your ML model once and then serve it, I guess, with a separate service.

But, you know, we didn't want to have people externally spinning up services, you know, to be able to replicate the, you know, system that we had.

So, I mean, basically, I don't think it would have been actually very cool if we had open -source the code in a way that wasn't actually runnable, I guess.

By someone just... At this point, you can download Python code and run a script.

You do need a lot of RAM right now, but you can do it on one machine.

How much RAM are we talking about?

Oh, like 500 gigs. It'll take a day if you don't do anything special to speed it up.

Cool. Possible is the key thing and people have done it um like uh vitalik peter and had a blog post where he you know talks about uh his explorations you know making sure the algorithm really does what it says it does and you know i think just the fact that a handful of people have done this uh you

know there's there's enough people who have done it that there's someone you'd probably trust who's who's verified yeah yeah and now it's rolling out to meta no big deal uh i love just like as you describe these principles just i could imagine a pm at a company being like okay guys here i want to do

this project it's gonna be completely like there's so much idealism to it that rarely works in real life it'd be open source you're gonna give it to everyone we don't have actual control over what it's gonna do don't worry about it it's gonna just change the way people see this thing that we've been

very careful about uh and then it works and i think that's very rare and it's really impressive and what i'm hearing partly is the sticking to those principles was actually fundamental to it working and not kind of bending over when someone's like, no, no, no, we can't do this.

What if we changed to this part?

I think if we had broken with any of those principles, like if there was anything black box, if there was, you know, whatever, the product would be a lot harder to trust.

And so I think it's because we've just stuck to them so cleanly, simply, that, you know, people can't trust it.

You've talked about a few moments when was like wow the white house changed their announcement because of a community note we talked about the dog is a cat are there any other moments that after you launched of like holy shit this is working this is gonna actually work all along you know we saw it we

saw it working like we were pretty we we wanted to be confident whenever we expanded it to new you know audiences or new countries or whatever like we wanted to be confident it was gonna work so you know maybe hold our breath a little bit just to see that it would do what we expected.

But we always expected that.

But that said, there were definitely stress cases.

I mean, the one that comes to mind is the start of the Israel -Hamas conflict in 2023 in October.

That was probably the largest deluge of misleading information I've ever seen shared on the internet at one time.

It was overwhelming.

that just the number of photos and videos and whatever coming out related to that was it was insane and um just to you know to give you an example in the first i think it was like first three days or something of that conflict we had 500 notes covering all sorts of different uh you know like out of context

imagery like people someone said like hey this is happening here um it's actually from like 2013 in syria there were people making fake like battle footage in the video game simulator arma 3 so they're like notes explaining the stuff looks really looked realistic and you unless you saw the note you like

wouldn't really know um there are all sorts of claims about what was going on in the ground and you know that was definitely the product was still pretty new at that point we had only we'd expanded in the u .s um less than a year before that.

We had been rolling out throughout the world that year.

And then this large event happened.

And I felt like we were just enough prepared at the right time for the system to be able to handle that.

Probably one of the most important things we did right before that was launch the ability to write notes on images and videos and have those matched to other posts.

I remember at that time thinking like, wow, I'm glad we launched that feature a few months ago versus still had it on the shelf because it was really important in that conflict.

And I think even it was like just a few weeks before we had launched a major speed up in notes to like, when we, when we first built the product, the number one focus was always quality.

Like we knew, we knew that notes, the product would live and die by the quality of the notes.

And like, that was the thing we could never give up on we also knew it needed to deliver speed and scale but we're like we will we'll get the quality in the right place and we can speak we can speed it up and scale it out over time and we had actually just launched a speed up that took like three hours

off the time it um time a note needed to go live and i was you know i think a matter of weeks before that conflict happened so again like super glad that was out there the in the first few days of the conflict the median time from a post going live to note showing up was five hours which is like crazy

fast difficult fact checking is like two to four it's really it's really common to see it take two to four days these notes were showing up in five hours we're like we are so glad we got those things out before this happened um it made the service a lot more helpful one other thing that was um i i think

uh nice to you know see see working then was i think one criticism of community notes some people bring up is well if you always need agreement from people who typically disagree then in these super polarized settings like that conflict being like probably number one uh then then you know uh you wouldn't

see any notes but actually the reality was there were the you know tons of notes about that conflict um so i think there is this kind of um you know nice uh nice property where actually and maybe this is a surprising fact that there's more agreement out there across polarized divides than maybe conventional

wisdom says, right?

And the places where people agreed were really objectively true and verifiable.

Like, I guess maybe this is more true the more polarized the setting is, but where the agreement actually lands you in basically notes that are very neutrally written, very focused on the facts, and easy to verify information.

I love just like, there's this talk for a while of just like no more there's no more facts like nobody believes there is a single true fact anymore like everything is subjective and i think community notes is exact proves the opposite yeah facts matter there are facts we can all agree with even the most

controversial topics yeah yeah we we saw this really from day one it's you know we when we would show those prototypes to people just depicting the idea, it was really obvious that people cared more about, or they cared a lot about getting understanding reality and what was going on.

And they were willing to disagree with like their side, so to speak, to recognize that.

And I think that's not always that obvious to people.

The world does feel really polarized, but people definitely are willing to cross partisan boundaries to, to get to, you know, accurate information.

And that's why the product works it feels like as we rely more and more on what we know and and understand about the world is becoming social media online and moving this quickly it feels like it's like we're i'm so thankful this exists because otherwise it just be what do we trust anymore like this is like

it like this being out aligns with we need this thing to exist at the same time and it feels like at the same time there's also this people just like i just don't trust i i think people have shifted from i trust what i read to okay i shouldn't just believe everything i'm reading uh is there anything

there you're noticing about just how people think about news they see and their shift of just like i'm not going to believe everything is there anything there you've noticed about just like human behavior just the way we've shifted understanding what is true we haven't done any research you know should look

broadly at at how people's perceptions are are changing there but i certainly have found you know myself that particularly seeing notes um i am more skeptical about what i read at first and i i think that's been helpful and we hear that from people that they think about things a bit more and you know

i think that's a good secondary effect and benefit of of something like this which is the more you see the patterns of how what you're reading can be wrong, the more you can thoughtfully question it and try to get a better understanding what's really going on.

So it's like, you know, historically, I think this was called like media literacy, but a basic idea of like, can you understand the ways in which things can go wrong and try to set them yourself.

And another aspect I think we help with that is discovery of the community notes.

Uh, I think often, you know, before community notes, you could have just been living in a little news filter bubble, or maybe there were fact checks out there that you should have been reading, but you weren't discovering them.

Uh, right. So, so the, the fact that the note applies, it is directly attached to the post, um, and visible by anyone who sees the post helps, you know, cross those filter bubbles and, and can kind of, I think for some people, it's the first time they've actually seen counter arguments to, you know,

to to claims made in their own little echo chamber.

That's incredible. Yeah.

I love the point you're making about how it actually teaches people to be a little more skeptical of the things they read.

Like it's an education system more than more than just here's this one thing is wrong.

I love that. Okay. Just a few more questions.

There was an audience question asked on Twitter.

We all asked on Twitter.

what people want to know back in the notes one was actually why you guys switched to anonymous contributors what was the decision between behind that yeah that was you know we had this pilot um where we were testing the with a small number of contributors like a few thousand contributors and we learned

a lot through that pilot probably the biggest thing we learned was related to anonymity or pseudonymity of contributors we had originally assumed that it was important that people contribute under their like real handle or their real name or whatever it was.

We actually like the first prototypes depicted that we kind of thought that would be important for like people trusting the note.

And actually it was totally wrong.

We were like, it was the best option was actually opposite of what we first tried.

We found a few things.

One, people were hesitant to write a note on a controversial topic because they didn't want to get like attacked or harassed online.

And so some people were comfortable doing it, doing this, but others were not.

And so it meant there was more potential good notes to be written, um, than were getting written.

And this is very clear feedback from the pilot too.

And this is super interesting.

People are actually more willing to cross partisan boundaries when they are anonymous or pseudonymous than when they are under their real name.

And it you publicly are using your name, you feel are affiliated with one side versus the other, you might hesitate to the perceived as breaking with that side.

But you may actually, for example, find a note helpful that's critical of that side.

And there's a bunch of studies that show when people are anonymous, they're much more willing to cross partisan boundaries and work with the other side, agree with the other side.

And we saw that too.

And so by allowing people to just to be pseudonymous you actually get more honest answers about what they really think and it helps find disagreement that really so counterintuitive yes you know you never hear the opposite always and it's so interesting that's the opposite yeah yeah i think this uh

the the same principle applies to making the likes private i was just thinking that yeah yeah i like a lot more stuff that's a little stuff i wouldn't have liked yeah it allows it allows freedom for honesty which is is like, you know, can generate, maybe like people reduce their quality, the quality

threshold that they put out there.

But we have so many quality mechanisms in the system that that wasn't an issue.

So we could keep quality high while opening up for that honesty.

Another question, you touched on this a little bit, which is around navigating the existing trust and safety apparatus of Twitter, which as you described, basically previously it was like, we make decisions on what is true and not.

and there's every company works this way you guys basically upended that like here's a completely different way you have no control over what is what we say is true or not talk about just that experience of kind of overcoming that I imagine very difficult hurdle of like okay forget all that we're going

to do a totally different yeah it was definitely what we were proposing was very different I will say that I think people were sort of open -minded to it generally speaking and I think everyone had a sense that what was being done at the time wasn't really working that well or solving the problem and people

were opening new ideas so that was that's like a good foundation but I think one thing we did that was probably very helpful in that is we wanted the product to prove itself at any point like first it had to prove that people could possibly you know find notes helpful then it had to prove that people

could possibly like write these notes that would be good quality.

And so anytime that we were proposing doing something with the product, like running some research test or running the pilot or expanding the pilot, we always had the data that had convinced us that that was a good decision.

Like we were stepping into the next phase of expansion that made sense.

And so I think we probably rarely proposed anything that seemed unwise like because we were holding such a high bar for quality ourselves and i think you know i suspect that went a long way so it's partly what i'm hearing is like uh take it step by step to prove this is actually working and partly be

confident it is working you're to yourself before you try to convince say the trust and safety team this is the way to go exactly uh is there any was Was there like a moment along that journey of just like, OK, here, it's like it shifted from no way this is a thing to OK, wow, let's actually consider this.

Or is it this very gradual process?

Whether other people were saying no way to.

Yeah, just internally of just like, OK, we're going to actually stop this trust and safety way of operating and instead rely on community notes.

So is there like a moment of like, OK, let's actually make that switch?

Or is that Elon actually?

Is that the big switch?

The biggest change there happened in X.

The biggest changes prior to that were just the decision to put this out there and, you know, and have it be operating at, you know, in public at first US wide scale.

But, yeah, then the big the bigger switches came in the X period.

I think even though there was original research before Birdwatch even started or community notes even started from external researchers showing that, you know, crowdsourced fact checkers can do, you know, lay people can do about as well as fact checkers.

And actually, the agreement rates were kind of similar between the groups.

Like, I think even though that research was out there, I think there were definitely a lot of people who didn't really believe it could work until it already worked.

basically prove it prove that it works and yeah that makes sense versus just a bunch of docs and strategy and thinking it's just like look it's actually working you can see for yourself yeah makes sense okay possibly last question uh we'll see what fractals of questions you guys bring up here uh i've

referenced this a couple times this uh incredible achievement of keeping a project alive through Jack and then I have this note and Kayvon running the show then and then Parag running Twitter and then Elon and then Linda taking over CO quite rare especially something this visible this impactful to everything

that X is any lessons or keys to that actually working of this project surviving throughout so many org changes and leaders it definitely has been a crazy time to be building something uh it's been fun uh the craziness has been entertaining um I think you know one one reason that perhaps the product

has has done so well and survived is the product itself the nature of the product itself it is designed to produce information that is found helpful by people who normally disagree and so even if you have CEOs or leaders who might disagree like there's a good chance actually they'll find it helpful

they'll be like wow, this thing does produce pretty useful output.

So I think there's something in the nature of the product itself that when people see it, whatever side they're on, left, right, whatever up, down, they're likely to find it pretty helpful.

So I do think that helps.

I also think the team executed really well.

We had ambitious goals that were exciting.

They solved a real problem.

This is a real problem that matters in the world.

at every step, you know, as we talked about the product needed to prove itself.

And, you know, we would make sure it proved itself and we would bring the results that convinced us and we would share those with people.

And so they would say, oh yeah, I agree.

It kind of proved itself.

Let's take the next leap.

And we've done that all along the way and we continue to operate that way.

and i think like that focus on the outcome and goal that matters and executing against it really helps like the team did not get distracted by much all through the period during which the acquisition happened like there was a lot of opportunity for distraction this team was shipping like every week

like we were super focused on the goal like let's make this thing work let's get these notes out there and um you know I think people saw that execution and and were excited to support it yeah like it's working why would we must have that and it's important and it keeps us from having to hire tens of thousands

of of people to fact check you know interesting thing about that is no one ever asked us or brought up or seemed to care about anything related to cost savings um in this process and i think that's like a pro like a an assumption people have outside the company that like this must have been a reason there

was interest in it but like that was never a goal it's not not at all why the project was started it's not why people were excited about the project and i think that's also you know for people outside who you don't see the conversations it's like kind of a heartening thing to know is that the focus was always

on solving the problem.

The other approach is even if you had 10 ,000 people doing it, like it, the real issue is that they don't work that well because they're not trusted or they don't scale or they're too slow.

And so, um, the goal was really always just, let's like help people stay informed at scale.

You know, let's build an internet, internet scale solution to an internet scale problem that people like.

Something I heard about you, Keith, when I was asking people about how this worked and why this worked so well is that they describe you with uh having a very low ego and that allowed you to give up this whole team and power the influence and just the name forget it whatever you want we'll call it community

that's great is there anything in there you can share of just like how you think about that and how important that is as a product leader to have a low ego um you know for me this this project i feel like i get to do community service with this project like my I like my I see my work is in service of the people

in the community and like that's what motivates me the only thing that I care about is delivering the outcome that the world finds helpful and so in some ways like project is is not been about like ego or results but it's like about truth seeking like let's find not truth in the sense of like what information but like

let's find out what's actually going to make this work um like how does it need to be how does it need to be structured what is it what should it be called like whatever is going to produce the best outcome is what we should do and um so i think you know i feel more attached to the product being helpful

than to anything else and so you know to whatever degree might seem like low ego is probably more a result of wanting to actually solve the problem and i think i think partly what i'm hearing is just if you win and succeed good things will happen so focus on that certainly satisfying things will happen

it's very satisfying to have people appreciate it satisfying that like people on the left and right you know love it it's satisfying that even people who receive notes love notes and reach out them and post them like that's amazing it feels it feels you know so good to have helped give people that and um

and yeah you know it's very motivating it's great reason to wake up in the morning it's absurd this has worked but it's also like of course this would work of course something like this should work it's like such internet it's of the internet you know that's why it works oh man where's community nets

going from here what should people look what's happening where is it going what's uh what's the future we're always working on you're basically more better notes faster so we want there's clearly opportunity to get more notes out there um we want to want them to stay as good or better than they are we

want to get them there faster so we're always working on like core product changes um to help deliver that like recently for example we um just released an update to what we call the community notes bat signal or the ability to request a community note so we anyone on x can say hey i think this post

needs a community note and now they can even add a source explaining why so that when a prospective writer sees that it's much easier for them to write a note um so we're always working on core things like that, core algorithm improvements.

I think there are also new frontiers that show a lot of potential.

AI and LLMs are one.

It's easy to imagine a lot of ways that AI could assist the people in this task they're doing of trying to get information out there quickly.

And maybe Jay should talk about the super notes work that we've done with some folks outside the company.

Yeah. So, I mean, one cool thing about having public data and code is that external researchers can collaborate with you.

And in this case, the super notes of this idea that we can basically take existing notes as input, existing proposed notes that aren't actually, you know, maybe they have some problem.

Maybe they have the whole part of the story.

maybe they're worded in kind of a biased way.

And basically take all these in, have an LLM generate a ton of different variants, and then basically make the simulated jury.

So to basically get a representative group of contributors for community notes who would be writing the note and try to predict based on their past ratings how they would rate these LLM generated notes.

And so this way you can actually, you know, rather than just like having an LLM write a note from scratch and hoping it's good, you can kind of like simulate the entire community notes rating process and explicitly create notes that are likely to be rated helpful by people.

So I think ideas like that are very promising for the future.

And it's a nice way that the elements and humans can work together.

I think like, obviously, you know, agents can can browse the web too and and and that's one way that uh you know you could imagine agents assisting humans is you know maybe maybe checking whether a source is actually supported by the note um or a note is actually supported by the source although then

you get into things like well uh you know are are people going to actually be as diligent you know right now i think raters are very diligent because they know just some community knows contributor wrote this like i better check this before i read it helpful but you know hopefully people you know we

can design things in a way such that people don't trust the output and actually verify it themselves before issuing a helpful rating yeah that is such an interesting area to explore where you want to avoid ai hallucinating sloppy slop versus make it easier and scale it even further what an interesting

challenge what's cool about this project in addition to this the ai element is that it's being done outside the company.

Like we talked earlier about like the open source transparency.

Like the key reason we made this all open source was so people could see how it works.

But the dream is actually that it's, it's not just that the contributions to the notes and ratings are from the people, but the dream is actually the product is built by the people.

Like what if the scoring algorithm were significantly or entirely written by the public?

Like that would be incredible.

And Super Notes is probably the first very substantial potential change in like the algorithm of the way it works that was coming kind of coming from the outside and plausibly could be part of the core so we'd love to see the product go in that direction as well sweet go super notes well guys the work you're

doing is tremendous I think this is every product person's dream I think to work on something like this small team lots of support lots of impact like just like innately interesting and so I think this is going to inspire a lot of people.

So let me just ask you, is there anything else you wanted to share?

Anything else you think might be helpful for folks to leave them with?

Sure, I guess one thing that I just thought was interesting over the course of working on this product is just there's, I think in a similar way to how retweets originally were not something like Jack came up with.

I think user just started doing it and then it became a core part of the product.

There's a huge way already in which there's just a lot of surprising things that people wanted to use community notes for that i don't think we really expected and it's it's kind of cool to see those uh you know uh user desires uh kind of emerge i think like one example you know i i guess we had always

been imagining um political uh type of misinformation but um for whatever reason there's like um you know a lot of people who love debating whether messier ronaldo got more goals um i guess uh it's kind of kind of a funny one uh there's a community moderation aspect right so like i think we also thought

that you know this would be specifically for um adding context to misleading or potentially misleading information but what you can see is that um there are some notes that um go beyond that um towards like calling out um content that they think is spammy or something um so i i think that's that's just

i guess another just another dimension in which community notes is a product that's like driven by the people itself that's so beautiful basically they're trying to keep twitter slash x uh healthy and they're just like no this should be taken down this tweet of spam yeah i love that uh is there an answer

on the messi versus who is the other ronaldo ronaldo okay uh is there like a definitive fact there Or is that just unknowable?

Yeah, I guess that's an interesting one because it's a case where raiders are actually very polarized.

I guess it actually kind of fits into the core algorithm where there's some people who are just diehard Messi fans or Ronaldo fans, just like they could be on politics.

So we actually specifically model that topic as well as some other topics so we can estimate people's opinion on that particular debate.

it's kind of kind of funny that something like that would emerge but i think that's the most controversial topic on x ronaldo versus messi that's a controversial one oh wow who knew okay uh keith is there anything you want to tell uh yeah you know community notes is cool itself but i think what it points

to about society is actually even bigger um you society often feels really polarized you hear people talk about it all the time like no one can ever agree on anything.

But actually like community note shows you people really can agree on quite a lot, even on super controversial topics related to politics and everything.

There's a lot of agreement.

That's why notes work.

And I think that's a really big reason for optimism about the world is that while it might feel polarized, there's probably like an 80 % set of people that agree on quite a lot of things.

And imagine if we could use the same kind of approaches we use with notes, but to find agreement on legislation or policies or things like that, that people want the government or the world to do.

Possibly we could get a lot more momentum behind these ideas that the people really want and everyone would be a lot happier.

Maybe 10 % of the people on the edges wouldn't be happy, but I bet there's a lot of agreement that we are not identifying.

And if we did it, we'd all be pretty happy.

So I don't know. I think it's easy for people to feel pessimistic about the world, but I think this product is a good reason to be optimistic about the future.

What an incredible way to end it.

I can also see Keith why people want to join you and work with you and work on this team.

Appreciate it. You do want to join.

We are hiring an ML engineer.

You get to work on these amazing problems with us and have a lot of fun.

So we're accepting applications x .com slash community notes.

Okay, great. I'm glad you get flooded uh guys thank you so much for doing this um is there anywhere other than that place to go off uh join the team as nmlml engineers there any other place you want to point people to either your socials or anything else i'm k coleman on x um hey please reach out if you

have any feedback or want to help us out whether you're you know want to work here or want to do something from the outside we'd love to talk yeah i'm at underscore jay baxter underscore at x uh yeah I think in particular, you know, besides just using community notes it would be great to, to get more

substantial contributions, you know, like pull requests collaborate on projects like super notes.

I think that's the most exciting type of stuff people do want to contribute.

Ship some code guys.

Yeah. That's amazing.

Guys. Thank you so much for doing this.

Thanks for having us, buddy.

Thank you so much. Bye everyone.

thank you so much for listening if you found this valuable you can subscribe to the show on apple podcasts spotify or your favorite podcast app also please consider giving us a rating or leaving a review as that really helps other listeners find the podcast you can find all past episodes or learn more

about the show at lenny's podcast .com see you in the next episode

[커뮤니티 노트: 인터넷의 진실을 재정의하는 집단 지성의 힘]-[An inside look at X’s Community Notes | Keith Coleman (VP of Product) and Jay Baxter (ML Lead)]

📋 Summary

커뮤니티 노트: 신뢰와 진실을 위한 새로운 패러다임

1. 커뮤니티 노트란 무엇인가?

2. 알고리즘의 핵심: '브리징 기반 합의(Bridging-based agreement)'

3. 투명성과 개방성: 핵심 철학

4. 사회적 영향과 미래: 오정보와의 전쟁

5. 결론: 인간에 대한 낙관론

🎯Key Sentences

📝Key Phrases

📖 Transcript