Keith Coleman

We built Community Notes because we wanted to build a better informed world. And as it scales to more parts of the internet, that means more people have access to accurate information.

Yeah, so a really important principle of the program is that all posts are eligible. That means posts from heads of state [and] posts from our company can get noted. As Elon likes to point out, his posts get noted.

It regularly identifies AI-generated imagery. [There has] been a ton of that recently with the Iran conflict. It [has] detected deepfake audio of world leaders. It covers lighter subjects like entertainment, fashion, etc.

And as you can see up here, we’ve even had multiple notes on both recent White House administrations. And at least in one case, the White House actually took down the posts [and] issued an updated statement.

And you can imagine there was a person, a random person on the internet, [who] wrote that note. You know, this isn’t a famous person. They went out there, saw the White House said something wrong, typed in this note, put it up there, and then suddenly, leaders of the free world changed their public statement. That’s like a superpower for people. So you can see why they're motivated to contribute.

I mean, the origin, for me, goes back to 2016. I was just a Twitter user then. I was following the 2016 election. There were three televised debates that year, but every day, there was a debate on Twitter. So that’s where I was following. That’s where the world was following. I remember getting a lot of good information, but it was also hard to tell what was true. And I was thinking, just sitting on the outside, thinking like: How is the world going to solve this problem? How are we going to do this in a way that works, and that people feel is fair amidst polarization?

So then fast-forward three years. I was working at Twitter at that point, and the industry had tried a lot of stuff by then. Facebook had built a huge fact-checking program. Twitter was working with fact-checkers. And we also had internal teams that would try to review posts and decide whether they were or [were] not misleading.

And there were a bunch of issues with it. It was just very clear these solutions were not solving the problem. There were issues with speed. So typical fact checks, just to put it in perspective, were often coming back in two to four days, which is like, infinity in internet time. Scale was an issue. Typically, people could review, I don’t know, [an] order of 10 posts or topics a day. And even if you could solve those, trust was the fundamental issue. There were just a lot of people who did not want, or trust, tech companies to be deciding what was or was not accurate.

And so, I was managing a team at the time, handed that off and just went to go prototype crazy new ideas, one of which became Community Notes.

Yeah, so emails like that, calls or whatever, they do come in. Fortunately, the answer is really simple: we have no override button. So if you're not happy with a note, you need to take it up with the people.

And this [was] kind of a crazy idea when we started. We went into a room full of trusted safety people and we’re like, “Hey, so the notes that show are going to be the ones that the people decide, and we can’t take it down.”

There's no veto. And they’re like, “What? Are you serious? What if there's a bad note?" But I think the point was if it’s the tech company’s opinion, why is anyone going to trust it?

It needs to be the people's opinion. And so we stuck to that principle. Everyone got behind it. And we have no way of changing the status of a note. Which is wonderful.

Yeah, I think one other thing to mention about this graph is it's kind of a big deal that this happens organically. People often assume the world is very polarized -- certainly it feels very polarized.

But [the] people here, they’re just making a choice where they see a post. They see a correction, and they’re like, “Things are wrong. I'm just not going to share it." And that's happening across the political spectrum. And we’ve seen that pattern again and again.

When we first were designing the product, we did interviews with hundreds of people, left and right. And it was really obvious that most people just want to know what's going on in the world. They know they're consuming incorrect stuff. They just want to sift through it. And this is just showing that in action. When given information, they're going to try to make a good decision.

I think people often assume, man, it must be tough to work in the space of misleading information. You must get sad all the time, whatever. Actually, I feel very optimistic working on it because we see there’s quite a lot of agreement, and people are actually quite reasonable.

I hope, it seems like it's lower than it might feel.

Yeah. The idea is can we have humans and AI co-write these things together, co-create them together? And does that allow us to do this at a much faster speed and larger scale? What you’re seeing on the screen here is an example of what that looks like. This is new.

If there’s demand for a note, like people are requesting a note on a post, AI will take a first shot at it. Humans can write too, but AI will take a shot. And in this case, this is based on a real example, the AI thought this video was from 2017 -- and it turns out it wasn't.

So humans go in there and they’re like, “Hey, actually, this is from 2022 in Ukraine.” And a bunch of people rate it and they make these suggested improvements. They can also leave suggestions on style or tone. So they can say, “Hey, I think this source is biased” or "I think you should use a primary source. It's going to be more trustworthy." And then the AI takes that, regenerates a note and usually gets it right.

And what's cool about this is first, you get a better note on this post people care about. But two, all of those corrections, all those suggestions are training data that you can feed back into the AI. So you can make it less likely to make that mistake again. You can make it better at researching in the first place. And also you can make it more neutral, less biased. So all these human suggestions make better notes, and they make better AI.

Yeah, it's cool.

So definitely in the last six weeks or so, with the Iran conflict, we've seen the biggest surge in synthetic media that I've seen, at least in the kind of misleading info space. And I will say like, we're on the frontier here. So this is the highest-scale, highest-speed solution that exists. These are new problems, so we don’t know what’s going to work. We can’t guarantee the problem will be solved, but I think there’s a bunch of reasons to be optimistic.

For that problem, like [the] synthetic media surge, we can both scale up the corrections, and we can both change the fundamental incentives and dynamics of the system. So in terms of scaling corrections, we talked about AI. Just to put some numbers on that, in the last four months alone, we've doubled the number of notes that are showing on X. So that’s not trivial for a scaled service -- 2X in four months -- I think there's clearly headroom on that. Is it 10X, 100X? But there's clearly headroom to grow.

The other thing on the incentive side, one of the reasons people post these things is they can make money off of it through creative revenue-sharing programs. And so we've recently put into place some changes to the policies there where, if your post is noted, you can't make money off it. Also, if you post AI-generated footage of a war or conflict and you do not clearly call it out, you are suspended from the revenue-sharing program for three months. If you do it again, you're suspended forever. That’s kind of a big deal. Those will shape the underlying motivations people have.

Yes, we are building this. This is an awesome future. So we have a pilot running, what you're seeing on the screen is what this looks like. The idea in Community Notes, we find, [is] kind of like corrections or context that's helpful to people from different points of view. What if we could find the ideas or opinions that are liked by people from different points of view?

And then when it happens in the pilot program, you see what you're seeing on the screen here. The post will just get a call out saying "liked by people from different perspectives." And we see this: people were very happy to see Delta not allow Congress to skip the TSA line until TSA was funded. Yeah, you're among millions of people who also feel this way. And we see this agreement across a lot of topics, [even] things that you think of as controversial. We see it across immigration, across the economy, taxes, international conflicts, etc. There really is a lot of agreement out there, not on everything, but there's quite a bit of it.

And the concept is if we can identify that, [then] we don’t need to boost this to start -- just to show people when there's agreement on something. First of all, I think they'll find it interesting, it's a curiosity. Second, it might incentivize more of that. Like maybe people will try to speak more in a way where they can find that agreement. And get more momentum behind those ideas.

So where my head always goes is imagine for one session of Congress, everyone just focused on delivering where there was agreement, whether it’s immigration, taxes, whatever, I think people would be stoked.

There's a lot of agreement on these topics. If all we did was pursue the areas of agreement, I think people would be pretty happy with the direction the world was going. And so my hope is, with programs like this, if we can identify common ground at internet scale, it'll make it a lot easier to create a future that humanity likes. And so hopefully we can help with that.