How Wikipedia Will Survive in the Age of AI (With Wikipedia’s CTO Selena Deckelmann)

0:04Hello, and welcome to the 4forMedia podcast, where we bring you unparalleled access to hidden worlds, both online and IRL. 4-4 Media is a journalist-founded company and needs your support. To subscribe, go to 4-4media.co. As well as bonus content every single week, subscribers also get access to additional episodes where we respond to their best comments. And they get early access to our interview series, too. Gain access to that content at 4-4media.co. This week, we're joined by Selena Dekelman. Selena is the Chief Product and Technology Officer at the Wikimedia Foundation, the nonprofit organization that operates Wikipedia.

0:45That means Selena oversees the technical infrastructure and product strategy for one of the most visited sites in the world and one of the most comprehensive repositories of human knowledge ever assembled. Wikipedia is turning 25 this month, so I wanted to talk to Selena about how Wikipedia works and how it plans to continue to work in the age of generative AI.

1:12Everyone knows what Wikipedia is, but something that I've encountered in my writing is that it's actually harder to describe comprehensively than you might think. It's a website, it's a technology, it's a community. I was wondering, what is your best definition of what Wikipedia is and what do you do there? That's a great question. I find that too, honestly. So I'm the chief product and technology officer at the Wikimedia Foundation, and we support Wikipedia and a number of sister projects like Commons, Wikidata and Wiktionary. I think when I think about it, I think about the websites and the number of page views that we're serving.

2:00So we're serving like 15 billion page views a month, about 1.5 billion unique devices. and the work that I do is to support 250 ,000 editors who are creating and maintaining over 65 million articles across about 300 languages, more than 300 languages. And in that work, when I think about what it is, we're unique, you know, we still have our own data centers. You know, there's stuff that we do in the cloud, but for the size of organization that we are, we're pretty small, it's about 650 people and my team's maybe like half of that. There's even fewer developers. We're really small for a top 10 website and we're using a lot of open source software, mostly open source software.

2:47And some of the staff that I work with, including the people that I work the closest with, they've been around since the very beginning. So we're here to talk about, you know, 25 years of this project. And there are people who, you know, At the same time as they were working on racking servers for the first versions of the website, they were running paper routes and writing their theses. And this is a global community of supporters, developers, editors from the very beginning as well. So it's just pretty incredible what that started out as and kind of the dream of creating a web page with a button that just says edit and letting the whole internet click that button and being like, okay, let's see what happens with that.

3:40If you told someone you were going to do that from the very beginning, I don't think they would have thought that would work very well, but it has. And when I think about what it is, it's that button, it's that edit button that anyone can press. It's all of these people who have worked together to produce the corpus of knowledge that exists now. And it's the principles and processes that those volunteers have created together that creates such an incredibly reliable, verifiable, transparent system for knowledge. Yeah, that's how I would describe it. I love that description of a website with an edit button.

4:23But I would add to that that it is a website with an edit button, but good. Because a lot of the internet is basically what you're saying, but bad. And I think something that I want to get into in our conversation is what has been done on your end to make sure that it's still a productive, net positive force in the world where so many others have failed. But before we get to that, something that I always find pretty interesting and complicated is the line between Wikipedia, the community-led, editor-led project and the Wikimedia Foundation. How do you explain where one begins and the other ends?

5:07Well, from a content creation perspective, I see a very clear line. You know, the volunteers, they self-organize and they create and edit the content. And it's just an incredible system because like I said before, we put up this webpage, anybody gets to click the edit button. And from the sound of that, it doesn't really sound like it's going to work. But it works because of the people who contribute. They're really good people, like you said. They've worked together to create a system that's designed to improve that content and add to it over time, not be 100 % perfect from the very beginning.

5:52It's designed for iterative improvement. And there's a lot of grace that goes into that and assumptions of good faith among the people who are choosing to contribute. You know, when I think about this, I think about like the many individuals and that's how they think of themselves as well. You know, it's not just like one community of people. It's like all of these individuals doing things. and they go by funny handles. Like there's this guy named Hurricane Hink. He wrote an article about a typhoon that's really important to my origin story was Typhoon Pamela that hit Guam in 1976. And he works with a community of people in a group, a wiki project that is called Project Tropical Cyclone.

6:32And they're part of this international group. It's, you know, when I think about one of the incredible aspects of Wikipedia, it's this these different groups of people that form gigantic basically newsrooms that are like clearing houses for all of the things that are being published on certain topics at any point in time like when Queen Elizabeth it was apparent that you know she was probably going to pass away pretty soon a group of these editors got together they named themselves I think the project was named London Bridge and they got together and they made lists of all the articles that were going to change.

7:08They were all like ready to like come and start just immediately making the changes as the news became available. It's just, it's just a very surprisingly like fast and accurate system for getting that information to the public, you know, in what the public feels is like a very trustworthy way. So yeah, so that, that's, that's like how I think about, you know, what the volunteers are and what they're responsible for and what they do. And from the foundation side, you know, we're accountable for the infrastructure to support all of that. So we enable help with like fundraising, legal partnerships.

7:44You know, in my case, I'm providing the technical infrastructure that enables all that global collaboration. And it's a little bit different, you know, from other platforms in that we also have a lot of volunteers who contribute to the technical infrastructure. And our guess is that maybe there's like 50 ,000 of these that have contributed from the beginning. You know, there may be more, maybe less. I don't have an exact number on that. But there's probably about 10 ,000 of them that are active worldwide today. And so unlike the content, though, I am ultimately responsible for the technical systems, including those data centers I talked about before.

8:23I guess two questions. Because I know you interact, right? There has to be a line of communication between the foundation and the editors. I'm wondering where's that line of communication for you? Where do you interact with them? And have you ever experienced tension between these two separate, but obviously cooperative groups? Yeah, there are many, many lines of communication. So there are some primary ones, but I want to share just how I felt when I started my job. So I've been here, you know, a little over three years. And when I started, I just went on, you know, different pages about the foundation and Wikipedia and searched for different communication channels because I was like, oh, maybe I should subscribe to a few mailing lists.

9:14You know, maybe I should get on some IRC channels because I assumed that people were using IRC and things like that at the time. And what I discovered is that there were thousands, thousands and thousands of channels, you know, in all sorts of communication mediums like Telegram is a very popular medium. Now there's many discords. There's lots of mailing lists. So many, many different communication channels for like rapid and open and very frank communication between people. So that's like one aspect of it. I definitely have like more like official channels, you know. So we created this thing called the Product and Technology Advisory Council.

9:53And that's a group of, you know, longtime, very trusted volunteers and trusted in terms of their reputation in the communities who come together with me and talk about ways that we can improve the infrastructure together. And one of the ways that we've talked about it, and when I say infrastructure, it's both the technical things, but also the ways that we do things. So like, how do we communicate about experiments that we're running? That's been an important topic recently. And so we come together and talk to them about what would be the best way for us to do that. And they make recommendations because the ways that people communicate on Wiki, that's what we call it.

10:33On Wiki is like when you type a message into a talk page or some other forum where you're actually trying to interact with a person instead of writing an article. And so when we're on wiki, there are different ways, you know, to share things. There's different forums that are more comfortable or more recognized than others. And so we like talk to the other human beings to find out, you know, where those places are and, you know, what the best way it would be, you know, what is the best way for us to introduce a new topic? Yeah, I think that that pretty accurately describes the broad scope of it.

11:10And I think, you know, it's a human system. And it is not without conflict. so you know and i i i was like thinking about before you know before i came on the the kinds of research that has been done on wikipedia these are so much you know it's like an incredible system because it's so open and all of the edits that have been done by all of the different editors they're like available to look at you know and you can see the time stamps you can see like what the person edited, you can see whether it was reverted. So there's all this like very rich information there. And one of the more fascinating pieces of research that I've come across, it was from 2017 and it was trying to study what happens when different people of different like political persuasion.

12:00So like, you know, in the US, if you've got a Democrat or Republican, what happens if they come together and edit on a particular topic together? And so what this research says is that over time, when folks do that, when they express those political points of view on Wikipedia and then they edit together, their editing becomes more neutral over time, likely as a result of being exposed to these different ideas. I think that's really incredible because there's not very many social media platforms or internet platforms where that is the case, right? Like the algorithms might like push you more toward a particular point of view, but here you're interacting with other human beings.

12:44And, and as a result, it seems like people get more moderate. And I, I think that's like such an amazing finding, you know, this is like a very simple tool, you know, it's an article with a talk page and then a set of policies that say that we're going to make pages about a topic not from a particular point of view, but as a summary of different points of view. And that tool, I think, has resulted in something quite special and unique. Yeah, it's an amazing finding and it's very congruous with the time, obviously. Yeah. And this is not something I want to get into, but I feel like that's an obvious reason that people on the extreme ends of the political spectrum are often upset with Wikipedia is because it is by, I don't know if by design, but the result is something kind of in the middle or kind of neutral.

13:42And obviously, if you're on an extreme political end, that is not something you like. Sorry, I completely forgot to follow up. How is the Cyclone Group related to your origin story? They're great. They're so amazing. They still like, they do such amazing coverage. Yeah, I, they have multiple different projects, but there was a hurricane that happened in Florida. I'm sorry, I don't have like the name of it, like top of mind, but like last year I did a little check-in on them and they were all working together. Hurricane Hank actually had like edited the page, but there were other people, you know, that had been mentored into taking the lead, But they respond immediately to disasters.

14:23And I think what's so helpful about that kind of work, you know, is that it's a clearinghouse for accurate information, you know, and they're helping sift through a lot of different reports that might be coming out that, you know, are or are not accurate or are not reliable. and they find the best and summarize it there. And I think that that human judgment in those moments is like incredibly valuable, especially right now. And I think as different news sources become more or less reliable, it's helpful to have a group of people that are commenting on that. And there are other ways to find out whether different news sources are the best in the moment.

15:09But I do think that Wikipedia editors have done a pretty good job. of keeping up with that as times have changed. So in 2023, he wrote a great post about AI and Wikipedia. I'm going to oversimplify here. So feel free to expand on any point if you want or correct me. But my reading of it is that essentially your message was that Wikipedia is inherently a human-led project. This is something I think has already emerged from our conversation. but that Wikipedia already uses machine learning in some ways and that it may be useful in the future. So this is 2023, given the rapid development of AI, that kind of feels like a long time ago.

15:58So I just wanted to check in and ask, has your perspective changed at all since then? And is that an accurate summation of how you feel about AI and Wikipedia? I think it's an accurate summation. There are some things that have definitely changed in that time. I went back and looked at that post as I do pretty regularly to see if there's, should I substantially revise it? I think we're probably about due, not necessarily for a substantial revision, but just like a reflection on what I and my colleagues thought then and what we think now. I think the heart of what I said then, you know, about sustainability, about equity, about transparency, those qualities remaining crucial, you know, to information on the Internet and the spread of knowledge on the Internet.

16:49Those things are so important. And that part of it hasn't changed. And I still believe that we have a sustainability crisis on our hands. And a thing that I hope for and advocate for is that companies that are, you know, creating new AI systems, some of them just incredible, you know, doing amazing things, advances in medicine and reducing toil for people who are trying to detect cancer. I mean, there's so many incredible applications of the technology that are obviously good for society. So I think that that is going to continue to be true. And the systems for gathering knowledge, I think, are going to continue to improve.

17:34And they already are much better than they were when I wrote that post. But the sustainability of human contributions to those systems, that is what I think we have not solved. And that's the question everyone needs to grapple with. I think Wikipedia has done a really good job, first of all, providing a mission and a purpose that people feel so good about contributing to. They want to come and share what they know. They want to collaborate with other people on doing that. And they're continuing to do it. So that's good. And then for these other systems, we have to think about what is the way that we're going to motivate people to contribute to the common good here.

18:22because the web, when it was originally conceived, it was built on links, which is, it builds that reciprocity into the system inherently. That was the web. Like an agentic AI system, I'm not really sure where the reciprocity is. That's the big question. How are we going to think about that system in the same way that we conceived the web? And I think it's totally possible. Human beings conceived the web, conceived the internet, created this system, created the rules around it, created all of the enterprises around it. The nonprofit systems and the profit systems all got created on top of that.

19:01And I think this is the question for the AI age. How do we also create systems of reciprocity that are for the common good at the same time as we have these commercial systems? And I think it's a little unbalanced right now. Say more about that. What do you think about agentic AI that kind of messes with the incentives or removes this link system you mentioned? Is it because you're locked into one specific LLM? Why do you think that has that impact? Well, if we just look at the link system, there's an assumption that a person is going to follow those links to learn more. Right. And in the agentic system, that is not the assumption.

19:47You know, it's very convenient and I know why it's compelling. And it's useful. You know, I use AI systems both to like vibe code things also to ask it, you know, what is the best like way that I can arrange my office to make it more pleasing and more, you know, whatever. How many more plants should I add? But what is not there is so I just gathered all of this information, but where did it come from? Sometimes, you know, that over time, what I have seen with, you know, chatbots in particular, I'm not seeing it as much with the agents, but you see the need to share the links, you know, because people want to verify is that information correct.

20:32they want to feel I would guess like the the producers of those systems want to help people feel like they can trust the you know the the content that's produced and if I compare it to what's evolved you know in wikipedia over time there's all these requirements you know when when you create an article you are required to offer citations you know and that is one of the ways that educators, you know, look to Wikipedia. They don't say to kids, go quote Wikipedia. They say, go to Wikipedia and look at all of those sources at the bottom of every article. Learn from those, you know, quote from those, you know, read the article to get a sense of this topic, but then go to those sources.

21:17And I think that's like a fundamental challenge. Like the reciprocity of the web is also built into Wikipedia. But, you know, how are we going to do that? And I'm not here to like mandate that it's links. You know, like, I don't think that there's only one way to create systems like this. But I do think we need to put some like real imaginative thought into what that's going to be. Because what we want is for people to continue to contribute to incredible projects like Wikipedia. We want them to be motivated to do so, so that the value, you know, of human knowledge creation continues to be part of these systems, right?

21:58Because, you know, there's another study that I just, it's only a couple years old. It's from 2023. I guess that's three years now. So there's a study that was done about the pile, you know, this is a source of training data. And some researchers, they looked at what happens when you remove different things from the pile. And how does the model respond differently? What does it produce that's different? And when you remove Wikipedia, the responses suddenly become much more toxic. And I think that's so interesting. What is it? And it'd be fascinating to dig even further into that and be like, why?

22:41You know, why exactly? I mean, I have my theories about why I think it's a really well written, high quality, neutral source of information. I think that's why. But I think there's more to know, you know, about that. I think there's so much to know. I think we haven't devoted enough time or energy to this idea about reciprocity because in the end, like these AI models, they are dependent on human generated content to know new things. And that's either through training or through accessing new content that's produced through agents. And that's going to continue to be important no matter what.

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27:59Yeah, I should mention, I don't have the article in front of me, but I did write a few months ago about the foundation noting that the different chatbots appear to be sending less referral traffic to Wikipedia directly. And that is a concern because, as you mentioned, that is kind of reducing the pool of potential editors that we need in order to keep the fire burning, to keep the flame alive. And it does mention in the post that the foundation is thinking about and talking to the AI companies about how we might be able to improve that situation. I'm wondering, generally, do you think OpenAI, Anthropic, Google, are they able to be good stewards or good partners in this project?