Interview with Lane Rasberry on Wikipedia and its Usefulness

Hello, I'm Ian Peterman, host of the Conscious Design Podcast. And today I'm really excited to have Lane with the University of Virginia here to talk about Wikipedia and some of the going on behind the scenes and what actually makes it a tool that we all get to use daily for free and enjoy and actually get good information out of it. So with that, one of the first things we wanted to talk about was the community around Wikipedia, because it's a large community and we don't all know who's the magic behind the scenes. So Lane, it's really great to have you here and take it away.

Thanks for having me, Ian. Of course I like talking about Wikipedia. Of course I like talking about the wiki community. Maybe the first thing that I'll say is that there is a Wikipedia community. Wikipedia, as you know, it's a general reference resource. It presents information for free and all sorts of topics, and that information actually comes from humans. So it's not as if there's a Wikipedia content corporation somewhere that's putting this content into Wikipedia. It's a volunteer community which has had a thoughtful development process. There's certain things that the community's chosen to do and certain things the community's chosen to not do or not decide. This has resulted in the community developing in a certain way, coming up with a culture, and that's why I'm really comfortable calling it a community because there is a culture. And the wiki community celebrates its 20th anniversary this year. Wikipedia has been around for 20 years, and at this point There's a lot that's stable about it. It's— in times past, people ask questions like, certainly in the beginning, is Wikipedia even stable? Is it going to exist in a few years? And now that it's 20 years old, that's a milestone which marks that while many other major internet platforms and online communities have risen, peaked, and fallen, we can say that Wikipedia's stable in these ways, less stable in these other ways, and this is what the community's about.

Yeah, it's amazing that it's a community like that has been able to last.

As you said, 20 years is a long time in internet years, let alone volunteer internet years. I feel it adds a multiplier to it to last that long, which is impressive.

Can you talk a little bit more about like What's—

what in your— you've been part of it for a long time. So what are the factors you think, from what you've observed, that has helped that to continue and grow? Because that's not an easy feat to keep a group of people going like that.

I'll say that there's been a lot of academic research and journalism and a certain amount of internal surveying in the Wikipedia community, Wikipedia platform, To try to determine what makes it work. And there's a lot of prognostication on the internet in general. Certainly, there's been major internet companies that have invested tens of millions or hundreds of millions of dollars saying, this is the wave of the future. Many of these have been wrong. It's challenging to predict these kind of things. And if I give you my opinion, that might differ from some other people's opinion, but I do have some opinions. And there's 3 things that I'll mention. that I think make the Wikipedia community successful and sustainable. The first one is that from the beginning, always, the Wikipedia community has said that if you're, if you're part of this community, we're here to build a general reference work. We're not here to talk about the subject of the encyclopedia. That is, if there's an article on a subject, you don't debate the subject itself. What you do is you talk about how to survey library resources and summarize them and then present it in a neutral way in the Wikipedia article. We're all about building this, this encyclopedia or this general reference work. So anyone who's not there to either build the encyclopedia or talk about the administration of the encyclopedia, they're, they're not a part of the wiki community. That, that's someone on the outside. There's a social theory behind this. There was an educational academic named Wenger who had this concept called a community of practice. And what this means is that you can't separate an activity from knowledge of the activity. Another way to say this is it's not possible to understand Wikipedia without actually editing Wikipedia and experiencing Wikipedia. So although we have lots of help manuals and documentation, although there's been so much research, to really understand what we're doing, you have to actually practice it. You have to actually have the experience of sharing general reference information. And that's a, that's a common experience among all the, all the Wikipedia community members. So as we're getting together and sharing this information, a second trait that we have among us, and this has been critical from the beginning, is we enforce civility. There's a code of conduct in Wikipedia. So whereas in other online communities, sometimes any sort of behavior is acceptable, We won't mention names. Yeah, we won't mention names, and we won't mention the kinds of behavior that happen online. But in Wikipedia, we treat each other with respect. There's no name-calling, there's no insults. Of course, this happens in Wikipedia. There's conflicts of all kinds. Inside Wikipedia, we have dispute resolution processes. We even have a justice system. If somebody disputes the dispute resolution process, or if there is name-calling, or if there is a personal conflict between 2 people, we have different ways of mediating these kinds of things. of things. And of course, there's criticisms about Wikipedia's justice system. I think it's pretty good, especially in comparison to other places on the internet. And I think it gives a lot of satisfaction, and people at least know that it's in place and at least know you're supposed to behave when you're on Wikipedia. And I think just even knowing that this rule is in place, that's a strong motivator that keeps the community together, even when people observe failures or even when there's a failure in an individual instance. The third thing I'm going to mention, so I said that there's a justice system in place, and that also means that there's enforcers, there's different people who do this. But part of the governance philosophy of Wikipedia, it's anarchism. Wikipedia, it's not quite an anarchy, it's not quite a democracy. Anytime you have an online community, there's going to be multiple governance systems in place. But when I say it's an anarchy, I mean that there's no hierarchy, there's no leader, there's no king or queen or regent of Wikipedia. There's no person who sits in a position of power, and because of that position of power, people automatically defer to them because of the role. We try to avoid appointing anybody with power. Of course, sometimes it happens, even, even in anarchist systems. But we try to make our decisions based on community consensus. Every time that there's some kind of dispute or some kind of policy issue that needs to happen, we invite everybody to the conversation. We discard any, any rank. Of course, You know, people have reputations. Some people have stronger voices and better articulate themselves. But whenever possible, we try to let newcomers and diverse voices into a conversation on equal ground with everybody else. And this, this plays out over and over again in every kind of decision that we say there's no leaders, there's no one person that if you convince that person, you get your way. It's community at every decision-making process.

That seems like a good system. Obviously, it's worked and it seems attractive, right? It seems attractive to especially people that are trying to research and put together information. Having a neutral system as much as possible would facilitate that. So that seems like a very— now that you're saying it out loud, it's like, oh, that's a very logical decision. That's right in line. But obviously, as we have many examples online, that's not necessarily the logical choice that we all, that we all reach towards.

That's right. Every online community is going to have some kind of government system. They're going to have conduct expectations, and they have certain kinds of activity that's allowed and not allowed. And this is the way that Wikipedia determined itself. And when I say governance, there's a lot of gaps in this. So if you say something like it's an anarchist system and we're not gonna have leaders, then you might wonder, well, what, what do you have? Of course we have laws. In anarchist systems, you can still have laws, you can still have rules, you just avoid this, this like leadership, leadership role whenever you can. You make it ad hoc if you need it, and it comes to pass. So different websites try different things, and this is, this is my view of how Wikipedia does things.

Got it. And so with this, we talked a little bit about consumer advocacy as some of the data that you work with and information, and I feel like that ties into the community because it's very much like what you're talking about and how you— how the Wikipedia community has come around is very— everyone's involved. You have— there is no rank, right?

Everybody—

That's right.

At the table, everybody gets to See the same information, hear the same information, and then make a decision based on that information. And I feel like that, that really ties into customer advocacy because that's kind of what that is, is saying, hey, the customer should, should be able to see the data and hear the data and then make a decision. So how does that— how has that path gone with Wikipedia and customer advocacy and And how do you feel that's going?

Well, this idea of advocating for the end user, the reader, the audience, the customer, the consumer, however you want to track these kind of people, that's a major draw of why anyone would want to volunteer their time contributing to Wikipedia. So since there are few or no paid content contributors, Perhaps I'm one. I'm actually employed by a university to facilitate the entry of content into the Wikipedia platform, but that's fairly uncommon. When there's so much volunteer recruitment and you have people in so many countries in the world volunteering their time in Wikipedia, they're doing this for a number of reasons. A common reason is that they feel like it has impact. They feel like they're sharing information that would either satisfy someone like them or bring some kind of benefit into the world. And if we weren't continually thinking of the end user, then we wouldn't have this kind of brand or reputation or image that we're on the consumer side. And one can't say this about other platforms. So in Wikipedia, supposing there's criticism of a— whatever you want to say, a politician, a concept, a policy position, a product, a company. If somebody brings this content into Wikipedia, it's not as if the empowered party, the politician or the corporation, can go to Wikipedia and look for the leader that will give them a back channel to remove or change this content or add their own view. Whenever we have a deliberation process about what editorial stance Wikipedia should have for something, this goes through the community, and there is no place to reach the Wikipedia editors except in public, in the discussion forum, in the notes which describe the development of the article. And every time someone makes an editorial change to a Wikipedia article, this is logged as public data saying this change was proposed on this day and here was the community response to it. And this kind of transparency and this kind of commitment that there's no leaders and that anyone can edit whatever they want within the rules, and the rules are very firm, they say what sort, what sort of content's acceptable and what sort of content is, is not acceptable. People get trust in this, and then that makes them comfortable in volunteering their time to commit to the system. So for example, you could have difficult situations where, say, corporations are on one side of an issue and you have advocacy groups on another side of the issue. And in the Wikipedia article covering these topics, of course, the Wikipedia article is going to present the corporate perspective. It's going to cite the publications that have talked about the corporate perspective and summarize them and present those. But if there's advocacy topics that are in minority publications, which are still not fringe, that are still in the, in the media ecosystem by respectable experts, then The Wikipedia community always puts these opposing positions next to each other and says, here's what this side says, here's what this side says. Maybe there's even a third, third perspective on the issue, and we present all these with equal standing. Whereas if you look at other sorts of media, social media, for example, you can pay more money to promote certain, certain views or have your views circulate more easily. Within these other media platforms, and there's certain other organizations, entities that for whatever reason have better access to mainstream media. They pull different levers of power, and their views get circulated through mass media, whereas in Wikipedia we don't have respect for those, those kind of authoritative decrees that this information should go out, and this is what people should be discussing. In Wikipedia, we, we try to summarize whatever expert statements there are without regard to the degree of money that one expert has versus another expert.

Right, which is one of the, one of the key differences that I think most people see is that the Wikipedia page is not— as many people try to figure out how to edit their own pages and things like that.

Sure.

It's not possible. It's, it's, there's checks and balances, and the whole picture is at least as, you know, as, as much as humans can do. We add in that information is all added in, which is, makes it a thorn in some people's side and, and great for others, but it's as neutral as possible, which I think is quite a feat to, to achieve.

When you can.

There's a lot of institutional or infrastructure bias in Wikipedia. One of the obvious biases is supposing you have an advocacy perspective that's backed by well-funded corporations, then in the media ecosystem, you'll find a lot of publications that are advocating for their view because they're putting content out. Wikipedia is not an original creator of knowledge. We define ourselves as an encyclopedia or as a summary reference resource, which means rather than doing journalism or rather doing original research or making judgments about what's right or wrong, we look for existing publications, summarize those, and then cite the sources. So there's going to be some perspectives that are very well funded, very easy to find in the media ecosystem, very well articulated, as well articulated as a statement can be with with infinite money or near limitless money. And then there's gonna be certain perspectives that don't appear in the media ecosystem because they're less funded. And if that perspective isn't already published, then Wikipedia is not gonna do the journalism or research to publish it. It means that perspective will not be in Wikipedia. And it's possible to find what seems like a controversy where either one side or the other won't show up. Like, for example, there's certain drug controversies where patient groups will be publishing a lot about it, and then the pharma company benefits by not participating in the conversation. So it might seem like there would be a conflict between patients advocating for drug safety and a pharma company defending itself, but you can see the, the well-resourced player sometimes not wanting to participate in the conversation because if they participate, it's just problems for them. More commonly, though, you see the opposite, where there's some kind of local or community or subject matter expert hero who has something that's very important to say, and they either have in-person supporters or they have a fan base online in social media. But they're not covered by journalism or research. What they have to say has never actually appeared in third-party media, so their following is based on what they've said and what they publish themselves, which is considered primary, primary information. And Wikipedia doesn't interpret primary information. So if you have these kind of statements, they don't migrate into Wikipedia. We exclude them until and unless someone presents these in third-party publication. That's, that's a very common bias.

Okay, so that's a— because you're—

is there You know, the logic behind that? Like, what, what makes— right, is it like primary, anybody can say anything pretty much, and that runs a risk of misinformation? Or like, what, what is that kind of logic process to exclude primary and rely on tertiary?

There's, there's a few processes. One is just as you said, as a primary source, people can say anything. And even if they're a subject matter expert, you don't know if they're speaking— I don't know what the phrase— ex cathedra, like the Pope. The Pope can casually say something, but if he's sitting in his chair giving an official proclamation, it's considered infallible and ex cathedra. There's not this kind of formality with someone tweeting something out. If they, if they go on Twitter and then they say something, we don't know if that's an official statement in their expert capacity. They're not expecting an interrogation. We just don't interpret primary sources. So that's, that's one thing. If someone's speaking offhandedly, we just don't want to make an assessment about how, how serious they took this. Another thing is we can just question, if something's so important, then why is it that there's only one person in the world who's spoken about it? Why hasn't it ever been covered by someone else? And that's a bit unfair because we have situations like In, in— we're in the United States right now, but for example, in India, there's entire palace complexes, entire, entire temples, large ruins. It's obviously big buildings from another era, Golden Age of India, that have never been featured in any publication. And somebody might say, well, there's this, there's this obvious big, big building here. It's centuries old. People have been talking about it for many generations. Can it be in Wikipedia? And we say, well, In the past 500 years, has anyone ever written about this thing? And it seems to just be an omission, but you can have something as real as a palace in the middle of a city that just hasn't been the subject of journalism or research that anyone can find. And so Wikipedia is going to have the bias of excluding that. That's a very odd thing, a very odd bias for a publication to have, because just about any other kind of encyclopedia or any other kind of travel guide or what have you, Yeah. Wouldn't be shy about taking pictures of something and saying that it exists. But Wikipedia has an aversion to doing these kinds of things. So you have odd situations like this that arise.

That would be very odd to me, especially if we live in one of those cities. You're like, hey, it's right next to my house. I see it every day. But doesn't— according to Wikipedia, does not exist.

I'm not going to name names about this, but just suppose Supposing you're the, the mayor or the head of a large metropolitan area, like you go through an election, and I'm talking about a very big city, and you get elected mayor, but you've never been featured in journalism. No one's ever interviewed you. There was no announcement of the election. Can that even happen? And I'm telling you, yeah, it happens. And it's kind of weird when—

Wow.

Someone gets in these positions. It's like, Can you imagine the US presidential election? Like someone gets elected and no one's ever heard of the people.

So basically, if nobody, if nobody wrote an article, if we went to the next election and no journalist wrote anything at all, Wikipedia wouldn't record that there was an election.

Because we have nothing to cite. Yeah. And I'm not saying that this is common, but there's, there's some odd cases where somebody or something seems like a very prominent, very important event. And yet, for whatever reason, in no language, in no media can we find records of the thing ever happening. And, and this gives us pause every time.

Well, not every system's perfect. So you're gonna, you're gonna find glitches eventually. Um, well, with, with all this, this kind of wraps into the next thing we want to talk about, data ethics. So we talked about that, like the data ethics of Wikipedia and kind of in general, this is something that you, you work in. How does that play into all of this? Because there's obviously a lot of information. There's even, you know, medical information. Not that you want to diagnose yourself off of Wikipedia, but how, how does that process look? What, what do you guys go through? And tell us a little bit about that data ethics side, which I feel is important.

Sure, I'll start by saying I'm, I'm at the University of Virginia. I'm in something called the School of Data Science. Within the School of Data Science, I'm in a department or division called the Center for Ethics and Justice. And what I do more than anything else in Wikipedia is share health and medical information in Wikipedia, including medical data. So you mentioned medical information. No, you shouldn't diagnose yourself with Wikipedia. However, I assure you that a lot of people use information in Wikipedia to inform their medical choices and healthcare decisions and the way that they talk with their friends and families and, and doctors when they're trying to learn about medical issues. Concerning ethics in general, the world is changing quickly. People have a lot more access to data. People have a lot more access to the tools which interpret data. Different people are going to have different things to say about this. I'm going to just draw a line to say what's, what's the line of where did the ethics go. And the line is when somebody, anybody, makes a tool and makes a product, uses data for anything, is the benefit going to entities which have more power and enriching them further? typically at the expense of people who have less power, or is the benefit going to disempowered, less empowered people with less agency? And the trend in data science, data development, in a lot of ways, undoubtedly many tools are increasing the overall wealth and the access to resources that people have in general. But when it comes time to divide the resources, most of the resources tend to go to people who are already wealthy, and new data products tend to take resources away, you know, despite maybe giving them other resources, but tend to, tend to take the resources that get divided away from the less empowered people. So there's a lot of ways to explore data ethics in Wikipedia. Of course, we're trying to benefit everybody. I'm not saying that Wikipedia has an agenda, but perhaps sometimes If somebody has volunteer time to give, they're going to give more of their volunteer time to communities which are underrepresented, less able, and people tend to volunteer less time in Wikipedia to, say, improve the reputation of corporations, these kinds of things. So that's the way it works. So besides just considering who does a tool benefit, when I'm talking about data, let me say the difference between data and other kinds of information. And different people are going to have different definitions of what that is, but when I'm talking about data, when we're talking about data in Wikipedia, data is the information that a machine would read, a computer would read, and the prose or images or non-data is what's human readable. So anytime anyone's curating data in Wikipedia, what they're expecting to do is to optimize information for circulation through perhaps commercial products. Google or Bing or Apple Siri, Amazon's Alexa, all of these slurp up data out of Wikipedia. And if someone asks them a question, they're— they have an easier time reading the structured data rather than the prose of the text of the encyclopedia or interpreting images. Doing machine recognition of what the images are. Other things that you can do with data are data visualizations. So for example, there's been a lot of experiments in the past year in, in Wikipedia dumping data into various repositories in the Wikipedia platform, using them to generate graphs about COVID infection rates, vaccination rates, putting these things on maps and charts and timelines. So whereas it would be very tedious to have a statistician interpret all these things and then have a graphic designer generate the appropriate charts for humans to read. If you can pull in the data and you say, well, what's good for Sweden is good for the United States and good for India, you, you develop a way of interpreting common datasets for one place, and then it tends to be reusable at scale in Wikipedia. Wikipedia is the encyclopedia. I'm going to say this also. There's a family of related projects. We call them all Wikimedia projects.

Okay.

And I'll give you an example of a few. So Wikipedia is the text of the encyclopedia. We have something called Wikimedia Commons, which is where we store all the images. So for example, if you have a biography, and you have that biography in multiple languages, often you can just use the same images— image across languages to profile the person. And so we store the images in one place and then reuse them in different language projects. So we have that. There's something called Wikidata, and that also is often language indifferent, meaning if you have numbers— this person was born on this day, they died on this day, This was— this is the population of a city in a certain time and place. You put the population in Wikidata, and then for the, for the 300 languages of Wikipedia that exist, then that population can just appear as a number because numbers, numbers translate very easily, right? So by and by, we're trying to convert more information in Wikipedia articles to structured data, and this assists with translation. It exists with— assists with modeling. It assists with easy, easier access to these kinds of things. But yes, different, different issues come up. Biases in the data, different levels of access to data, and we're continually having to discuss what's, what's right and wrong with data in Wikipedia and what's right and wrong with data in the broader world as people are considering new data products outside of Wikipedia.

Right. Well, that's interesting how you're breaking it up. So you're The Wikipedia that we think of, right? The average user enters Wikipedia and really they're using multiple products without knowing it because of how you're having to structure it for search engines to be able to actually pull up the information and find that and call it out.

That's exactly right. And I said that there's a Wikipedia community and there is a lot of commonality in the Wikipedia community. But the skill set and the, the hobby interest to do research and to write text articles, that's, that's in Wikipedia. There's another skill set of people who like taking photographs. So if you see photographs in Wikipedia, those are donated photographs or collected online somehow that we've vetted the copyright for. And doing photography and Managing the provenance of copyright. Those are 2 skill sets too. That all happens in Wikimedia Commons and not by the people who are doing writing and research for Wikipedia. And then Wikidata is yet another skill set, because just because you're good at taking pictures and just because you're good at writing text for articles doesn't mean you're good at importing and wrangling datasets. So Wikidata has its own community, and there's other communities as well. But they share these common values. Again, no leaders, follow the rules, be civil, these things.

Oh, that's awesome. That's awesome. Yeah, I wasn't personally aware that it was multiple sets of people because the thought that most people have is like, oh, I go here and I read it and there's like a group of mysterious people just entering in everything all at once and like one person could enter the the photos and the text and, and, you know, somehow magic happens with the code and it just works. But it makes way more sense that there's these levels and different expertise and interest, right? The photographer probably isn't a heavy data coder. I mean, maybe they are.

Maybe, yes, there's overlap, sure.

But not every photographer wants to do code or write. So that makes a lot more, a lot more sense to have it grouped out into specialties.

The easiest way that I can explain it is if you imagine a large publishing house, maybe a newspaper that's also producing video and has a website. All of these roles exist in Wikipedia except for the actual original research, like the journalism. We don't send journalists out to get the original stories, but every other role that has to do with publishing that you'd find in a conventional publishing house, it exists in Wikipedia. We do other things as well, but it's a large organization with specialization of roles. Specialization without leadership and authority, of course.

Right, right.

No leadership and no journalists.

Yes, yes, yes.

And then you have Wikipedia. Mm-hmm.

Yes, you get it. Yes.

So the last thing we wanted to talk about, I wanted to mention a little bit, is the sustainability side, because that's Articles in that realm are definitely— it's one that are debated, right? People debate about it. So there is, I feel like especially right now, there's a certain level of community and ethics around it and having to curate that information really carefully just because it's a hot topic. So how has that been? And working through that and how is it— it obviously wasn't as hot of a topic, right? It's something that's become more and more focused on by people. So how does that work into being able to tell the information and also having a change in kind of popularity?

There, there's no one in Wikipedia who dictates what everybody's going to do. It's not as if someone can say, you, you guys go do this one thing. People propose ideas, and if it's a popular idea, if people want to volunteer their time doing it, then that's what they do. I'm telling you that sustainability is one of the more popular ideas in Wikipedia. It gets discussed in many communities, many languages, many cultures. I think it's a candidate for the most popular group of content development in Wikipedia and the most organization. That's not to say it's huge, and that's not to say that everyone participates in it, but it's popular and recurring and it gets a lot of attention. People engage with the concept of sustainability in different ways. The way that many people would think of as content creation. In Wikipedia, the encyclopedia, people coordinate themselves in subject matter interest groups. We call these wiki projects. So there's a wiki project climate change, and anyone who is interested in monitoring all the Wikipedia articles for climate change, they can go to this wiki project, talk with other people who are monitoring and developing these articles. and they can coordinate. Sustainability means more than climate change, though. For example, I— one of the articles that I worked on was the concept of antibiotic use in livestock production. If you don't know about this idea, I'll explain it briefly. Antibiotics, they treat disease in humans. You can use the same antibiotics in farm animals. And if you give farm animals antibiotics continuously, considering their lifespans and their lifestyles, they tend to resist illness more. But at the same time, if you're continually feeding these animals antibiotics, there's drawbacks too. It builds up something called antibiotic resistance. The antibiotics get less effective over time. So when I edited this article, I tried to do a survey of what information exists on this. And I found a lot of advocacy groups who are saying we need to mind antibiotic resistance, we don't want this to be a thing. There's a right way and a wrong way to, to use antibiotics, even in animals. It shouldn't be completely unregulated globally, because if you have one country that doesn't have regulation on this, they can actually change the environment of, of bacteria for the entire world and build up different kinds of antibiotic resistance. So I added whatever information I could, and this is an example of an advocacy issue that somebody might pick up on Wikipedia and how they share it. The idea is I edited this article because I wanted other people who were looking for information on antibiotic resistance to be able to find it online. That was my wish. And for them to also see who's ever published on this, who are the experts in the field, these kinds of things. What I couldn't find was any sources to cite from the livestock industry, the meat production industry. So this is, this is one of the examples where you have consumer advocacy groups who talk about an issue, and there's no debate with the other side of the issue. If you want to know what the livestock industry thinks about it, well, one of the things they think about it is they're not going to be caught in a panel debate with the consumer advocacy side of it, despite this, this being an issue and what it is. And you find other perspectives like the veterinary perspective, which isn't on one side or the other necessarily. They're just looking for appropriate use in animal care and protection of the antibiotics, you know, to benefit industry and also to advocate for the other side. So these kind of things happen. This is content creation. Another way that we could look at sustainability is meta-sustainability. What is the sustainability of Wikipedia and the Wikipedia platform itself? We've considered things like what is the carbon footprint from an environmental perspective of running the Wikipedia servers? And we ask for those. There's an organization called the Wikimedia Foundation that pays for the servers, operates things, does things that the community of volunteers wouldn't do, and they give this kind of report. So we have these reports. These are, you could say, celebrated by the community. We really respect this kind of transparency in many things, not just for carbon footprint. But when these kind of transparency reports come out, community discusses them among ourselves and says, how do we interpret these numbers? What do they mean? Are these the kind of numbers that we want? What should we think of these kind of reports? Other kinds of sustainability are sustainability of perspective. So supposing we're going to be talking about a global issue, maybe we're talking about climate change, maybe we're talking about sustainability from some other perspective, but How do we get diverse voices in the room so that not everything we're saying is the perspective of, say, editors in the United States? When you have a sustainability discussion, should you get local community stakeholders to write about these things in their own language for their own community, or is it just necessary? Is there really no way to do that? And we regret the colonialism, but if we don't publish this information somehow right now, then we can't foresee this information being available in these communities in, in the coming years, and it's urgent to share this information right now. So we have some people who say we need to translate climate change information in as many languages as possible, and what the source content we have is from the international community, the Intergovernmental Panel on Climate Change, the United Nations Organization, which, which publishes in limited languages and mostly English. Or we can, we can wait for people to spontaneously get online and also become acclimated to Wikipedia culture and also produce volunteers and also write the content. Sometimes we just have to make judgments. And of course, we never want to just send content out outside of the review of the culture in which it's going to be used. But on the other hand, there's a lot of tough decisions to be made, especially when there's a timer on sustainability.

Right. Well, that brings up an interesting point with timing, timing of information, right? In that there's that balance. And most mainstream media, it's very much, oh, we're gonna push this journalist when researched it. And now we have an article sometimes as quickly as a week or less, depending on, you know, we have same-day hourly updates depending on how active an event is. So it's an interesting— when you're trying to go through the Wikipedia approach and make sure that you're referencing information and you're a little bit more researched, you're not doing that primary work. Mm-hmm. I hadn't really thought about the fact that you kind of have to balance that out of where— when do we actually push stuff out and try to make something happen because it is so relevant versus using the more measured approach that's generally taken and can be, right? Stone temples sitting around for thousands of years, they're not going anywhere. You can document that at any time.

Yes.

And so that's an interesting balance and place to be that I hadn't thought about in the Wikipedia structure of how do you, how do you get that information out and retain the integrity that you've had with what you put out so far. So that's an interesting point.

The fundamental building block of Wikipedia, and this is the best way I can explain it briefly, is that if there's information in Wikipedia for every claim You have to cite a reliable source. We're continually matching claims with citations. So if we have sources to cite and then somebody to actually summarize them without doing plagiarism or copyright violation and putting it in context of Wikipedia article, then that's how we build Wikipedia, one sentence and citation at a time.

Right, which takes— it takes longer than just sitting there and I'm going to write an article. Here you go. 2 hours later, I have 1,000 words. It's ready for publication, but not cited to anything at all.

Certainly journalism has it— has its place too. Journalists have a magical skill set, which we respect a lot. It's irreplaceable. It's very unfortunate that journalism is in decline for different reasons around the world because of competition from social media and new media, computer-generated media. That's another data ethics problem. Should we just let machines write the news that humans are supposed to be reading? And increasingly, this is happening as well. Right. But Wikipedia relies on journalists interpreting things. And if we don't have good journalism, we're not going to have good Wikipedia articles.

Yeah, I can't imagine using Twitter bots as your primary source of information as they scan the internet for things. So yeah, I would— I see that as an ecosystem you tap into and really, really need to thrive. So yeah, this has been, this has been really great. It's been very informational learning about the Wikipedia ecosystem that lives behind it and the people that it takes. It's, you know, not just a few people sitting there typing away, which I think is good to Good for people to know. It's— there's systems in place and there's, there's a lot more to it and a lot of thought that gets put into it. Um, and I personally have been using it for a long time, many other people as well. So it's good to, good to see kind of behind the curtains a little bit and see what's, what's happening. Um, other than, you know, obviously everyone can go to Wikipedia and want to volunteer and become part of, part of this, obviously join. Is there anything else that you would like to share right now?

I, I'll just say I, I won't tell anybody that Wikipedia editing is certainly for you. There's a lot of people who try it and it's just not for them, so I'm not going to have an open call saying everybody should go edit Wikipedia. However, however, I'll say this: if there's anybody who's wiki-curious, You can go to Wikipedia, create an account, try adding one sentence and one citation. Wikipedia has been around for 20 years. Had you done this 20 years ago, you'd remember it to this day. I meet people who said, I edited Wikipedia one time 10 years ago and I still remember my experience. So if you're expecting that there's going to be a free and open media ecosystem that persists, maybe Wikipedia will last another 20 years, maybe it's going to be replaced by some project. That's, that's its legacy. But if you, if you want to give it a try, a good, a good first try would be just adding one sentence and one citation. Go into, read a reputable news source, find an article, find something to cite, and then try to, try to get that sentence and citation in Wikipedia. If you do that, you'll remember and you'll have that community of practice understanding of how Wikipedia works that you can't get otherwise.

That was a great suggestion. Good way to dip your toe and, and get to know it.

And then if you don't like it, that's why you're not committing to a whole, whole article.

So you can, you can back out gracefully and move on. So perfect. Well, thank you, Lane. I really appreciate your time being here on the podcast. And thank you.

Thanks for having me, Ian.