User-generated content is at a turning point. With generative AI models cranking out tons of slop, content repositories are being polluted with low-quality, often useless material. No website is more vulnerable than Wikipedia, the open-source reference site populated entirely with articles created (and revised) by users. How Wikipedia is handling the issue — in light of its strict governance policies — is worth watching, especially for organizations that also rely on user-generated content.

Links from this episode:

• Wikipedia Editors Adopt ‘Speedy Deletion’ Policy for AI Slop Articles


• How Wikipedia is fighting AI slop content


• From the technology community on Reddit: Volunteers fight to keep ‘AI slop’ off Wikipedia


• Wikipedia:WikiProject AI Cleanup


• Wikipedia loses challenge against Online Safety Act verification rules


• Wikipedia can challenge Online Safety Act if strictest rules apply to it, says judge

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Special thanks to Jay Moonah for the opening and closing music.

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Disclaimer: The opinions expressed in this podcast are Shel’s and Neville’s and do not reflect the views of their employers and/or clients.

Raw Transcript:

Shel Holtz (00:00 )

Hi everybody, and welcome to episode number 477 of For Immediate Release. I’m Shel Holtz.

@nevillehobson (00:08 )

And I’m Neville Hobson. Wikipedia has long been held up as one of the internet success stories, a vast collaborative knowledge project that has largely resisted the decline and disorder we’ve seen on so many other platforms. But it’s now facing a new kind of threat, the flood of AI generated content. Editors have a name for it, not just editors by the way, we do as well. It’s called AI slop. And it’s becoming harder to manage as large language models make it easy.

to churn out articles that look convincing on the surface, but are riddled with fabricated citations, clumsy phrasing, or even remnants of chat bot prompts like as a large language model. Until now, the process of removing bad articles from Wikipedia has relied on long discussions within the volunteer editor community to build consensus, sometimes lasting weeks or more. That pace is no match for the volume of junk AI can generate.

So Wikipedia has now introduced a new defense, a speedy deletion policy that lets administrators immediately remove articles if they clearly bear the hallmarks of AI generation and contain bogus references. It’s a pragmatic fix, they say, not perfect, but enough to stem the tide and signal that unreviewed AI content has no place in an encyclopedia built on human verification and trust. This development is more than just an internal housekeeping matter.

It highlights the broader challenge of how open platforms can adapt to the scale and speed of generative AI without losing their integrity. And it comes at a moment when Wikipedia is under pressure from another front, regulation. Just this month, it lost a legal challenge to the UK’s online Safety Act, a ruling that raises concerns about whether its volunteer editors could be exposed to identity checks or new liabilities. The court left some doors open for future challenges, but the signal is clear.

the rights and responsibilities of platforms like Wikipedia are being redrawn in real time. Put together these two stories, the fight against AI slop and the battle with regulators shows us that even the most resilient online communities are entering a period of profound change. And that makes Wikipedia a fascinating case study for what lies ahead for all digital knowledge platforms. For communicators, these developments at Wikipedia matter deeply. They touch on questions of credibility.

how we can trust the information we rely on and share, and on the growing role of regulation in shaping how online platforms operate. And there are other implications too, from reputation risks when organizations are misrepresented, to the lessons in governance that communicators can draw from how Wikipedia responds. So, Shail, there’s a lot here for communicators to grapple with. What do you see as the most pressing for communicators right now?

Shel Holtz (02:52 )

Well, I think the most pressing is being able to trust the content that you see is accurate and authentic and able to be used in whatever project you’re using it for. And Wikipedia, we know based on how it’s configured, has always been a good source for accurate information because it is community edited, errors are usually caught.

We have talked about in past episodes, the fact that more obscure articles can have inaccuracies that will sit for a long time because nobody reads it, especially it’s not read by people who would have the right information and correct it. But by and large, it is a self-correcting mechanism based on community, which is great. It does seem that the shoe is on the other foot here because when Wikipedia first launched,

I’m sure you’ll recall that schools and businesses banned it. You can’t use this, you can’t trust it. It’s written by regular people and not professional encyclopedia authors. Therefore, you’re going to be marked down if you use Wikipedia, it’s banned. And they fought that fight for a long time and finally became a recognized authoritative site. And here they are now banning something new.

that we’re still trying to grapple with. We do need to grapple with it. The AI slop issue is certainly an issue. I worry that they’re going to pick up false positives here. Some of the hallmarks of AI writing are also hallmarks of writing. I mean, if I hear one more person say, an dash is absolutely a sign that it was written by AI. I’m gonna throw my computer out the window.

I’ve been using dashes my entire career. I was using dashes back when I was doing part-time typesetting to make extra money when I was in college. And dashes are routine. There is nothing about them that makes them a hallmark of AI. That is ridiculous. But we are going to see some legit articles tossed out with the slop. The other thing is some of the slop may have promise. It may be

the kernel of a good article, and this is a community platform, and wouldn’t people be able to go in and say, wow, this is really badly written, I yeah, yeah, I may have done this, but there’s not an article on this topic yet, so I have expertise, I’m gonna go in and start to clean this up. It’s a conundrum, what are you gonna do at this point? We haven’t had the time to develop the kinds of solutions to this issue that might take root.

And yet the volume of AI slop is huge. The number of people producing it is equally large. And you have to do something. So I think it’s trial and error at this point to see what works. And there will be some negative fallout from some of these actions. But you got to try stuff to take it to the next level and try the next thing.

@nevillehobson (05:52 )

Yeah,

I think there’s a what I see is a is a really big issue generally that this highlights and part of it is based on my own experience of editing Wikipedia articles in a couple of cases for an organization working with people like butler inc. Bill Butler has been an interview guest on this podcast a few times, which is

The speed of things, the one memorable thing that stays in my mind about using Wikipedia or trying to progress change or addition is the humongous length of time it takes with the volunteer editor community. The defense typically is, well, they’re volunteers, they’re not full-time, they’re not employees, they’re not dedicated, they say you’ve got to be patient, they’re doing it for their own free will to help things. I get all that, I’m a volunteer myself in many other areas, but…

That’s great. But as they themselves are saying, things are moving at light speed with AI slop generation, you can’t afford to have three to four weeks where you you the the person editing is asked the community, is this good? Are you okay with this? What else? And three weeks go by before you get a reply. And often you don’t you have to nudge and so