Are you talking about that godawful thing that I just clicked on in the "wheat" article, that the back button doesn't work on?
I'm pulling that out. Sorry, but "back button works" is a basic thing of Web functionality. I should not need to click a "return to article" button to get back where I was. Todd On Sat, Jul 11, 2026 at 8:32 AM James Heilman via Wikimedia-l < [email protected]> wrote: > English Wikipedia is a conservative organization / project as are many > other large versions of Wikipedia. Many stakeholders need to be convinced / > brought on board to make even relatively minor changes. Innovating within > smaller versions of Wikipedia or in other projects outside Wikipedia is > much easier. And successes can occasionally be brought into the larger > Wikipedias such as we did with Our World in Data interactive graphs... > > https://en.wikipedia.org/wiki/Wheat#Production_and_consumption > > We have now added 100s of these in various languages. And they are getting > thousands of plays a day. > > James > > On Sat, Jul 11, 2026 at 3:28 PM Charles Roberson via Wikimedia-l < > [email protected]> wrote: > >> Wikimedia-I used to be a premium listserve of high minded ideas about how >> to move the Foundation into the future. The past few months it has drifted >> into a lot of whining about AI with no real effort to accomplish anything >> or even plan to do so. >> >> - Charles >> >> On Sat, Jul 11, 2026 at 1:44 AM Todd Allen via Wikimedia-l < >> [email protected]> wrote: >> >>> We sure do know what a good AI strategy looks like for Wikipedia. No AI >>> on Wikipedia. >>> >>> We have not succeeded by being FaceGramTwitTube. We have succeeded by >>> not being like them. >>> >>> So, same here. No "latest and greatest". No AI on Wikipedia. Ever, for >>> any reason, period. Wikipedia is written by people for people. >>> >>> Todd >>> >>> On Fri, Jul 10, 2026 at 11:09 PM James Heilman via Wikimedia-l < >>> [email protected]> wrote: >>> >>>> What has motivated me to spend time writing Wikipedia over the years is >>>> writing for humans. The fact that the content is openly licensed and the >>>> work is supported by an NGO is also key. >>>> >>>> Personally i do not feel any motivation to write primarily for trillion >>>> dollar machines surrounded by venture capital folks hoping to make a >>>> killing. If the machines want to adapt to human facing content sure. >>>> >>>> The approaches you mention is how Healthline succeeded, they basically >>>> have dozens of articles covering the same topic just addressing it from a >>>> slightly different question. >>>> >>>> J >>>> >>>> >>>> Sent from Gmail Mobile >>>> >>>> On Fri, Jul 10, 2026 at 21:24 Alex Stinson via Wikimedia-l < >>>> [email protected]> wrote: >>>> >>>>> Forking this conversation, because I don't think we have a shared >>>>> framing of what we are competing for in a "Google" Zero landscape >>>>> dominated >>>>> by ChatBot/AI search style RAG citations (i.e. >>>>> https://en.wikipedia.org/wiki/Retrieval-augmented_generation). >>>>> >>>>> For the last 9 months, I've been examining how civil society content >>>>> should be showing up in AI search, and there is a missing perspective in >>>>> our "we will build it and they will come" approach to Wikipedia. I don't >>>>> think we can wait for the big tech companies or European regulatory bodies >>>>> to adopt a different idea of how RAG should work. Here is my take from >>>>> what I have been engaging with in the AIO/AEO/SEO space: >>>>> >>>>> *Wikipedia doesn't have content that is SEO/AEO optimized* >>>>> >>>>> Part of the problem, even if we did have an MCP server is that the >>>>> models (at least in my tracking), are pushing many citations away from >>>>> "factual" websites, towards "authoritative" websites. This authoritative >>>>> content includes: >>>>> >>>>> - Expert original, analysis that makes strong claims based on >>>>> facts (i.e. blog posts by authoritative companies or recently published >>>>> ScienceDirect articles) >>>>> - Content that has been updated recently, with the biggest "hot >>>>> takes" (i.e. I have monitored a couple of prompt pools where citations >>>>> shift to newer content after 2-3 months) >>>>> - Content that helps users make a decision between different >>>>> choices (i.e. review websites, etc) >>>>> >>>>> >>>>> This is following Google's longer-term push towards "human centered >>>>> and useful" content (sometimes called E-E-A-T an abbreviation of >>>>> experience, expertise, authoritativeness, and trustworthiness, in SEO >>>>> world). >>>>> https://developers.google.com/search/docs/fundamentals/creating-helpful-content >>>>> >>>>> >>>>> To win in an AI optimization battle -- its less about Wikipedia doing >>>>> well in the keyword search indexes that led to our content being visible >>>>> (which is why we have a reputation as a "fact checking" website) and more >>>>> about "winning" in the criteria for what makes a good RAG citation --- and >>>>> our content format, is the exact opposite of the EAAT criteria: >>>>> >>>>> - Wikipedia is not authoriative, but rather points to other >>>>> authorities >>>>> - We ground our content in anonymity instead of named experts or >>>>> instutional process/opinoin >>>>> - We rarely do original analysis instead summarizing the >>>>> experience and expertise of others, >>>>> - Alot of our content is out of date, and self-aware of its gaps >>>>> (i.e. maintenance tags), so also is likely to be undermining its own >>>>> trustworthiness >>>>> >>>>> >>>>> *All the data points to us being used, but without an official roundup >>>>> we are all talking in the dark about different assumed reputation losses* >>>>> >>>>> RAG unlike Google Search Indexing, seems to be using Wikipedia for a >>>>> fraction of a fraction of responses, favoring these other kinds of >>>>> sources: >>>>> >>>>> - Only 5% of AI overviews have Wikipedia in them: >>>>> https://ahrefs.com/blog/most-cited-domains-ai-overviews/ >>>>> - I have access to SERanking's corpus of prompt monitoring across >>>>> 5 models (ChatGPT, Perplexity, Google Models and they suggest that in >>>>> May >>>>> ~16% of prompts included Wikipdia, and in their most recent month >>>>> (June), >>>>> ~13% of prompts. SERankings corpus is probably the # 4 or 5 in >>>>> commercial >>>>> AIO data -- so could have gaps. >>>>> - Studies from earlier in the year put Wikipedia at about ~13% of >>>>> CHATGPT citations ( >>>>> >>>>> https://www.prnewswire.com/news-releases/wikipedia-and-reddit-now-drive-over-25-of-chatgpt-citations-in-the-us-new-5w-research-finds--wsj-nyt-and-bloomberg-do-not-appear-in-the-top-20-302768339.html >>>>> but chatgpt on average includes >20 sources in a response, compared to >>>>> googles 5-10 and doesn't expose it in the interface very well) >>>>> - Comparable "top" Websites, like Youtube, Reddit, and LinkedIn >>>>> tend to represent a greater % of content (in the SERanking data pool >>>>> nearly >>>>> 30% of responses had a Youtube Video cited for instance) >>>>> - Domain specific citation pools have pretty significant >>>>> differences in "which" sources are being called, with Wikipedia doing >>>>> well >>>>> on some prompt pools: https://generativepulse.ai/report/ >>>>> >>>>> >>>>> >>>>> >>>>> *RAG/AI search optimization focuses more on intent than keywords, and >>>>> we aren't very effective at serving intent, and we don't know where our >>>>> optimization options are* >>>>> What we need is an understanding of "which actual user reader behavior >>>>> are we seeking to serve?". In the past we were extremely lazy, because >>>>> keyword search always delivered Wikipedia as "a first". Now we need our >>>>> content to be more optimized for the kind of user curiosity driving their >>>>> use of a chatbot/search tool: >>>>> >>>>> - What percentage of prompts or AI searches are informational vs >>>>> opinion forming? Are we even a competitor for grounding opinion based >>>>> questions or only the informational ones? >>>>> - How many of the interactions are two or three steps down a chain >>>>> of more "specific" interactions with the chatbot and thus no longer >>>>> need >>>>> "general knowledge" information from Wikipedia, but rather the kinds of >>>>> stuff that we rely on our citations to provide ? >>>>> - How much are the AI companies optimizing for "sales" or >>>>> "addiction" rather than for leading users to reliable content? (I was >>>>> tracking a series of informational topics about food that (on ChatGPT >>>>> and >>>>> Google), kept wanting me to continue the conversation by *inviting >>>>> me to go to local hamburger restraunts)*. Do we even have a >>>>> reasonable chance to be in those searches? >>>>> - How much is geolocation forcing more and more responses into >>>>> "local" sources rather than "global" websites? In one dataset I >>>>> tracked, in >>>>> Global South countries citations were overwhelmingly to Facebook and >>>>> Instagram despite more authoritative academic, news and Wikipedia-type >>>>> sites in the same searches from the UK. >>>>> >>>>> >>>>> *We may need to radically change the "readable signals" on our content >>>>> pages, meaning changing the Manual of Style, Editing Practices, and AI >>>>> enabled enrichment.* >>>>> >>>>> If we are trying to market Wikipedia's content into AI interfaces, we >>>>> also can't do what most AI optimization/marketing agencies would suggest: >>>>> writing listicle/FAQ type content that closely matches the user-queries >>>>> that folks are giving the IA models (i.e. analysis like: >>>>> https://neilpatel.com/marketing-stats/trust-signals-ai-engines-reward-most/ >>>>> ). >>>>> >>>>> We would then have to experiment with other content types, that _no >>>>> longer look like the encyclopedia_. Or we would need to be reconfiguring >>>>> the Encyclopedic content to expose enrichments to paragraphs or sections >>>>> within the encyclopedia that pretty radically change editorial >>>>> assupmtions >>>>> and our Manual of Style (i.e. instead of simple 1-2 word section headings, >>>>> like "History" we may need intent-focused headings like "What is the >>>>> history of [x topic]?). >>>>> >>>>> If we want to compete in the shifting AI search landscape -- we would >>>>> need a lot more data from the Foundation on where we are succeeding or >>>>> not, >>>>> and then consider *_radically different_ *ways of exposing our >>>>> content in terms of treating RAG systems as a user that needs correct >>>>> paths >>>>> to Wikipedia pages. >>>>> >>>>> However, this doesn't necessarily need to change the *human reader >>>>> experience *, but would need to be about configuring the content >>>>> (beyond an MCP server or Enterpise APIs) *for an AI audience/consumer >>>>> experience -- *which I haven't seen addressed in any WMF publications >>>>> or community conversations. Without a firm theory of "What kind of >>>>> consumer >>>>> is an AI search agent/RAG index?" and "How does our content need to serve >>>>> that AI audience?" the editing community won't be able to adjust its >>>>> editing practices or weigh in on feature recommendations that make our >>>>> content "AI useful". >>>>> >>>>> As I have written elsewhere, I think there is a inherent audience for >>>>> editing/using the Wikis organically: >>>>> https://en.wikipedia.org/wiki/Wikipedia:Wikipedia_Signpost/2026-06-21/Op-ed >>>>> -- but its a different question than competing "with other information >>>>> sources" for AI as an audience. >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> On Fri, Jul 10, 2026 at 2:30 PM Steven Walling via Wikimedia-l < >>>>> [email protected]> wrote: >>>>> >>>>>> >>>>>> >>>>>> On Fri, Jul 10, 2026 at 9:52 AM Erik Moeller via Wikimedia-l < >>>>>> [email protected]> wrote: >>>>>> >>>>>>> On Fri, Jul 10, 2026 at 5:59 PM James Heilman via Wikimedia-l >>>>>>> <[email protected]> wrote: >>>>>>> >>>>>>> > Yah a search engine that actually gives real references that >>>>>>> supports the statements in question would be amazing. >>>>>>> >>>>>>> Almost like .. a Knowledge Engine. ;-) >>>>>>> >>>>>> >>>>>> Is the WMF building an MCP server to connect Wikipedia and Wikidata >>>>>> directly to Gemini, Claude, and ChatGPT? This is a more lightweight, >>>>>> backdoor way to leverage the audience of those platforms but present >>>>>> structured outputs to AI chats for users based on Wikimedia knowledge. If >>>>>> we did so, we could present citations within the returned responses to >>>>>> users, and those platforms make it transparent to the user when they are >>>>>> calling a particular tool. >>>>>> >>>>>> Steven Walling >>>>>> >>>>>> Sadly, the only realistic path I see there would be through >>>>>>> acquisition, and even if that was financially feasible, you'd begin >>>>>>> by >>>>>>> inheriting a lot of corporate practices that aren't really consistent >>>>>>> with Wikimedia values. >>>>>>> >>>>>>> But perhaps there is a middle ground where Wikimedia seeks to define >>>>>>> more clearly the terms of engagement that it wants with search >>>>>>> engines >>>>>>> (clear attribution, clear and correct references, calls-to-edit, >>>>>>> etc.), and then finds and recognizes search partners who implement >>>>>>> those. To Luis' point, that need not be done by WMF. >>>>>>> >>>>>>> Warmly, >>>>>>> >>>>>>> Erik >>>>>>> _______________________________________________ >>>>>>> Wikimedia-l mailing list -- [email protected], >>>>>>> guidelines at: >>>>>>> https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and >>>>>>> https://meta.wikimedia.org/wiki/Wikimedia-l >>>>>>> Public archives at >>>>>>> https://lists.wikimedia.org/hyperkitty/list/[email protected]/message/HNDPDZBBDMILF7WGMUBVJVIAZYQ7OXOS/ >>>>>>> To unsubscribe send an email to >>>>>>> [email protected] >>>>>> >>>>>> _______________________________________________ >>>>>> Wikimedia-l mailing list -- [email protected], >>>>>> guidelines at: >>>>>> https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and >>>>>> https://meta.wikimedia.org/wiki/Wikimedia-l >>>>>> Public archives at >>>>>> https://lists.wikimedia.org/hyperkitty/list/[email protected]/message/IUDAKJRN5EQT5CCWEEYQXKDSVXCDBXR6/ >>>>>> To unsubscribe send an email to [email protected] >>>>> >>>>> _______________________________________________ >>>>> Wikimedia-l mailing list -- [email protected], >>>>> guidelines at: >>>>> https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and >>>>> https://meta.wikimedia.org/wiki/Wikimedia-l >>>>> Public archives at >>>>> https://lists.wikimedia.org/hyperkitty/list/[email protected]/message/YODBKTCLA2XJC24Y23I2SUN3PUYA4QXE/ >>>>> To unsubscribe send an email to [email protected] >>>> >>>> _______________________________________________ >>>> Wikimedia-l mailing list -- [email protected], >>>> guidelines at: https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines >>>> and https://meta.wikimedia.org/wiki/Wikimedia-l >>>> Public archives at >>>> https://lists.wikimedia.org/hyperkitty/list/[email protected]/message/5MPMZGZ2MXLLHER3NTNUS6KHIMAXIIBD/ >>>> To unsubscribe send an email to [email protected] >>> >>> _______________________________________________ >>> Wikimedia-l mailing list -- [email protected], guidelines >>> at: https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and >>> https://meta.wikimedia.org/wiki/Wikimedia-l >>> Public archives at >>> https://lists.wikimedia.org/hyperkitty/list/[email protected]/message/QAGHRXXTGSXKVFOALBRQHP5G27NUIFDD/ >>> To unsubscribe send an email to [email protected] >> >> _______________________________________________ >> Wikimedia-l mailing list -- [email protected], guidelines >> at: https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and >> https://meta.wikimedia.org/wiki/Wikimedia-l >> Public archives at >> https://lists.wikimedia.org/hyperkitty/list/[email protected]/message/6RKSJMWMVUHUUVV7WGKPOCOHCN4NBQK4/ >> To unsubscribe send an email to [email protected] > > > > -- > James Heilman > MD, CCFP-EM, Wikipedian > _______________________________________________ > Wikimedia-l mailing list -- [email protected], guidelines > at: https://meta.wikimedia.org/wiki/Mailing_lists/Guidelines and > https://meta.wikimedia.org/wiki/Wikimedia-l > Public archives at > https://lists.wikimedia.org/hyperkitty/list/[email protected]/message/FRGCURSOK3KPMT3UWZFOR6Z4TMZFE7KF/ > To unsubscribe send an email to [email protected]
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