@lauren I think they ("we", since I work there) thought that the general public would distinguish language models from "AI" and that a bunch of "warning this is slop" messages would be enough.

Some bits of grey:

1. We've used language models for machine translation in the Content Translation tool for a decade, and probably (in a bit of hubris) consider ourselves somewhat expert in identifying and mitigating the biases inherent in that technology (biases in dozens of languages!). All translated content is human reviewed. We were giving conference talks on AI bias before that was cool.
2. We also use language models to help vandal fighters, and again have been doing so for a decade, they are controlled for bias and human reviewed, etc.
3. Historically all of our article summaries have been human generated. Not a lot of articles have summaries. Humans are slow. There are millions of articles in dozens of languages.
4. "Some folks at a conference" thought it would be interesting to make an opt-in experiment, to see if we could use what we know about responsible use of language models to make a summary tool. The experiment was opt-in and even if you opted in the summary was collapsed by default; I think it was also only shown if we didn't have a human-authored summary. Part of the experiment was to try to quantify usefulness, bias, etc.
5. Before the experiment was launched, folks cried AI and shut it down. (This should have been foreseen!)

I am no fan of generative AI, but language models in general have been a useful tool to triage vandalism, help translate content, help volunteers communicate across language barriers, etc. They also have biases we have studied extensively (eg "doctor" and "teacher" get translated with gendered language in languages with grammatical gender, to start a long long list). Especially in the translation use case, they have the potential to help alleviate systemic inequities by making more of our content accessible in minority languages. WMF is trying to figure out how to navigate in a world where bad actors and slop are doing their best to poison the well, and messaging technical subtleties is not one of its strong points.

That said, anything that looked that similar to Google's slop summaries of search results was obviously a PR disaster waiting to happen and I have no idea why no one on the C-team saw that trainwreck coming.