from the keep-my-name-out-of-your-llm dept

Over the weekend, I noticed Andy Baio publish on Bluesky an amusing experiment in response to Mark Pattern posting about how the identify “David Mayer” seems to interrupt ChatGPT:

The “David Mayer” problem bought a good bit of consideration in some corners of the media, as numerous individuals tried to determine what was occurring. Fairly shortly, individuals began to show up a small checklist of different names that broke ChatGPT in an identical means:

  • Brian Hood
  • Jonathan Turley
  • Jonathan Zittrain
  • David Faber
  • David Mayer
  • Guido Scorza

I really knew about Brian Hood, and had meant to jot down about him some time again, however by no means bought round to it. A 12 months and a half in the past, a commenter right here at Techdirt had posted a few times about the truth that ChatGPT broke on “Brian Hood.” That was a few month after Brian Hood, an Australian mayor, threatened to sue OpenAI for defamation, after somebody generated some false statements about Hood.

OpenAI’s obvious “answer” was to hardcode ChatGPT to interrupt on sure names like “Brian Hood.” After I tried to generate textual content about Brian Hood, utilizing an identical technique to Andy Baio’s check above, I bought this error:

There was widespread hypothesis on-line about why these particular names are blocked. A fairly comprehensive Reddit post explores the possible causes every individual ended up on ChatGPT’s blocklist.

There are lots of David Mayers, however one possible perpetrator is a UK-based American theater historian who made news a few years ago when terrorist watch lists confused him with a Chechen ISIS member who generally glided by the identify “David Mayer.” As of Monday after I was writing this text, the arduous coding on the identify “David Mayer” had been eliminated, although the explanations for which might be unclear.

Jonathan Turley and Jonathan Zittrain are each high-profile professors (although one is nutty and one may be very considerate). Turley freaked out last year (across the identical time Brian Hood did) when he claimed that somebody generated false details about him through ChatGPT.

Not like the others on the checklist, with Zittrain there’s no such path of freaking out or elevating alarms about AI-generated content material. Zittrain is a Harvard professor and the School Director on the Berkman Klein Heart for Web and Society at Harvard. He writes rather a lot concerning the issues of the web although (his ebook The Future of the Internet: And How to Stop It is value studying, even when a bit old-fashioned). He’s, apparently, writing an identical ebook about his concerns regarding AI agents, so maybe that triggered it? For what it’s value, Zittrain additionally appears to don’t know why he’s on the checklist. He hasn’t threatened to sue or demanded his identify be blocked.

Guido Scorza, an Italian information safety skilled, wrote on ExTwitter final 12 months about the best way to use the GDPR’s problematic “proper to be forgotten” to delete all the information ChatGPT had on him. That is one thing that doesn’t fairly make sense, provided that it’s not a database storing info on him. However, it seems that the way in which OpenAI handled that deletion request was to only… blocklist his identify. Straightforward means out, and so on., and so on.

Nobody appears to have any concept why David Faber is on the checklist, but it surely might definitely be one other GDPR proper to be forgotten request.

Whereas I used to be ending up this publish, I noticed that Benj Edwards at Ars Technica wrote a similar exploration of the topic, although he falsely claims he “is aware of why” these names are blocked, and his reporting doesn’t reveal way more than the identical hypothesis others have.

Nonetheless, all of that is form of foolish. Exhausting coding names that break ChatGPT would be the least pricey means for AI corporations to keep away from nuisance authorized threats, but it surely’s hardly sustainable, scalable or (importantly), wise.

LLMs are instruments. Like most instruments, the focus of liability for misuse should fall on the users, not the instrument. Customers have to be taught that the output of LLMs is probably not correct and shouldn’t be relied upon as factual. Many individuals know this, however clearly, it still trips up some people.

If somebody takes hallucinating output and publishes it or does one thing else with it with out first checking to see if it’s professional, the legal responsibility ought to fall on that one that did not do the right due diligence and relied on a fantasy-making machine to inform the reality.

However, after all, for these providers, convincing the world of those ideas is rather a lot more durable than simply saying “fuck it, take away the loud threatening complainers.” However that form of answer can’t final.

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Firms: openai


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