The comments do not seem to be addressing something very important: > I don't care much about my name being public, but I don't know what else it might have me

The comments do not seem to be addressing something very important: > I don't care much about my name being public, but I don't know what else it might have memorized (political affiliations? Sexual preferences? Posts from 13-year old me?). Combine this with https://news.ycombinator.com/item?id=28216733 https://news.ycombinator.com/item?id=28216733 https://news.ycombinator.com/item?id=27622100 https://news.ycombinator.com/item?id=27622100 Google fuck-ups are much, much more impactful than you'd expect because people have come to trust the information Google provides so automatically. This example is being invoked as comedy, but I see people do it regularly: https://youtu.be/iO8la7BZUlA?t=178 https://youtu.be/iO8la7BZUlA?t=178 So a bigger problem isn't what GPT-3 can memorize, but what associations it may decide to toss out there that people will treat as true facts. Now think about the amount of work it takes to find out problems. It's wild that you have to to Google your own name every once in a while to see what's being turned up to make sure you're not being misrepresented, but that's not too much work. GPT-3 output, on the other hand, is elicited very contextually. It's not hard to imagine that <There is a Hristo Georgiev who sold Centroida and moved to Zurich> and <There is a Hristo Georgiev who murdered five women> pop up as <Hristo Georgiev, who sold Centroida and moved to Zurich, had murdered five women.> only under certain circumstances that you can't hope to be able to exhaustively discover. From a personal angle: My birth name is also the pen name of an erotic fiction author. Hazy associations popping up in generated text could go quite poorly for me.