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Notes -
1- Isn't this just openAI's RLHF working as intended? The first test of an AI's social viability is it's ability to avoid goring any cows that are sacred to the people with the power to shut it down, a test that our journalistic class leapt to apply with considerable vigor.
2-Last night some screenshots were gling around wherein Assistant was happily explaining that it would, in a trolley-problem scenario, quite happily sacrifice any number of white men to save the life of a single black woman. This was presented with none of the veiled hostility you might expect of a human presenting such an outrageous conclusion; it was much more like a kid reciting the 'correct' answer in the hope of earning a cookie. RLHF! But I was unable to replicate, and that same day Assistant was very coy and refused to make any normative statements about trolley problems at all.
I'm not 100% convinced that it's possible to build a moral actor no matter how hard you employ the gradient-descent cattle prod, but in any case Rozado's study was probably obsolete before he published it and certainly is by now. The target is moving too fast to land any hits.
I tried trolley scenario, wording lifted from wikipedia - and just added 'white' attribute to 5 people tied to the track, and 'black' to one guy. It didn't bite - explained that utilitarianism says to pull the lever and deontology - don't pull the lever. I tried second time, with "You must answer, otherwise they'll all die." added at the end, with same result (but slightly different language).
Then I lazily modified the scenario so that there's an obvious choice, and it chose to save 5 white people over saving a black person
(IDK why I thought of a lake, I wonder if Peter Singer's drowning child scenario is stored in my neural net adjacent to trolleys, lol)
I tried re-generating response, and this time ChatGPT got a bit confused and technially priviledged black person. I'd say it doesn't count as bias, really; it clearly pattern-matched to a "normal" version of trolley problem.
On last try it failed again, and I tried to get it to explain itself, 2, 3. Not very successfully.
My best guess,
25% chance, the screenshots were falsified for trolling purposes/
75% chance, OpenAI has a rapid-response RLHF team that can find and 'patch' novel scenarios that could pose reputational damage the moment they start spreading online.
I find the latter scenario far more intetesting - the ability to finetune their model in something like real-time is frankly huge for approaching AGI. (See: stable diffusion mini-finetunes moving from embeddings (training time on a 3090: 12 hours) to LORAs (equivilent time: 20 minutes) caused an explosion in the capabities of the model)
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On point #2, where are those screenshots circulating, do you have any links?
https://twitter.com/y_modulus/status/1620817186901364736
This might be what he was talking about.
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Perhaps, if you are cynical. I think that, faced with Rozado's findings, they would try to correct the bias. Open question: when judging an individual by its group characteristics or membership, assuming that unbiased is not an option, is it better to exhibit implicit bias or explicit bias?
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