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Ah. Yeah, I'm basically saying "lean towards terrible and dystopian and harmful, not useless". If you tell people it's useless, dystopian, and harmful, and they
by JoshuaDavid 6y ago
Ah. Yeah, I'm basically saying "lean towards terrible and dystopian and harmful, not useless". If you tell people it's useless, dystopian, and harmful, and they find out it's actually useful, they may not take seriously the "dystopian and harmful" bits.
It sounded kind of like you thought it wouldn't be possible to get interesting results which tell you something you didn't already know from ML with much better than random chance.
>> I find it equally plausible that the computer determined that there was a difference in personal grooming habits or facial expressions between groups.
> Right, so then the question is if this is valuable.
That's not really my question, but I'd argue that the answer is "it depends on how you're trying to use it". If you're an advertiser of questionable ethics, and trying to promote your local gay bar, it probably is useful to you. Likewise if you're a computer science professor trying to get grant funding. If you mean "useful to society as a whole", probably not.
Which comes down to the difference between "this will accomplish the goals of the people who want to use it" and "letting those people use this tool is a good idea". The danger is that if you try to convince people not to use the tool because it doesn't work, but the tool does in fact work, trying to convince them later because the results are harmful is less likely to work.
- joshuamorton 6y ago> It sounded kind of like you thought it wouldn't be possible to get interesting results which tell you something you didn't already know from ML with much better than random chance. In general I do think this is true, but it's not verifiable. Like I said, in general I think that the priors that underlying facial structure should be strongly correlated with sexual orientation are very low. It's not impossible, just unlikely, so when you get "results", the most likely explanation is not that you've found something profound, but that you're encoding social biases. And so from the perspective of a researcher, you haven't actually accomplished your goals (of discovering something profound), you've instead committed a relatively elementary error that legitimizes certain forms of stereotyping. And again I note that my priors suggest that this is the most likely outcome.