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Facebook Apologizes After A.I. Puts “Primates” Label on Video of Black Men

nytimes.com

31–40 of 173 posts

Re: Facebook Apologizes After A.I. Puts “Primates” Label on Video of Black Men

#32

Earlier quoted context omitted.

There’s a time and a place for being pedantic, this isn’t it.

Exactly, we should keep feeding the outrage machine.

There is a world of nuanced discussion between flippant dismissal and outrage. Please let’s try to shoot for somewhere in the middle.

Re: Facebook Apologizes After A.I. Puts “Primates” Label on Video of Black Men

#33

Aren't we all primates?

Yes, we are, and the author of the NYT article seems weirdly unaware of that. However, the issue here, I’m sure, is that Facebook’s algorithms don’t classify videos of white humans as involving “primates” as well.

[deleted]

Re: Facebook Apologizes After A.I. Puts “Primates” Label on Video of Black Men

#36
post #11

Don't these kinds of companies have a basic checklist before releasing features like this? And if so, why doesn't this checklist include things like "doesn't identify members of racial group as animals" ? It makes me think that any woke PR coming from Facebook is lip service, if they don't have even basic checks in place.

The question is how would they know they are members of a racial group when it couldn't even identify them as part of the righ species? The answer is that these algorithms are not fit for serious classification and are not appropriate for this type of application.

EDIT: pardon me, what I wrote is wrong. We are all primates after all :)

Re: Facebook Apologizes After A.I. Puts “Primates” Label on Video of Black Men

#37

Surprised they weren't more careful with this after Google had the same problem a few years ago. https://www.theverge.com/2018/1/12/16882408/google-racist-go...

Yeah you’d think think they be extra careful on their model which classifies videos of people before releasing it.

Re: Facebook Apologizes After A.I. Puts “Primates” Label on Video of Black Men

#38

Aren't we all primates?

The angry answers to your comment, and also the fact that the AI has this problem, seems to highlight the USA centric character of the data used and the people working on Facebook.

I wonder what would an AI trained with pictures from India would show.

Re: Facebook Apologizes After A.I. Puts “Primates” Label on Video of Black Men

#39

Earlier quoted context omitted.

There’s a time and a place for being pedantic, this isn’t it.

Exactly, we should keep feeding the outrage machine.

No, we should put effort into not being outrageous, whether or not it is intentional.

Re: Facebook Apologizes After A.I. Puts “Primates” Label on Video of Black Men

#40
post #28

Earlier quoted context omitted.

Another way to put this is: nobody working in this field has control over what they are building, and can't make any promises about how it will behave. It's like launching a rocket ship that you can't test in a physical simulation first. Something is going to go wrong that can't be predicted because we lack the understanding, but this is seen as an acceptable risk.

Which is inherent to the problem. The domain is the space of _all possible natural images_, it’s so big, it’s ridiculous. Fundamentally, these techniques do not analyze images like humans do, but are rather trained to pick out any salient signal it can latch on to. That seems to be “primates are mostly like humans but darker”, which is superficially true but a pretty weak definition as it includes dark skinned humans…

It's probably because humans are primates – but the AI systems often have to treat “human” as a completely separate category as “primate”, so they have to draw weird, complex boundaries around “primate” (actually “all non-human primates”). When the “primate” classification is stronger than the “human” classification, the system says “primate” rather than “human”, and if it's predominantly been trained on “pictures of white Americans are not pictures of primates”, its “primate” definition might not be skewed to miss everyone else.

I expect you'd get better results if you allowed the system to call humans “primates”, then accept “human primate” as “human” when parsing the output. (That is, leave the “is_primate” output line floating while training on pictures of humans.) I don't know whether that would work, though.

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