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Facebook apology as AI labels black men 'primates'

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Re: Facebook apology as AI labels black men 'primates'

#81

Earlier quoted context omitted.

Richen the dataset it’s trained on enough so that the model is correct before you release it to prod.

We don't actually know how to do that, or how rich is "rich enough." It's an open avenue of research to be able to extrapolate how well-tuned a neutral net is on data not in its training set. Not to imply the problem is unsolvable, just that if an institution has zero tolerance for this mistake, the fix your describing is no guarantee it won't occur.

That’s not quite complete, right? It’s that we don’t know how to do that without sacrificing other things.

Re: Facebook apology as AI labels black men 'primates'

#82
post #60

Earlier quoted context omitted.

This reminds me of a favorite tweet from 2013: "Then Google Maps was like, 'turn right on Malcolm Ten Boulevard' and I knew there were no black engineers working there" -- https://twitter.com/alliebland/status/402990270402543616 Facebook, like a lot of tech companies, has long had problems with diversity in engineering. Here's an article from April that discusses specific incidents and the broader background: https:/…

This isn't a problem with diversity. Everybody knows how to pronounce Malcom X. And it's not like just because a google engineer was black that he was like "oh, let's try and see if Malcom X is pronounced correctly because he's black and I'm black too". This only happens in white people's brain.

> This only happens in white people's brain.

'Eleven Jinping': Indian TV fires anchor over blooper.[1]

[1] https://www.bbc.com/news/world-asia-india-29274792

Re: Facebook apology as AI labels black men 'primates'

#83
post #60

Earlier quoted context omitted.

This reminds me of a favorite tweet from 2013: "Then Google Maps was like, 'turn right on Malcolm Ten Boulevard' and I knew there were no black engineers working there" -- https://twitter.com/alliebland/status/402990270402543616 Facebook, like a lot of tech companies, has long had problems with diversity in engineering. Here's an article from April that discusses specific incidents and the broader background: https:/…

This isn't a problem with diversity. Everybody knows how to pronounce Malcom X. And it's not like just because a google engineer was black that he was like "oh, let's try and see if Malcom X is pronounced correctly because he's black and I'm black too". This only happens in white people's brain.

I don't know if I 100% align up with how you stated it, but yea, its a matter of training data set. I don't think these companies have published their training data set. But thinking back on the issue with asians and facial recognition on Apple's face ID. If they just choose 100 people at random, based off US statistics, 5-6 of those 100 people would have been Asian. And that reflects the 5.7 percent of the population is Asian. And we probably all agree 5-6 people is not a sufficient data set, but picking 100 people at random would be a pretty easy assumption to make for making a data set.

So yea, I think it is an issue with generating a data set and not hitting a sufficient amount of test cases. Because in this instance, asians would be an edge case where creating a small data set to train an algorithm on with a group with a lower representation in the population.

Re: Facebook apology as AI labels black men 'primates'

#84
post #52

Earlier quoted context omitted.

Intentional or not, the outcome is all that matters. In every aspect of your life

I don't know if this is necessarily true. We have separate charges for murder and manslaughter for example.

The end outcome and impact on everyone (in your case, the deceased, the family) depends on intent.

Doesn’t change the original statement I made one bit

Re: Facebook apology as AI labels black men 'primates'

#85
post #17

Earlier quoted context omitted.

Human-like really depends on your interpretation. That's a generous reading of what's going on. If you google Gorilla faces, I don't think you would be confused. The AI is not that smart and these examples show it.

Us humans are super good at distinguishing faces. So what's obviously different to us might not be so clear to an AI or another species.

>Us humans are super good at distinguishing faces.

It would be interesting to test a bunch of midwesterners at their ability to tell Asians apart or to be able to distinguish various Asian ethnicities. My guess is that a lot of the distinguishing features that they look for are altered or missing.

Re: Facebook apology as AI labels black men 'primates'

#88
I don't like these stories. It always trends towards the most inflammatory arguments, those being inherint bias and unconscious racism put upon our technology. Real issues in those topics aside, are any articles like this doing anything but feeding flames and generating ad revenue?

Instead, I want to talk about pareidolia. Humans are social creatures. We have evolved to identify others of our kind and read their expressions. This was important to us, as we evolved alongside gorilla analogues as well, and the few of us that couldn't discern one face from another didn't usually last long.

I think we're trying to place too much of a human expectation onto these machines. I think that human features and primate features are strikingly similar, and it's our specialized brains that let us so easily discern. Yes, with enough data and training we could have more accurate models, but we can't cry foul everytime an algorithm doesn't behave like a human does.

Reference: https://www.reddit.com/r/Pareidolia/

Re: Facebook apology as AI labels black men 'primates'

#89
post #59

Earlier quoted context omitted.

Richen the dataset it’s trained on enough so that the model is correct before you release it to prod.

That's sort of obvious. How do you know that wasn't attempted?

Even if it was fixed, in a probabilistic system like this, isn't it basically guaranteed to happen with some inputs?

Re: Facebook apology as AI labels black men 'primates'

#90
post #51
post #15

This happened to both Google Photos and Flickr too. Which makes it an inexcusable mistake to make in 2021 - how are you not testing for this? Google Photos in 2015: https://www.wired.com/story/when-it-comes-to-gorillas-google... Flickr in 2015: https://www.independent.co.uk/life-style/gadgets-and-tech/ne...

The reason these companies don't fix these systems is because they don't know how. It is easier to remove certain outputs or retire the whole system. There is no line of code they can tweak.

[self-censored to prevent further downvotes because HN is downvoting me for what I said and the delete button is gone; sorry it seems discussion about solutions to racial issues isn't welcome here]
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