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

nytimes.com

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

#111

Post by whoaisme »

jrm4 wrote: post #100

Black person here. So, the lack of outrage here (I mean in hacker news) is unsurprising, and would of course be greater if there were more black people "in tech" and by extension here. And even as I write this, I'm not trying to judge -- just more open the door to understanding, like, y'all understand this fact, right? I find myself searching for metaphorical equivalents. I'm thinking something like "what if it label…

Your comparison of this error to Jews being labelled rats is obviously a comparison made in bad faith. Also I think it's funny that you assume that if there were more black people in the industry there would be more outrage. It seems regardless of what happens, black people want more outrage even when outrage is not justified. Even math is racist and not objective. Jesus.

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

#112

Post by jjj123 »

rscoots wrote: post #108
ant6n wrote: post #60

Earlier quoted context omitted.

The problem is the training set, which apparently skews too much towards white ppl, and doesn't include checks for the primates/non-white humans differentiation. One could argue this is due to white people building things for white ppl, which does indeed point towards systemic racism in the overall development process.

Interested in hearing how you obtained the proprietary training material for this algo from Apple. Can we see it? Also which teams at apple made the algorithm? Since you claim to know they were all 'white'. In reality, I'm sure everyone working on this team was well aware of these potentials for training set bias before most of us even knew what ML was. Even if this was considered it'd be pretty risque to have an emp…

I worked closely with an AI ethicist at $100B+ tech company company and their findings were that all of our AI training data was biased and the ML teams had no plans to de-bias their training data because they had no incentive to do so. I have no reason to believe this finding doesn’t hold for the FAANG companies. AI ethics are mostly an afterthought in tech today.

And to your second point about how would we know if the team was “all white,” of course we don’t know that and it’s probably not true. What we do know is that tech in the us is disproportionately whiter than the general public, and ~10 person teams with no black people on them are the norm, not the exception.

Edit: I should say that 10 person teams without black people on them are the norm in FAANG companies and others headquartered in the Bay Area. Other tech hubs in the US are much more diverse.

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

#113

Post by overgard »

I'm not an expert, but aren't pretty much all neural networks that are used for classifying images prone to adversarial attacks and general weird conclusions? In this case it comes up with something offensive, but I'm sure there are plenty of other cases where it's just incorrect etc. I'd imagine the only solution would be to have a human editor before these are posted, or just not use this technology in that kind of context.

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

#114

Post by co2benzoate »

jonnycat wrote: post #67

The people here saying the label is "correct" are both wrong, and missing the point. The objective of the model is not "taxonomic classification", the objective is "video recommendation". The label, in the context of the purpose of the model, is completely wrong.

Why does there tend to be a reflexive set of predictable comments on any article about racism within the tech industry that boils down to "Here is some half baked unresearched explanation that justifies why this instance of racism isn't that big of a deal?"

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

#115

Post by toxik »

wizzwizz4 wrote: post #72
toxik wrote: post #59

Earlier quoted context omitted.

These models typically don’t have hierarchical labels like that, and they apply a softmax to their output - which means /one/ label will be considered correct. (A softmax means taking the exp of your predicted scores, then divide by the sum.)

I know – but there's no technical reason they shouldn't have more complex relationships between labels (assuming you can train that, which I don't know). If we can't get better training data, at least trying to fix the problem at the algorithms (instead of slapping crude filters on the end of them) would be nice.

I agree in spirit but disagree in practice, I think. Like we said previously, the domain is humongous so even establishing meaningful relationships between labels and sublabels is extremely difficult. Many cases are likely ambiguous too, our human understanding isn’t actually hierarchical - it’s much more elusive. It’s a square peg round hole type problem really, humans don’t really think in terms of labels in the first place, we mostly use them for the purposes of language.

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

#116

Post by rscoots »

jjj123 wrote: post #112
rscoots wrote: post #108

Earlier quoted context omitted.

Interested in hearing how you obtained the proprietary training material for this algo from Apple. Can we see it? Also which teams at apple made the algorithm? Since you claim to know they were all 'white'. In reality, I'm sure everyone working on this team was well aware of these potentials for training set bias before most of us even knew what ML was. Even if this was considered it'd be pretty risque to have an emp…

I worked closely with an AI ethicist at $100B+ tech company company and their findings were that all of our AI training data was biased and the ML teams had no plans to de-bias their training data because they had no incentive to do so. I have no reason to believe this finding doesn’t hold for the FAANG companies. AI ethics are mostly an afterthought in tech today. And to your second point about how would we know if…

Clearly my point was to highlight your prejudicial instincts around this issue.

For all you know the entire team that worked on this project could've been black. Or zero of them could've been white etc.

We can and should have a conversation about training sets and ML ethics. Resorting to unprovoked racist attacks is quite a counterproductive approach imo.

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

#117

Post by chuckee »

jrm4 wrote: post #100

Black person here. So, the lack of outrage here (I mean in hacker news) is unsurprising, and would of course be greater if there were more black people "in tech" and by extension here. And even as I write this, I'm not trying to judge -- just more open the door to understanding, like, y'all understand this fact, right? I find myself searching for metaphorical equivalents. I'm thinking something like "what if it label…

> So, the lack of outrage here (I mean in hacker news) is unsurprising

Facebook deployed a flawed AI system, and when the flaw was pointed out to them, they disabled it, and apologized.

What else would you have them do, that makes this so outrageous? Donate $10 million to racial justice groups [1]? Impose diversity quotas on its law firms [2]? Commit to spend $1 billion with diverse suppliers in 2021, and $100 million specifically with Black-owned businesses [3]?

[1] https://www.nbcnews.com/business/consumer/want-know-where-al...

[2] https://www.nytimes.com/2017/04/02/business/dealbook/faceboo...

[3] https://diversity.fb.com/read-report/

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

#118

Post by UncleMeat »

co2benzoate wrote: post #114
jonnycat wrote: post #67

The people here saying the label is "correct" are both wrong, and missing the point. The objective of the model is not "taxonomic classification", the objective is "video recommendation". The label, in the context of the purpose of the model, is completely wrong.

Why does there tend to be a reflexive set of predictable comments on any article about racism within the tech industry that boils down to "Here is some half baked unresearched explanation that justifies why this instance of racism isn't that big of a deal?"

Because it permits people to take no action. If people admit there is a problem then they must justify their inaction. But if there is no problem then their inaction is justified be definition.

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

#119

Post by ratsthrowaway »

jrm4 wrote: post #100

Black person here. So, the lack of outrage here (I mean in hacker news) is unsurprising, and would of course be greater if there were more black people "in tech" and by extension here. And even as I write this, I'm not trying to judge -- just more open the door to understanding, like, y'all understand this fact, right? I find myself searching for metaphorical equivalents. I'm thinking something like "what if it label…

>"what if it labeled Jewish people as rats"

Shit man, if only.

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

#120

Post by pvaldes »

toxik wrote: post #28
stathibus wrote: post #22

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…

Primates are not darker than humans. Primates is the Order, they came in all colors, including brilliant blue, white with black stripes, orange, yellow or red.

We live in a world when everybody is offended by nothing. The problem is that nobody should be offended by being called a Gorilla. In the same way as nobody is offended by being called an eagle or a wolf. Is a wonderful animal, smart, strong, protective and gentle. What if some idiots used the term pejoratively five generations ago? We know better. Societies can change.

If white people is not being classified as primates, the algorithm should be corrected so they are. Not fixed excluding black people from humanity.

People should be educated also to understand that an AI algorithm is returning probability, not truth

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