4 ms·

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

by ant6n 5y ago

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.

fallingknife 5y ago
But the problem is that there isn't any primates/non-white humans differentiation because humans are primates. I doubt anybody smart enough to be an AI engineer of any race would care if they were called a primate, because they are.
- hn_throwaway_99 5y ago
  I feel like this is a very "engineer" response that completely ignores how society in general would view this. Yes, humans are primates. But this wasn't a discussion about taxonomy in biology class. There are lots of cases where primates is used in everyday language where it is clearly intended to refer solely to monkeys and apes. When I go to the "primate house" at the zoo I'm not going to expect to see naked humans behind the glass.
  - fallingknife 5y ago
    But an AI image recognition system is a very "engineer" kind of thing.
    - adventured 5y ago
      And in cases where that engineer thing is used on people - it matters when you label a black person as a primate on a live social media network, since it's understood that would be likely to cause significant offense.
    - tartoran 5y ago
      Right and that’s why we should curtail its use because thinking in an engineering box suits very few real world examples. This algorithm is clearly broken, it doesn’t label all people as primates, it labels Black people wearing a green T-shirt possibly as such, I mean I’m sorry but that algorithm is definitely broken. The person in question should not be labeled as primate by any means not should any other humans unless the context is specifically some form of species taxonomy. Also your reaction seems to be all daisies and roses, and I don’t blame you for your social context ignorance you displat, I guess you are just an engineer after all..
- ant6n 5y ago
  I was gonna write "monkey-blackppl-differentiation", but decided it was too offensive and aimed for more neutral language, thinking for anybody who doesn't want to be an asshole it's clear what it's about.
- petre 5y ago
  Does the subject have clothes on? Most probably not a monkey.
rscoots 5y ago
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 employee dedicate time specifically to differentiating black ppl from apes in the algorithm.
- jjj123 5y ago
  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.
  - rscoots 5y ago
    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.
  - Melchizedek 5y ago
    Tech is not disproportionately white. It’s disproportionately Asian.

by ant6n 5y ago

fallingknife 5y ago

But the problem is that there isn't any primates/non-white humans differentiation because humans are primates. I doubt anybody smart enough to be an AI engineer of any race would care if they were called a primate, because they are.

hn_throwaway_99 5y ago
I feel like this is a very "engineer" response that completely ignores how society in general would view this. Yes, humans are primates. But this wasn't a discussion about taxonomy in biology class. There are lots of cases where primates is used in everyday language where it is clearly intended to refer solely to monkeys and apes. When I go to the "primate house" at the zoo I'm not going to expect to see naked humans behind the glass.
- fallingknife 5y ago
  But an AI image recognition system is a very "engineer" kind of thing.
  - adventured 5y ago
    And in cases where that engineer thing is used on people - it matters when you label a black person as a primate on a live social media network, since it's understood that would be likely to cause significant offense.
  - tartoran 5y ago
    Right and that’s why we should curtail its use because thinking in an engineering box suits very few real world examples. This algorithm is clearly broken, it doesn’t label all people as primates, it labels Black people wearing a green T-shirt possibly as such, I mean I’m sorry but that algorithm is definitely broken. The person in question should not be labeled as primate by any means not should any other humans unless the context is specifically some form of species taxonomy. Also your reaction seems to be all daisies and roses, and I don’t blame you for your social context ignorance you displat, I guess you are just an engineer after all..
ant6n 5y ago
I was gonna write "monkey-blackppl-differentiation", but decided it was too offensive and aimed for more neutral language, thinking for anybody who doesn't want to be an asshole it's clear what it's about.
petre 5y ago
Does the subject have clothes on? Most probably not a monkey.

rscoots 5y ago

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 employee dedicate time specifically to differentiating black ppl from apes in the algorithm.

jjj123 5y ago
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.
- rscoots 5y ago
  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.
- Melchizedek 5y ago
  Tech is not disproportionately white. It’s disproportionately Asian.