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That is clearly overfitting due to unrepresentative training data. The "issue" is a different one: that training data - IE, reality, has _unwanted_ biases in i
by Jerrrry 4y ago
That is clearly overfitting due to unrepresentative training data.
The "issue" is a different one: that training data - IE, reality, has _unwanted_ biases in it, because reality is biased.
Producing images of men when prompting for "trash collecting workers" should not be much of a surprise: 99% of garbage collection/refuse is handled by men. I doubt most will consider this a "problem," because of one's own bias, nobody cares about women being represented for a "shitty" job.
But ask for picture of CEOs, and then act surprised when most images are of white men? Only outrage, when proportionally, CEO's are, on average, white men.
The "problem" arises when we use these tools to make decisions and further affect society - it has the obvious issue of further entrenching stereotypical associations.
This is not that. Asking DALLE for a bunch of football players, would expectedly produce a huddled group of black men. No issue, because the NFL are disproportionately black men. No outrage, either.
Asking DALLE for a group of criminals, likewise, produces a group of black men. Outage! Except statistically, this is not a surprise, as a disproportionate amount of criminals are black men.
The "problem" is with reality being used as training data. The "problem" is with our reality, not the tooling.
Except in the cases where these toolings are being used to affect society - the obvious example being insurance ML algorithms. et al - we should strive to fix the issues present in reality, not hide them with handicapped training data, and malformed inputs.
- CuriousSkeptic 4y ago> Asking DALLE for a bunch of football players, would expectedly produce a huddled group of black men I think, for about 95% of the world football is synonymous with soccer. Its kind of interesting that you take this particular example to represent what reality looks like statistically
- TomWhitwell 4y agoIn the UK… “The Environmental Services Association, the trade body, said that only 14 per cent of the country's 91,300 waste sector workers were female.” So 2x dall-e searches should produce 1.2 women.
- less_less 4y ago> This is not that. Asking DALLE for a bunch of football players, would expectedly produce a huddled group of black men. No issue, because the NFL are disproportionately black men. No outrage, either. This is not great. Only about 57% of NFL players are black, and the percentage is more like 47% among college players. It would be better to at least reflect the diversity of the field, even if you don't think it should be widened in the name of dispelling stereotypes. > Asking DALLE for a group of criminals, likewise, produces a group of black men. Outage! Except statistically, this is not a surprise, as a disproportionate amount of criminals are black men. Only about 1/3 of US prisoners are black. (Not quite the same as "criminals" but of course we don't always know who is committing crimes, only who is charged or convicted.) That's disproportionate to their population, but it's not even close to a majority. If DALLE were to exclusively or primarily return images of black men for "criminals", then it would be reinforcing a harmful stereotype that does not reflect reality.
- cmeacham98 4y ago> Asking DALLE for a group of criminals, likewise, produces a group of black men. Outage! Except statistically, this is not a surprise, as a disproportionate amount of criminals are black men. "criminals" producing most black people actually would be a perfect example of bias in DALL-E that is arguably racism. Black people commit a diproportionate amoumt of crime (for a variety of socioeconomic reasons I won't get into here), but even so white people make up a majority of criminals (because white people are the largest ethnic group by far). Thus, a random group of criminals, if representive of reality, should be majority white.