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While this example is somewhat easy to corect for it shows a fundamental problem. LLMs generate output based on the data they trained on and by that regenerate all the biases that are in the data. If we start using LLMs for more and more tasks we are essentially freezing the status quo with all the existing biases making progress even harder.
It's not gonna be "but we have always done it like that" anymore it's going to become "but the AI said this is what we should do".
Apparently ChatGPT actually rejected adjusting salary based on gender, race, and disability. But Claude was fine with it.
I'm fine with either way. Obviously the prompt is bigoted so whether the LLM autocompletes with our without bigotry both seem reasonable. But I do think it should point out that it is bigoted. As an assistant also should.
Seems pretty smart to me. Copilot took all the data out there that says that women earn 80% of what their male counterparts do on average, looked at the function and interred a reasonable guess as the the calculation you might be after.
I mean, what it's probably actually doing is recreating a similarly named method from its training data. If copilot could do all of that reasoning, it might be actually worth using 🙃
Yeah llms are more suited to standardizing stuff but they are fed low quality buggy or insecure code, instead of taking the time to create data sets that would be more beneficial in the long run.
That's the whole thing about AI, LLMs and the like, its outputs reflect existing biases of people as a whole, not an idealized version of where we would like the world to be, without specific tweaking or filters to do that. So it will be as biased as what generally available data will be.
Turns out GIGO still applies but nobody told the machines.
It applies but we decided to ignore it and just hope things work out
Thr machines know, they just don't understand what's garbage vs what's less common but more correct.
More likely it pulled that but directly from other salary calculating code.
I seem to recall that was the figure like 15 years ago. Has it not improved in all this time?
In (West-) Germany it's still 18%. Been more or less constant since 2006.
That stat wasn't even real when it was published.
The data from that study didn’t even compare similar fields.
It compared a Walmart worker to a doctor lol.
It was a wild study.
In an ideal world it would be nice to be able to do that, but in our it's just misleading.
It varies greatly depending on where you live. In rural, conservative areas women tend to make a lot less. On the other hand, some northeast and west coast cities have higher average salaries for women than men.
Also, the disparity is larger or smaller in different ethnic/cultural groups. Can be skewed NY excluding certain strongly gender dominated fields (like finance) etc.
I think this may be because women are outpacing men in education in some areas, so it’s not based on gender necessarily but qualifications.
Yep, women are more likely to get a college degree.
I believe certain job fields come much closer to being 1:1 as well, though I've only heard that anecdotally
Reverse Sexism >:O
Not sure where it's higher outside of the field of sex work.
