[ospohngellert]

Making sure that NLP algorithms are unbiased is important not just from a social justice perspective, but from a perspective of how useful the algorithms are. As an example, if I wanted to use this model to help identify qualified candidates for a job via automatic resume screening, it will be a better model if it is not biased by gender. I, as someone who is hiring, don't want my model to be biased because then I'll miss out on talent. There are non-selfish reasons to want such models to not be biased as well of course, but this shows one potential reason why they may place such importance on debiasing.

EDIT: fixed typo

[enlyth]

I'd rather my resume go straight into the bin than be analyzed by some glorified Markov chain trained on reddit posts

[smoldesu]

It's good that you bring this up, because it's exactly the sort of thing I wanted to discuss. Why do we feel comfortable letting machine learning screen resumes? Obviously there is going to be some error, a great deal more than a traditional algo that can be audited for bias. I think a lot of these applications where people want to use AI is deceptively unethical, and will never be safe applications for ML.

[ospohngellert]

I agree to some extent. I'm not sure whether AI should be used for resume screening, but I'd lean towards no until biases are proven to not be an issue (if that's possible). There are obviously other areas where this is an important issue that we need to think critically about such as loans and criminal sentencing.