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> is there actually anything to suggest the algorithm is biased on the gender axis, as opposed to any other axis? None of us are allowed to know that. That's t
by function_seven 7y ago
> is there actually anything to suggest the algorithm is biased on the gender axis, as opposed to any other axis?
None of us are allowed to know that. That's the big problem here. They delegate the decision to a black box that cannot be questioned.
When the process is set up like that, I think it's fair to assume the worst case scenarios and put the burden on the company to prove otherwise.
Adverse inference is a sensible way to combat secret decisions like this.
- rndgermandude 7y ago>None of us are allowed to know that. That's the big problem here. They delegate the decision to a black box that cannot be questioned. The entire article is about questioning the black box, with regulatory force. Which is a good thing that is is going to be investigated. >When the process is set up like that, I think it's fair to assume the worst case scenarios Disagree. Consider it yes, but not assume it as a foregone conclusion. > and put the burden on the company to prove otherwise. Agree.
- xenihn 7y agoBlack-box algorithms that affect your livelihood are bad, and I don't understand how anyone can be opposed to full transparency. I don't care what the context is. Whether its credit ratings, job applications, or college admissions.
- setpatchaddress 7y agoit’s notable that a lot of mid-20th-century fear surrounding the increased use of computers was centered around this exact scenario: a black box, the judgement of which cannot be questioned, deciding your fate, with no recourse. We all scoffed at this for a long time. ML makes it real, apparently.