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Comment Re:Put out fires quickly letting fuel build up (Score 1) 7

It's almost as if allowing emissions to ramp up with little meaningful effort to control them is having the inevitable consequences predicted decades ago. But let's not deal with that, because it's hard. Instead let's have the President of the United States demand Canada hold back the tides.

Comment Re:Why? (Score 1) 154

Yeah, there's two main problems:

1) People entering the wrong fields. For example, medicine really needs workers, at all levels, but not enough people are going into it.

2) Certain manual labour fields, like field work and home construction, because... well, I think we all know why there's a shortage of workers in those fields.

Comment Re:Is it much different? (Score 1) 78

Yes, but you can eliminate that bias. I would actually be VERY careful about using AI to make personnel decisions. But if you control the whole stack it could be done safely. Start with a fresh model, train it with the performance metrics and valid data points ONLY, and make sure to DENY it ANY data on membership in protected classes. You would have to go the extra mile and anonymize all PII... make sure that there are no names in there that could give a clue to national origin or gender or such. Theoretically you shouldn't need to if you deny it the class memberships in the first place. But it's best to do that extra due diligence anyway. Models can make some weird connections.

But at the end of the day, an AI model that never knew someone was gay, still doesn't know that they're gay, and has no way to find out they're gay; can not recommend that someone be fired for being gay. And being gay (or black or female or from another country or whatever) is not a shield that prevents you being fires for malingering or incompetence.

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