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In ML we know that in high dimensional spaces bias is a good, an essential thing. But it needs to be engineered right. Let's improve the engineering!
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I'm not against making continued funding conditional on not screwing over all your trainees! Sadly this is not a feature of the current system, as many students and postdocs who have left science against their will can attest.
In principle yes, but engineering good bias in social systems even harder than ML systems!
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It's not entirely trivial because you need to guard against false or politically motivated accusations, but yeah I agree. This should be a thing already.
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In some ways, it sort of is. At teaching institutions, the "UBI" is lots of teaching. Even research equipment must be justified as contributing to teaching and mentorship. Research can be for "curiosity" and long-term impact instead of short-term $$.
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