As you know, Timnit's paper was not censored - it would be published either way - and she was not fired. Rather, if you trash your company's efforts in your area and threaten to resign, you shouldn't be surprised if they let you.
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Tämä twiitti ei ole saatavilla.
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Sir, I've read your book, and I'm sure you know how to apply Bayes theorem. Condition your probability of truth by the fact that that "side" was written by a team a mere dozen junior researchers, risking careers on it, or being sued by one of the richest companies ever. Thank you
Applying Bayes requires conditioning on all the evidence, not just one (interpretation of a) piece that suits you, as you're doing here.
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So that exactly what he does and he does not apply same probability on all evidences. As he is explaining.
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I'm glad Pedro Domingos moved from events misinformation to mathematical misinformation, because the latter is easier to handle. One strength of Bayesian inference is to enable useful information processing and decision making in the presence of inevitable partial information 1/3
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That’s...not true at all.
Kiitos. Käytämme tätä aikajanasi parantamiseen. KumoaKumoa
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That's just false about Bayes -- but let's do this one: The probability of you sir, having a very different problem than finding the specifics of
@timnitGebru's firing conditioned on the fact that you're simultaneously uncomfortable with this issue and also ethics peer reviews. -
It seems to me that you're generally uncomfortable with ethical considerations playing a role in AI -- and your debate on the aforementioned specifics may purely be a reaction to your larger discomfort.
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