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> Is this the sort of hormonal influence you find desirable? Nope. I said nothing about desirability. The question was: "What is the brain using except conditi
by dblotsky 9y ago
> Is this the sort of hormonal influence you find desirable?
Nope. I said nothing about desirability. The question was: "What is the brain using except conditional probabilities derived from past inputs?"
> All these factors you mention can be modeled as constant or contingent biases applied to the inputs.
It's possible, but we can't do it yet. If you have proof that we already can, please share it.
> To the extent that the brain is using unstated factors to make decisions, its decision making is unfair.
Fairness is human-defined, and difficult to encode in a computer. I conjecture that human + computer will always result in more fair and safe results than either one in isolation.
> You're hand-waving.
Yep. The number of variables (and their interactions) affecting a human decision far surpasses the number of variables in any regression method. In a lot of literature, number of variables characterises complexity.
> So what?
My example is empirical evidence of a human element identifying a false positive better than a computer. Europeans fighting wars is not such an example.
- quotemstr 9y agoHow would one go about supporting your conjecture (that fairness(human+computer) > fairness(computer)) if you can't define what "fairness" means, except by circularly referring to the inclusion of "human" term in the function input? Your argument doesn't make sense to me.
- dblotsky 9y agoIt's circular because the definition is circular, kind of like: "A mountain is larger than a hill, and a hill is smaller than a mountain." It's a shifting definition. Therefore I think modern statistical methods don't allow for that kind of self-reference, but humans do. I justify my conjecture by using laws as evidence. Except for the most basic of cases, they involve a human to interpret the law and the case to decide a verdict. Philosophically speaking, I think the "key component" that humans bring, besides still-superior decision-making in many cases (not all), is creativity. So far, I haven't seen any machine learning that can outperform humans in light of limited brand-new data.