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Comment by foldr | Hacker News Reader

>We’ve learned those tricks nowadays, and now we don’t have that kind of a disease.

I'm sure the people doing those experiments also shared the conviction that they were smarter and more objective than people in past ages.

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I read that (the quote) and thought, surely this is sarcasm.

Feynman is using very dry humor there, I'm pretty sure.

Or maybe I'm revealing my biased image of him...

But we are getting better, right? Despite undoubtedly repeating a lot mistakes (and often times being foolishly ignorant of that), some collective knowledge is surely being retained, otherwise we would not make progress in basically all sciences.

The fact that we're making progress in acquiring knowledge doesn't necessarily entail that we're getting better at being objective or unbiased. I see no reason to think that we are. (Nor am I particularly convinced that objectivity and lack of bias are major factors driving scientific progress, but that's probably another conversation.)

The very experiences that Feynman recounts have lead to a practice of doing "blind" experiments in particle physics and other places.

You simply do your analysis with some extra, unknown, factor added and once you think you done the best you can, the blinding is removed and you check to see what you measured.

Sure, but who knows if this has been beneficial to scientific progress or not? It's not like we can wind back time and do a comparative experiment.

edit To expand on this a bit, as it might sound flippant. People often talk about "bias" as if it's something that obviously ought to be eliminated. But in fact you can't get anywhere without biases. We only have the time and resources to explore a tiny portion of the hypothesis space in most domains.

> People often talk about "bias" as if it's something that obviously ought to be eliminated

Yeah, bias means our model of reality is distorted; one doesn't correspond to the other as well as it could. An example of bias, from https://en.wikipedia.org/wiki/Space_Shuttle_Challenger_disas... (appropriately enough)

<<<In the appendix, he argued that the estimates of reliability offered by NASA management were wildly unrealistic, differing as much as a thousandfold from the estimates of working engineers. "For a successful technology," he concluded, "reality must take precedence over public relations, for nature cannot be fooled." >>>

That is bias, and it killed people and didn't do the US any favours. If by bias you mean something else, your post needed to be clearer.

I think that's an odd definition of bias. Bias is just a prior inclination to believe P rather than not P. P may or may not be true.

In any case, that's the kind of bias that's relevant to this discussion.

Okay, decent answer, upvoted. I think what I said still applies, if P = "shuttle is safe 9,999 launches in 10,000" then not(P) turns out to be true. I think that's bias by both our definitions.

Now you are basically saying "what if overtraining is good?"

Overtraining is bad by definition, like overcooking. But "don't overtrain" is about as useful a maxim as "don't overcook".

Naive bayes has higher bias than logistic regression. Is that a good or a bad thing? Depends.

(I don't actually see any analogy with overtraining.)

That's really interesting. How are the blinding factors constructed and applied?

> The fact that we're making progress in acquiring knowledge doesn't necessarily entail that we're getting better at being objective or unbiased.

Agreed. In your original comment however you wrote "smarter". Granted, it's a rather vague term, but I would say the type of progress we are making in sciences could easily qualify.

otherwise we would not make progress in basically all sciences

Other than physics, chemistry and, to some extent, biology, how sure are we that we have made progress? Can we say that the CBT-psychologists of today are any closer to a theory of human cognition than their Freudian predecessors? Can we say that modern dynamic general stochastic equilibria theories of macroeconomics do better at predicting long-term economic trends than the Keynesian models that preceded them? Even in physics, we seem to be spinning our wheels, building larger and larger particle accelerators while waiting for a theoretical breakthrough that never seems to come.

We might be getting better, but it’s not hard to find examples of this. Nefarious or not, dropping “outliers” because they don’t fit the narrative is common. It’s one form of p-hacking.

Maybe we are not making progress.

:kappa:

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