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Comment by svnt | Hacker News Reader

The issue the anecdote is reflecting is that across the data of 50 naive made-up coin tosses there are too many alternating sequences and probably zero HHHHHH.

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and it's different from 50 randomly selected true coin tosses because you think it's impossible for all of them to alternate?

I understand your point, but the context is that repeatedly, experiments have shown that humans inject too much pattern to be good rngs. It turns out that is visible with training after the fact.

Yes, it is possible that any two 50-sequence patterns are actual rng. But some of them are much more likely, and we can tell.

> some of them are much more likely, and we can tell

Yeah if you define randomness as subjective "stuff humans can't predict" then sure...

I'm not sure what your point is. A collection of samples were taken from humans, and they did not form a uniform distribution. Samples from an unbiased RNG are much closer to uniform.

Are you saying we should ignore the distribution we observe from humans and predict them as uniform anyway?

You say yourself "strings are equally likely if they're being purely randomly selected". So you move the goalpost to define "random" as "whatever a human would think is random".

> Samples from an unbiased RNG

you mean a PRNG.

> Are you saying we should ignore the distribution we observe from humans and predict them as uniform anyway?

I'm saying the exercise in general is a little pointless, but that's fine.

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