The Human Mind is a Bayes Logic Machine

lexxyz writes "Apparently the human mind can predict the distribution type for a given sample of results. A study found in The Economist has shown that a group of minds working on single pieces of data, can together generate the statistical model used to represent a given sample. Note that it takes a group of people to be able to accurately predict the behaviour of something, not a single individual"

Comments

Bayesian logic has strictures and inferences.....

[postbigbang]

It's not all about data and results. It's also about pre-formed boundaries, or domains within which answers usually (and some might say 'logically') fall.

This is one of those elementary, goosey sorts of tomes (if you RTFA) where a bunch of nerds go around with a bad hypthosis and come to an 'enlightened' conclusion.

Consider the techniques that surround Wolfram's expostuations-- that the world is algorhmic, and language ill-describes these algorithms, loosely defining them as processes. These setup boundaries within which we derive domains where answers must lay.

Proving that with just a few data points within a tight algorithm that you'll get the right answer is just hilarious-- of course you will. The domain fits, and so the answer must. The domain gets defined by a number of experience points as hidden references that allow the frequentists to get magic (e.g. hidden and historical) inferences to the answer. This is where the phenomenon of the trick question makes us all so frustrated.

My point? Inference has predefined boundaries, and so of course Bayesian logic doesn't require a bunch of data to lead to a correct conclusion because the boundaries are already so tightened that only those that randomly guess, and don't use historical data points (e.g. their freaking memories) are going to blow the answers.

Sigh.

Original paper here

[SiliconEntity]

Here is the paper:

http://web.mit.edu/cocosci/Papers/prediction10.pdf

It begins:

If you were assessing the prospects of a 60-year-old man, how much longer would
you expect him to live? If you were an executive evaluating the performance of a movie
that had made 40 million dollars at the box office so far, what would you estimate for its
total gross?

These questions have specific "right" answers, which can be achieved based on having the proper mental model for how lifespans and movie grosses are distributed. See how good a job you could do, without peeking, just based on your prior knowledge about the world.