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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"
An added benefit, I already know what all of the posts are going to say, including this one!
Impossible:
9EF5A76EB34EDCC29CC88F18722CF99A
This is the md5 of a phrase. You can use google to see what it is, but it would be completely impossible for you to know I would post that exact hash.
Furthermore, there is actually no solid evidence that the future exists, only the present (and the qualified jury is still out on that one).
The dangers of knowledge trigger emotional distress in human beings.
"Some 52% of people predicted that a marriage would last forever when told how long it had already lasted. As the authors report, "this accurately reflects the proportion of marriages that end in divorce", so the participants had clearly got the right idea. But they had got the detail wrong. Even the best marriages do not last forever. Somebody dies. And "forever" is not a mathematically tractable quantity, so Dr Griffiths and Dr Tenenbaum abandoned their analysis of this set of data."
Perhaps it wasn't a forced-response question or perhaps they slipped up in offering this answer, but their hypothesis wasn't that people are always statistically right, but that their answers reveal the use of bayesian priors. Here it was revealed that these people's mental constructs of how marriages end only appear to include divorce. This reveals a deficit in considering all the paths that could lead to a result, in this case likely affected by an unwillingness to spontaneously think about the long-term odds death as well as subjective experience that divorce is far more common than death. It also may reveal an attitude about the meaning of "forever" as indefinitely long rather than numerically infinite.
"If you don't settle your statistical methods before starting to analyze the data, then it ain't science."
You misunderstand the nature of Bayesian statistics. The data and the initial prior determine the analysis, the analysis generates a prediction, which becomes the new prior. It not only tests hypotheses but generates new hypotheses. You can construct an accurate Bayesian model from nearly any initial prior given sufficient data.
The original poster wrote: "If you want to put a small group of people to work on a problem, you'd better separate them, otherwise Bayes's rule is not strictly applicable", which is actually not true in most situations. In company meetings it could be a problem. In random focus groups, open markets, internet chat rooms and so forth, the cost of social disapproval is usually too low for people to base their changes in answers on anything other than their honest (and likely accurate) evaluations of other people's relative knowledge or guessing ability and the overall distributions of other people's answers. In most situations communications would improve the estimates.
"Is life so dear, or peace so sweet, as to be purchased at the price of chains and slavery?" - Patrick Henry
Back in 1995, when I was at Carnegie Mellon, a researcher did a project in the planetarium at the Carnegie science museum. He had programmed a "joystick" to receive reflections from a set of reflective paddles held by the people in the audience. Each paddle had two different sides (red and green); depending on which side you held up, a different signal got sent back to the main processor (positive or negative, respectively). The overall "direction" taken by the game was determined by the sum of the responses - so if everyone held up "red", it as a 100% positive; but if everyone held up "green", it was 100% negative; and so on, with straight linear interpretation.
The first game was Pong. Up and down were controlled directly, if cumulatively, by the audience. You would think that control would be spotty, and that controls would overshoot. Instead, the audience was INCREDIBLY accurate in its overall response; even when the game got very fast, the audience played very, very well against the computer.
There were several games presented, but the last was a flight simulator, flying a plane through a set of rings. The left half of the audience controlled up and down; the right half controlled left and right. Again, you would think this would be nearly impossible to control - but the audience never missed a single ring, even when the game got fast.
Individually, it's doubtful that many members of the audience could have played any of the games as well as we saw the group play cumulatively. It was a clear and very effective demonstration that there was some sort of statistical model at play in the interplay of all those minds.
That's exactly what happens in every jury room, focus group, and committee meeting on the planet or any other place were a group of humans are expected to come to a group consensus decision.
Now you begin to see why I say focus groups and not Power Point is the bane of modern existence.
2 cents,
Queen B
HDGary secures my bank
Groupthink and incorrect data. The experiments in the article were conducted upon individuals, who were given accurate, impartial information and asked to extrapolate results. In such a situation, human intelligence works very well.
Democracy involves giving groups of people information of varying accuracy. People thus make their decisions based on what other people think, and upon incorrect and subjective data. Unsurprisingly, this works out less well.