MAGAZINE OF THE SOCIE TY FOR SCIENCE & THE PUBLIC MAGAZINE OF THE SOCIETY FOR SCIENCE & THE PUBLIC
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Scientific guesstimation
relies on Bayesian brains
Science and guesswork evolve hand in
hand, along with the human brain itself.
Think about it. Brains evolved to
make successful guesses about the best
survival strategies, helping their bodies
live longer and reproduce more successfully than they otherwise might. At the
same time brains also evolved the abil-
ity to engage in scientific investigation about things pretty
far removed from the perils of the savanna.
Turns out, though, that there is a connection between
these seemingly discordant abilities. Brace yourself: It has
something to do with Bayesian statistics.
In Bayesian statistical analysis, a “prior” probability (an
estimate made before data are collected) is factored into
calculations of the likelihood that a hypothesis is correct.
Bayesian math annoys some traditionalists who cling to
good old frequentist statistics, and the proper use of statistics in science is certainly an enormously complicated issue
(SN: 3/27/10, p. 26). Bayesian math also poses computational
challenges; in complex cases it can be more perplexing than
calculating an NFL quarterback’s efficiency rating.
Nevertheless, neuroscience research suggests that brains
are naturally Bayesian: They operate on the basis of past
experience but update previous beliefs as new evidence
warrants doing so. On Page 13, Laura Sanders discusses one
intriguing instance where the brain bases its judgments on
prior probabilities (perhaps instilled in early evolutionary
times). This example involves the brain’s tendency to rate
an object’s motion as slow. Since most objects don’t move
very fast, when you have to guess about an object’s velocity,
it’s best to go with what’s most probable. If new observations
differ from expectations, your brain should compensate by
modifying its likelihood guesstimates in the future.
Science as a whole proceeds in that very way: Conclusions
based on old evidence are modified as new evidence arrives.
In Bayesian terms, science reflects a cognitive strategy of
basing degree of belief in a hypothesis not just on data collected in an experiment, but also on the probable truth of the
hypothesis as estimated before collecting the new data.
If that’s confusing, you have discerned why Bayesian
methods haven’t been universally adopted in science already,
even if the brain itself uses them instinctively without doing
the math. ( Well, the brain does do the math. It just doesn’t
show its work.) —Tom Siegfried, Editor in Chief
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