Brain in a vat scenario
"Is there a nonzero probability that I am a brain in a vat? Of course; that’s boring. [PDF]
"Practically everything has a nonzero probability all the time, and who cares?
"What is
interesting is why the brain in a vat scenario is a bad explanation for sensory experience,
and what this case teaches us about the criteria for an adequate explanation.
"The BIV hypothesis is one of a family of theories that can be generated to explain
any evidence.
"For instance,
- One can explain the motions of the planets by citing the hypothesis that God pushes the planets around just so.
- One can explain why a book fell off a shelf by hypothesizing that an invisible demon pushed it off.
"What do these
theories have in common? They all propose a mechanism that allegedly generated the
evidence to be explained, where this mechanism could, with about equal plausibility, be invoked to explain an extremely wide variety of evidence —perhaps even to explain any
possible evidence in the particular field in question (for instance, any possible series of
planetary motions, or any possible series of sensory experiences).
"Thus, the likelihood
functions for such theories are spread out over a wide range of possible evidence.
"By
contrast, the sort of theories we normally take seriously —such as our common sense
beliefs about the external world, or Newton’s theory of gravity —have relatively narrow
likelihood functions, that is, they generate substantive expectations about what the
evidence should be like.
"If those expectations are realized, the normal
theories will receive higher posterior probabilities than the BIV-like theories, in
accordance with Bayes’ Theorem.
"Of course, one can generate BIV-like theories that have narrow likelihood functions,
by simply incorporating postulates into the theories that stipulate that the mechanism
generating the evidence operates in the specific way, or under the specific conditions,
that it would need to in order to generate just that evidence and no other.
"But then one
simply trades (a) theory with a low likelihood for (b) theory with a low prior probability."
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Empathy recommended