Information-Gathering Behaviour

 

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Sections

• Value of Information as a Scientific and Philosophical Problem
• Two Attempts
• Measuring Information
• The Standard Account of the Value of Evidence
• Information Aversion

 

Summary

 

• Shannon’s proof uses consistency requirements to identify a mathematical measure of the information content of a proposition, just as the Cox proof mentioned in Part 1 uses consistency requirements to derive probability.

   

• Bernardo showed that the ideally epistemically motivated Bernardo agent values tests of a proposition H exactly to the extent that they provide Shannonian information about H. Our ideally epistemically motivated agent with a finite number of cognitive acts provides a rough approximation to this utility function. One distinction between scientifically rational and scientifically irrational attitudes (about whether or not H) is that information about H has value for the former but not for the latter.

   

• According to a well-established theorem of decision theory, information cannot have negative utility when the probabilities are act-independent.

   

• In light of this theorem, the question arises of whether the human propensity to be averse to some information is explainable within descriptive Bayesianism (or indeed any intentional framework).

   

• One possible way to include information aversion within descriptive Bayesianism is to invoke motivated inference; in particular, the motivated inference from receiving disconfirmatory information about H to the giving up of one’s opinion that H. If the opinion that H is motivated by a strong value bias, then the disconfirmatory information is aversive, in that the subject would greatly prefer not to receive it.

   

• This provides a further distinction between scientifically rational and scientifically irrational attitudes: the latter is a necessary condition for information aversion, whereas a scientifically rational agent cannot be averse to information.