reckless intuitions of an epistemic hygienist ([info]gustavolacerda) wrote,
@ 2005-10-12 22:54:00
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Entry tags:econ, phil

Aumann wins Nobel
Robert Aumann, of "you can't agree to disagree" fame, shares the Nobel this year with Thomas Schelling. via Marginal Revolution

from Tyler Cowen, Robin Hanson - Are Disagreements Honest?

... according to well-known theory, such honest disagreement is impossible. Robert Aumann (1976) first developed general results about the irrationality of “agreeing to disagree.” He showed that if two or more Bayesians would believe the same thing given the same information (i.e., have “common priors”), and if they are mutually aware of each other's opinions (i.e., have “common knowledge”), then those individuals cannot knowingly disagree. Merely knowing someone else’s opinion provides a powerful summary of everything that person knows, powerful enough to eliminate any differences of opinion due to differing information.


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Disagreements
[info]r6
2005-10-13 07:19 am UTC (link)
I suspect people disagree because it takes too long to explain their opinion and come to common knowledge.

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Re: Disagreements
[info]gustavolacerda
2005-10-13 09:00 am UTC (link)
People are nowhere near as ideal as that. There's a lot of inference blocking due to emotional attachments, social dynamics, fashionable beliefs, etc.

I think this paper discusses that. If not, surely another Robin Hanson paper does.

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[info]dagidham
2005-10-13 11:26 am UTC (link)
Two people, same info, different values = honest disagreement. E.g. Two lunch partners must order one meal from a menu of a ham meal and a salad meal. Bob prefers and picks ham. Mary prefers and picks salad. Honest disagreement, right? It sounds wrong to presuppose that two people given the same info will arrive at the same opinion.

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[info]gustavolacerda
2005-10-13 11:32 am UTC (link)
they define "disagreement" as disagreement about matters of fact.

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[info]dagidham
2005-10-13 05:00 pm UTC (link)
Oh, I see. So their result would have importance for cases where two scientists interpret the same data in opposing ways.

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