Episode 105: R. A. Briggs discusses epistemic decision theory
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What is epistemic decision theory and why is it important?
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Hello and welcome to Elucidations, a philosophy podcast ordinarily recorded at the University of Chicago, but which today is being brought to you from Palo Alto. With me is R A Briggs, Professor of Philosophy at Stanford University. And they are here to discuss. Epistemic decision theory. R. A. Briggs, welcome.
Uh hi, thanks.
So recently in philosophy there's been this really cool area that maybe not everybody knows about called formal epistemology, which tries to bring some mathematical methods to bear on traditional philosophical questions in epistemology. What's epistemology? Well, roughly it's the study of like how to make good use of evidence to confirm your hypotheses, to arrive at knowledge of things, something like that. What is knowledge? What is belief? So formal epistemology study some of these questions using some of the machinery of mathematics. I think a lot of people might find it surprising that you could use the formal machinery of mathematics to study these big, grand philosophical questions. So how does that exactly work?
So I think that already people in a lot of disciplines are using uh the tools of mathematics to study these grand philosophical questions. So statistics is basically a kind of formal epistemology. You wanna know the answer to some really complicated question. You know, what are the effects of drinking a glass of red wine every day, to sort of pick an example. And then you have sort of easy to observe things about like who drank red wine in your study that you you can fund and you can maybe control who drinks red wine. And you can observe what happens to them. But the causal relationships are really hard to observe, and it's hard to tell whether something is just a noisy coincidence in any one case or whether there's a real pattern there.
So statistics is kind of a set of tools for helping you to spot patterns, and logic is a set of tools for sort of doing reasoning in a controlled and formal manner. So I think the idea that mathematical tools could help. help you with the job of epistemology is sort of has been there for a long time and is just in accordance with how people in a lot of disciplines already reason.
So a lot of the research in formal epistemology is sort of interdisciplinary with this branch of both philosophy and economics referred to as decision theory. So what exactly is decision theory? Where did that come from? And is that how did that come to be part of philosophy?
Right, so decision theory is basically uh using mathematical methods the way formal epistemology uses them to study epistemology questions about sort of using evidence, but uh decision theory uses them to study h how to make a good, prudent, rational decision. So uh I have generally when I'm making a decision some uncertainty. So I wanna know what career to choose, but I don't know exactly what the outcome of any choice will be. And I also have sort of some goals, some values uh that I can attach to certain outcomes. So decision theory uses usually probability to model the uncertainty and then uh attaches numbers to the outcomes measuring how good they are called utilities. and then advises you based on probabilities and utilities how to make a decision.
So it seems like this is the kind of thing you would program into a robot. Like you would you know, if you had a robot and you wanted to give the robot certain objectives, certain things it needed to accomplish, and then it needed to reason about how to accomplish those objectives and what to do based on the information it had. Like decision theory is what you would you'd try to write software that had some of these ideas from decision theory in.
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Chapters
8 chapters
1
What is epistemic decision theory and why is it important?
0:00–5:00
2
How does formal epistemology use mathematics to study evidence and belief?
5:00–9:23
3
What are expected value and dominance, and how do they guide rational choices?
9:23–13:37
4
When should we update our beliefs by conditionalization?
13:37–18:30
5
Why do probability rules matter for accurate degrees of belief?
18:30–23:31
6
What arguments show that conditionalization maximizes expected accuracy?
23:31–27:46
7
How does epistemic decision theory combine decision theory with belief updating?
27:46–32:05
8
What are the limits of the formal models and when might they fail?
32:05–36:46
Speakers
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