196 | Judea Pearl on Cause and Effect

Sean Carroll's Mindscape: Science, Society, Philosophy, Culture, Arts, and Ideas

Sean Carroll | Wondery

Society & Culture, Physics, Philosophy, Science, Ideas, Society

4.8 • 4.4K Ratings

🗓️ 9 May 2022

⏱️ 77 minutes

🔗️ Recording | iTunes | RSS

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Summary

To say that event A causes event B is to not only make a claim about our actual world, but about other possible worlds — in worlds where A didn’t happen but everything else was the same, B would not have happened. This leads to an obvious difficulty if we want to infer causes from sets of data — we generally only have data about the actual world. Happily, there are ways around this difficulty, and the study of causal relations is of central importance in modern social science and artificial intelligence research. Judea Pearl has been the leader of the “causal revolution,” and we talk about what that means and what questions remain unanswered.

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Judea Pearl received a Ph.D. in electrical engineering from the Polytechnic Institute of Brooklyn. He is currently a professor of computer science and statistics and director of the Cognitive Systems Laboratory at UCLA. He is a founding editor of the Journal of Causal Inference. Among his awards are the Lakatos Award in the philosophy of science, The Allen Newell Award from the Association for Computing Machinery, the Benjamin Franklin Medal, the Rumelhart Prize from the Cognitive Science Society, the ACM Turing Award, and the Grenander Prize from the American Mathematical Society. He is the co-author (with Dana MacKenzie) of The Book of Why: The New Science of Cause and Effect.

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Transcript

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0:00.0	Hello everyone and welcome to the BlindsKate Podcast. I'm your host Sean Carroll.
0:03.3	As we go through life, one of the things that we're inevitably going to do all the time
0:08.4	is to assign credit or blame for things that happen in the world, either to people or to other
0:15.1	events that are happening, right? We have effects, things that happen, and we have the causes
0:20.0	for those effects, the reasons why those things happen. This idea of a structure of reality based
0:26.8	on causes and effects and their relationships is perfectly obvious, right? I mean, it's something
0:31.2	that is completely evident to us ever since we were little kids. The ancients talked about
0:36.2	an Aristotle famously, kind of organized a whole categorization of causes and different kinds of
0:42.5	causes and their effects. But like many such ideas, when you think about it a little bit more deeply,
0:48.0	it becomes tricky. What exactly is going on? If I say, I got sick because of a virus. What do I
0:55.0	really mean? I mean, there's a kind of simple answer, which is, if it weren't for the virus, I wouldn't
0:59.9	have gotten sick, right? The virus weren't there. But you try to implement that in some systematic way,
1:04.8	and what you find is it's much trickier than that. For example, what if you had gotten the virus,
1:10.5	but you were also vaccinated, so therefore you were protected against it. Or what if you didn't get
1:15.4	the virus, but you got something else, so you got sick anyway. Furthermore, that kind of reasoning
1:20.3	isn't limited to just the virus, right? I mean, Darwin's theory of evolution is responsible for
1:25.4	viruses in the first place, in some sense. So did you get sick because of Darwin's theory of
1:30.8	evolution? Did you get sick because space time is for-dimensional, without which maybe there wouldn't
1:35.2	be such thing as viruses? It's hard to pin down exactly what's going on. And this difficulty
1:40.6	is not just for physicists or philosophers or other kind of scientists. It's becoming increasingly
1:46.5	important in artificial intelligence research, because computers don't have this immediate,
1:52.4	obvious feeling that there are causes and effects in the world like human beings do. So we really
	...

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