yego.me
💡 Stop wasting time. Read Youtube instead of watch. Download Chrome Extension

Is science synonymous with ‘truth’? Game theory says, ‘not always’. | Kevin Zollman | Big Think


3m read
·Nov 3, 2024

Processing might take a few minutes. Refresh later.

[Music]

Uh, game theory can be applied to scientific understanding in a lot of different ways. One of the interesting things about contemporary science is that it's done by these large groups of people who are interacting with one another. So, science isn't just the lone scientist in his lab removed from everyone else, but rather it's teams working together, sometimes in competition with other teams who are trying to beat them out to make a big discovery.

So, it's become much more like a kind of economic interaction. These scientists are striving for credit from their peers, for grants from federal agencies, and so a lot of the decisions that they make are strategic in nature. They're trying to decide what things will get funded, what strategies are most likely to lead to a scientific advance, how can they do things so as to get a leg up on their competition, and also get the acclaim of their peers.

Game theory helps us to understand how the incentives that scientists face in trying to get credit, in trying to get grants, and trying to get acclaim might affect the decisions that they make. And sometimes there are cases where scientists striving to get acclaim can actually make science worse because a scientist might commit fraud if he thinks he can get away with it, or a scientist might rush a result out the door even though she's not completely sure that it's correct, in order to beat the competition.

So, those of us who use game theory in order to try and understand science apply it in order to understand how those incentives that scientists face might eventually impact their ability to produce truths and useful information that we as a society can go on. Or how those incentives might encourage them to do things that are harmful to the progress of science by either publishing things that are wrong or fraudulent, or even withholding information that would be valuable.

This is one of the big problems that a lot of people have identified with the way that scientists’ scientific incentives work right now. Scientists get credit for publication, and they're encouraged to publish exciting new findings that demonstrate some new phenomena that we've never seen before. But when a scientist fails to find something that's informative, too, the fact that I was unable to reproduce a result of another scientist shows that maybe that was an error.

But the way that the system is set up right now, I wouldn't get credit for publishing what's called a null result, a finding where I didn't discover something that somebody else had claimed to discover. So, as a result, when we look at the scientific results that show up in the journals that have been published, it turns out that they are skewed towards positive findings and against null results.

A lot of different people have suggested that we need to change the way that scientists are incentivized by rewarding scientists more for both publishing null results and for trying to replicate the results of others. In particular, in fields like psychology and medicine, places where there's a lot of findings and there are lots of things to look at, people really think that we might want to change the incentives a little bit in order to encourage more duplication of effort, in order to make sure that a kind of exciting but probably wrong result doesn't end up going unchallenged in the literature.

Traditionally, until very recently, scientists were mostly looking for the acclaim of their peers. You succeeded in science when you got the acclaim of another scientist in your field, or maybe some scientists outside your field. But now, as the area of science journalism is increasing, the public is starting to get interested in science, and so scientists are starting to be rewarded for doing things that the public is interested in.

This has a good side and a bad side. The good side is it means that scientists are driven to do research that has public impact, that people are going to find useful and interesting, and that helps to encourage scientists not just to pursue some esoteric question that maybe is completely irrelevant to people's everyday life. The bad ...

More Articles

View All
Automatic stabilizers | National income and price determination | AP Macroeconomics | Khan Academy
So what we have depicted in this diagram is the business cycle that we have looked at in other videos. This horizontal axis is time; the vertical axis is real GDP. What we see in this dark blue color, you can view that as full employment output at differe…
Tracy Young on Scaling PlanGrid to 400+ People with YC Partner Kat Manalac
All right, Tracy, welcome to the podcast. Thank you for having me! How you doing? I’m doing good, thank you. Cool, so your company’s PlanGrid, and you were in the winter 2012 batch. For those who don’t know, PlanGrid is in the construction industry, b…
How the delivery of a speech affects the impact of the words | Reading | Khan Academy
Hello readers. Today we’re talking about how the delivery of the speech affects the impact of the words. So what do I mean by that? It’s all the ways that how a person says something affects what they mean. Words on a page may have a certain definition, b…
8 Benefits Of Traveling Alone
The first time I truly traveled alone was around five years ago. I didn’t really know what to expect and how it would be to face the world equipped with a small trolley and backpack. Well, it was one of the greatest experiences I’ve ever had. So, I did it…
Living Alone✨ a day in my life in Tokyo🇯🇵, Michelin star restaurant🌟, shopping in Shibuya🗼
Foreign [Music] Good morning everyone! As you guys might or might not realize, I am in Tokyo right now. So today, we’re gonna spend a day together in Tokyo while I shop and do my own things. I have actually quite a lot of things that I need to buy and th…
Worked examples for standard algorithm exercise
We’re now going to do a few example questions from the Khan Academy exercise on the standard algorithm. So we’re asked which of the following correctly multiplies 74 times 8 using the standard algorithm. So pause this video and see if you can work on that…