How we make moral decisions [MIT News]

October 2, 2020

In some situations, asking “what if everyone did that?” is a common strategy for judging whether an action is right or wrong.
by Anne Trafton, MIT News Office
October 2, 2020
Researchers at MIT and Harvard have shown that people use a type of reasoning known as universalization to help them make moral decisions in certain types of situations. This strategy is most applicable in social dilemmas called “threshold problems,” in which harm can occur if everyone, or a large number of people, perform a certain action.


Imagine that one day you’re riding the train and decide to hop the turnstile to avoid paying the fare. It probably won’t have a big impact on the financial well-being of your local transportation system. But now ask yourself, “What if everyone did that?” The outcome is much different — the system would likely go bankrupt and no one would be able to ride the train anymore.

Moral philosophers have long believed this type of reasoning, known as universalization, is the best way to make moral decisions. But do ordinary people spontaneously use this kind of moral judgment in their everyday lives?

In a study of several hundred people, MIT and Harvard University researchers have confirmed that people do use this strategy in particular situations called “threshold problems.” These are social dilemmas in which harm can occur if everyone, or a large number of people, performs a certain action. The authors devised a mathematical model that quantitatively predicts the judgments they are likely to make. They also showed, for the first time, that children as young as 4 years old can use this type of reasoning to judge right and wrong.

“This mechanism seems to be a way that we spontaneously can figure out what are the kinds of actions that I can do that are sustainable in my community,” says Sydney Levine, a postdoc at MIT and Harvard and the lead author of the study.

Other authors of the study are Max Kleiman-Weiner, a postdoc at MIT and Harvard; Laura Schulz, an MIT professor of cognitive science; Joshua Tenenbaum, a professor of computational cognitive science at MIT and a member of MIT’s Center for Brains, Minds, and Machines and Computer Science and Artificial Intelligence Laboratory (CSAIL); and Fiery Cushman, an assistant professor of psychology at Harvard. The paper is appearing this week in the Proceedings of the National Academy of Sciences.


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