People do not always expect impartial and evidence-based reasoning from others, according to new research published in the journal Cognition. Instead, the study indicates that people commonly think that some beliefs should be affected by what would be morally beneficial to believe.
“There has been a growing interest in psychology regarding metacognition, which basically just means people’s evaluation of their thinking and beliefs,” said study author Corey Cusimano, a postdoctoral research associate at Princeton University.
“There seems to be a clear connection between people’s attitudes towards thinking, on the one hand, and the kinds of beliefs that they form and that spread in groups. Concurrent with this research in psychology, some recent work in philosophy has argued that certain forms of motivated reasoning may be justified and right to do.”
“These two ideas, when juxtaposed with one another, invite the question: Under what conditions to people think that motivated reasoning is good reasoning?” Cusimano explained. “Our hope is that by understanding how people evaluate thinking as good or bad, we will be better able to find faults in how people think and design interventions to improve reasoning.”
In the study, 839 adults were randomly assigned to read one of six short stories “in which the main character acquires strong but inconclusive evidence for a proposition that they have a moral reason to reject.” The participants then reported what an impartial observer would believe and what the main character in the story should believe.
For example, one of the stories detailed a young man who had married his high school sweetheart, only to learn later that 70% of such marriages end in divorce. The participants were asked to indicate what an “advanced artificial intelligence” would estimate the probability of the marriage ending in divorce to be. The participants also indicated what the married man ought to believe about the probability that he would get divorced.
The researchers found that the participants tended to indicate that the main characters in the stories should hold an inaccurate belief. In the case of the married man, the participants believed that he should be more optimistic about his marriage than an objective and impartial artificial intelligence.
The findings suggest that “the people around you may not want you to be perfectly impartial when you think about them,” Cusimano told PsyPost. “Your friends and family members might want you be biased in their favor.”
Cusimano and his colleagues conducted two additional experiments, with another 1,254 participants, which replicated and clarified the findings. In particular, the researchers found that social distance played an important role. A husband, for instance, was seen as having a greater obligation to be optimistic than a friend, even though both had the same evidence.
“Across all studies, participants routinely indicated that what a believer ought to believe, or was justified in believing, should be affected by what would be morally beneficial to believe,” the researchers wrote in their study. “The extent to which participants prescribed these optimistic beliefs was strongly associated with the amount of moral benefit they thought an optimistic belief would confer.”
But, as with any study, the new findings include some caveats.
“First, our results are just one study on this topic, and they should be followed up by other scientists and replicated in other domains,” Cusimano explained.
“The second, I think more important caveat, is that our results do not show us that people are engaging in morally motivated reasoning. All our studies show is that people think it would be right to do so. This is important: people might think that others ought to be motivated but also think that they themselves ought not to be. Or, people might think that they and others ought to be motivated in situations where, it turns out, people often are not engaging in much motivated reasoning at all.”
The study, “Morality justifies motivated reasoning in the folk ethics of belief,” was authored by Corey Cusimano and Tania Lombrozo.