Article: Friday, 8 May 2020
People’s social lives are full of situations in which there is a conflict between selfish urges and the welfare of others. Unfortunately, selfish motives often prevail as is manifested in scientific misconduct, plagiarism, software piracy, and financial and insurance fraud. Little is known about the neurocognitive processes that underlie moral decisions which determine whether people behave unethically or not. Associate professor Dr Maarten Boksem and PhD candidate Sebastian Speer of Rotterdam School of Management, Erasmus University (RSM) investigated the causes of individual differences in the motivation to be fair or selfish, and whether it is possible to gain insights that could be used to increase fairness.
It is clear that there are large differences in how individuals weigh their own benefits against another person’s welfare. However, even when individuals act fairly, the motivations for doing so may be quite different from person to person. A preference for fairness may originate either from prosocial or from strategic motivations: we may wish to improve others’ well-being, or avoid the repercussions of selfish behaviour. Understanding these differences is crucially important for understanding social decision making that enables cooperation on a societal level. Yet, until now the underlying psychological and neural mechanisms of these individual differences in prosociality have remained largely elusive.
“We investigated whether we could decode selfish versus prosocial motivations from neural patterns during decision-making in economic games,” Speer explained. “We collected functional magnetic resonance imaging (fMRI) data from prosocial and selfish participants while they played several rounds of the ultimatum game (UG) and dictator game (DG), and related their behaviour during these interactions to patterns of neural activation during decision-making, using machine learning methods.”
In these games, participants have to decide how they want to divide an endowment of €20 between themselves and another participant. In the UG, responders can reject the offer when they feel it is too low, in which case neither participants get anything. In the DG, responders have to accept any offer. So, while participants may decide to be fair in the UG, they may have different motivations for doing so:
They may act out of fairness concerns.
Or because they want to avoid rejection of the offer on the responders’ side
Here, the authors used fMRI to identify neural patterns that differentiate between these two very different motivations.
To do so, they made use of the fact that, if participants were motivated by prosocial concerns, their behaviour in the UG would be similar to their behaviour in the DG. However, if participants are motivated by selfish or strategic concerns, their behaviour would be different in both games (high offers in the UG, but low offers in the DG).
Novel machine-learning methods revealed that particularly individual differences in the engagement of a network of brain regions associated with theory of mind, drive decisions to be fair and prosocial. Theory of mind refers to the inference and understanding of another person’s empathy, beliefs and intentions.
The research shows that prosocial participants appear to intuitively empathize with their opponents, which leads them to split their money evenly.
Conversely, selfish participants strategically use empathy when it is necessary to avoid rejection and financial punishment. But they do not empathize with their opponent if there is no potential punishment.
This suggests that, whereas both prosocial and selfish participants have the capacity to empathize, they do differ in their propensity to use it.
Similarly, the analysis indicated that for selfish players, neural patterns in a network of regions associated with cognitive control, representing effortful and deliberate processes, which allows us to inhibit impulsive responses in favour of long-term goals, differed more strongly between games than for prosocial players. This suggests that selfish participants must make an effort to overcome their greedy urges to keep all money to themselves in order to make a more even split to reduce the chances of getting rejected by their co-player and thus not earning any money at all. For prosocial players, in contrast, as they intuitively empathize with their opponents, no cognitive control is needed as an even split is natural and intuitive.
The results provide insights for the development of possible interventions aimed at reducing unethical behaviour, as the study demonstrated that more selfish people can also empathize with others. So, interventions targeted at fostering fairness might aim at stimulating and encouraging selfish people to take the perspective of others, trying to infer the opponents’ emotional reactions to their actions.
Rotterdam School of Management (RSM)
Princeton University
The article Decoding fairness motivations from multivariate brain activity patterns was published in Social Cognitive and Affective Neuroscience.
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