RT Journal Article
SR Electronic
T1 Computations underlying people’s risk-preferences in social interactions
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 100313
DO 10.1101/100313
A1 Erdem Pulcu
A1 Masahiko Haruno
YR 2017
UL http://biorxiv.org/content/early/2017/01/13/100313.abstract
AB Interacting with other individuals to negotiate how we want distribution of resources (e.g. money, time) to be made is an important part of our social life. Considering that not all of our requests from others are always granted, the outcomes of such social interactions are, by their nature, probabilistic and therefore, risky. While risk-perception has been well studied in non-social contexts, its computational mechanisms in social interactions remains unknown. Here, we investigated value computations underlying how people make unfair, fair or hyper-fair Ultimatum offers to others who accepted or rejected these offers probabilistically in relation to how they valued them. We showed that people adjust their risk-preferences dynamically in social interactions, and these can be predicted from a weighted linear combination of one’s Social Value Orientation (SVO), inference about the opponent’s SVO–including one’s uncertainty in it; and relative prosociality (Δ SVO) interacting with one’s risk attitude in the value-based domain. In tandem, our results provide the first evidence to suggest that dynamic risk taking is also a cardinal element of social interactions.Significance Before requesting something important from another person, we find ourselves thinking about how they would perceive our request. If we judge that our approach will not be perceived well, we consider tweaking it to make it more acceptable. This study describes the computational mechanisms underlying how people assess the risk inherent in such uncertain social situations where their requests (i.e. offers) may be accepted or rejected depending on how the others value them. Surprisingly, despite its cardinal importance, risk-perception in social interactions has not previously been studied using a computational framework. In an ecologically valid experimental design, we show that people’s risk-preferences in social interactions may be adaptive to changing characteristics of their opponents.