Knowing me, knowing you: Interpersonal similarity improves predictive accuracy and reduces attributions of harmful intent

Abstract

To benefit from social interactions, people need to predict how their social partners will behave. Such predictions arise through integrating prior expectations with evidence from observations, but where the priors come from and whether they influence the integration is not clear. Furthermore, this process can be affected by factors such as paranoia, in which the tendency to form biased impressions of others is common. Using a modified social value orientation (SVO) task in a large online sample (n=697), we showed that participants used a Bayesian inference process to learn about partners, with priors that were based on their own preferences. Paranoia was associated with preferences for earning more than a partner and less flexible beliefs regarding a partner’s social preferences. Alignment between the preferences of participants and their partners was associated with better predictions and with reduced attributions of harmful intent to partners.

Assumed agreement about paranoid conspiracies in social networks protects against distress

“…But our data continue to suggest that paranoia and conspiracy theorizing -even the social aspects thereofare related to low-level domain-general primary learning mechanisms (30) which may be dopaminergically and noradrenergically mediated (31,32). This domain general contribution to paranoia involves learning expectancies about the environment and the agents within it (33), a process that may be guided by using oneself as a source of prior beliefs (18). Our data represent an extension of those processes into real world social relationships.…”

“…However, we do not know how those assumptions relate to their specific social networks. Furthermore, empirical and computational work has shown that participants' perceived similarity between themselves and the partner with whom they are interacting mechanistically influences social interaction by generating more accurate predictions and less threatening impressions of the partner (18). Paranoia rendered such alignment more challenging (18).…”

“…Furthermore, empirical and computational work has shown that participants' perceived similarity between themselves and the partner with whom they are interacting mechanistically influences social interaction by generating more accurate predictions and less threatening impressions of the partner (18). Paranoia rendered such alignment more challenging (18). This disconnect emphasizes the importance of relating task-elicited behaviors to real-world social understanding if we are to explain paranoia and conspiracy theories more completely.…”

Formalising social representation to explain psychiatric symptoms

“…This extends prior assessments of how social influence may govern a self's SVO [64]. Using models that estimate the preference for relative and absolute joint payoffs (Figure 1; [65]), experimenters can estimate how uncertainties and social orientation of self-preferences may disrupt the process of learning about the social-values of an other along multiple, contextually relevant dimensions (i.e. relative versus absolute payoff preferences).…”

“…relative versus absolute payoff preferences). These multiphase configurations allow testing of key psychiatric phenomena, such as the misattunement hypothesis [66], with results suggesting that discrepancies in self-other representations may make individuals more prone to developing paranoid explanations of social events [65]. Extending prior imaging work using multiphase paradigms [61][62][63], it will be useful to probe whether computational biases as a function of paranoia are reflected in reduced functional modelling of others, whether therapeutic outcomes may be marked by increased functional modelling of others, and importantly, whether this is reflected in positive outcomes.…”