Beliefs about others' intentions determine whether cooperation is the faster choice

Is collaboration the fast choice for humans? Past studies proposed that cooperation is a behavioural default, based on Response Times (RT) findings. Here we contend that the individual’s reckoning of the immediate social environment shapes her predisposition to cooperate and, hence, response latencies. In a social dilemma game, we manipulate the beliefs about the partner’s intentions to cooperate and show that they act as a switch that determines cooperation and defection RTs; when the partner’s intention to cooperate is perceived as high, cooperation choices are speeded up, while defection is slowed down. Importantly, this social context effect holds across varying expected payoffs, indicating that it modulates behaviour regardless of choices’ similarity in monetary terms. Moreover, this pattern is moderated by individual variability in social preferences: Among conditional cooperators, high cooperation beliefs speed up cooperation responses and slow down defection. Among free-riders, defection is always faster and more likely than cooperation, while high cooperation beliefs slow down all decisions. These results shed new light on the conflict of choices account of response latencies, as well as on the intuitive cooperation hypothesis, and can help to correctly interpret and reconcile previous, apparently contradictory results, by considering the role of context in social dilemmas

A divisive model of evidence accumulation explains uneven weighting of evidence over time

Divisive normalization has long been used to account for computations in various neural processes and behaviours. The model proposes that inputs into a neural system are divisively normalized by the system's total activity. More recently, dynamical versions of divisive normalization have been shown to account for how neural activity evolves over time in value-based decision making. Despite its ubiquity, divisive normalization has not been studied in decisions that require evidence to be integrated over time. Such decisions are important when the information is not all available at once. A key feature of such decisions is how evidence is weighted over time, known as the integration kernel. Here, we provide a formal expression for the integration kernel in divisive normalization, and show that divisive normalization quantitatively accounts for 133 human participants' perceptual decision making behaviour, performing as well as the state-of-the-art Drift Diffusion Model, the predominant model for perceptual evidence accumulation. Divisive normalization is thought to be a ubiquitous computation in the brain, but has not been studied in decisions that require integrating evidence over time. Here, the authors show in humans that dynamic divisive normalization accounts for the uneven weighting of perceptual evidence over time.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Technological change and market design

Technological innovations lead to new market designs and new designs catalyze the emergence of newtechnologies.Building on examples drawn from recent advances in medical, electricity, car, computing, and data collection technologies, this note discusses the relationship between technological change and market design with an emphasis on new questions for market design theory