Understanding others' distal goals from proximal communicative actions.

Many social interactions require individuals to coordinate their actions and to inform each other about their goals. Often these goals concern an immediate (i.e., proximal) action, as when people give each other a brief handshake, but they sometimes also refer to a future (i.e. distal) action, as when football players perform a passing sequence. The present study investigates whether observers can derive information about such distal goals by relying on kinematic modulations of an actor's instrumental actions. In Experiment 1 participants were presented with animations of a box being moved at different velocities towards an apparent endpoint. The distal goal, however, was for the object to be moved past this endpoint, to one of two occluded target locations. Participants then selected the location which they considered the likely distal goal of the action. As predicted, participants were able to detect differences in movement velocity and, based on these differences, systematically mapped the movements to the two distal goal locations. Adding a distal goal led to more variation in the way participants mapped the observed movements onto different target locations. The results of Experiments 2 and 3 indicated that this cannot be explained by difficulties in perceptual discrimination. Rather, the increased variability likely reflects differences in interpreting the underlying connection between proximal communicative actions and distal goals. The present findings extend previous research on sensorimotor communication by demonstrating that communicative action modulations are not restricted to predicting proximal goals but can also be used to infer more distal goals.

Democratic forecast: Small groups predict the future better than individuals and crowds.

Predictions pose unique problems. Experts regularly get them wrong, and collective solutions (such as prediction markets and super-forecaster schemes) do better but remain selective and costly. Contrary to the idea that face-to-face discussion hinders collective intelligence, social deliberation improves the resolution of general knowledge problems, with four consensually agreed answers outperforming the aggregate knowledge of 5,000 nondeliberating individuals. Could discussion help predict the future in an efficient, cheap, and inclusive way? We show that smaller groups of lay individuals, when organized, come up with better predictions than those they provide alone. Deliberation and consensus made individual predictions significantly more accurate. Aggregating as few as two consensual predictions did better than classical "wisdom of crowds" aggregation of 100 individual ones. Against the view that discussion can impair decision-making, our results demonstrate that collective intelligence of small groups and consensus-seeking improves accuracy about yet unknown facts, opening the avenue for efficient, inclusive, and inexpensive group forecasting solutions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).