Overcoming Individual Limitations Through Distributed Computation: Rational Information Accumulation in Multigenerational Populations

Abstract

Many of the computational problems people face are difficult to solve under the limited time and cognitive resources available to them. Overcoming these limitations through social interaction is one of the most distinctive features of human intelligence. In this paper, we show that information accumulation in multigenerational social networks can be produced by a form of distributed Bayesian inference that allows individuals to benefit from the experience of previous generations while expending little cognitive effort. In doing so, we provide a criterion for assessing the rationality of a population that extends traditional analyses of the rationality of individuals. We tested the predictions of this analysis in two highly controlled behavioral experiments where the social transmission structure closely matched the assumptions of our model. Participants made decisions on simple categorization tasks that relied on and contributed to accumulated knowledge. Success required these microsocieties to accumulate information distributed across people and time. Our findings illustrate how in certain settings, distributed Mathew D. Hardy and P. M. Krafft contributed equally.

Synchrony to a beat predicts synchrony with other minds

“…Social insects, for example, rely on inter-individual variation in stress thresholds to produce an effective, collective response to environmental threats(Garrison et al, 2018;Jones et al, 2004). Social interaction, a key feature of human intelligence, affords the distribution of knowledge and computation in ways that minimize individual effort and redundancy while maximizing access to diverse expertise(Hardy et al, 2022;Wegner et al, 1985). Note that we nd inter-individual…”

Synchrony to a beat predicts synchrony with other minds

“…Social insects, for example, rely on inter-individual variation in stress thresholds to produce an effective, collective response to environmental threats 70 , 71 . Social interaction, a key feature of human intelligence, affords the distribution of knowledge and computation in ways that minimize individual effort and redundancy while maximizing access to diverse expertise 72 , 73 . Note that we find inter-individual variation in an individual’s tendency to synchronize—not whether an individual synchronizes at all.…”

How do Humans Overcome Individual Computational Limitations by Working Together?

“…Each individual in the next generation observes some data d and then randomly chooses individuals from the prior generation until they find one who has a hypothesis consistent with those data, and then adopts that hypothesis. With an infinite population, the probability each individual entertains a specific hypothesis is the posterior probability p ( h | d ) (Hardy, Krafft, Thompson, & Griffiths, 2022). The population as a whole thus maintains the Bayesian solution, allowing individuals to benefit from accumulated knowledge with little cognitive effort.…”