The social dynamics of collective problem-solving

Abstract

When searching for solutions to a problem, people often rely on the observation of their peers. How does this process of social learning impact the individual and the group's performance? On the one hand, research has shown that individuals benefit from social learning in numerous situations and across many domains. Through social learning, individuals can access good solutions found by others, improve them, and share them in turn. On the other hand, this individual benefit may come at a cost: An excessive tendency to copy others often decreases the overall exploration volume of the group, thus reducing the diversity of discovered solutions, and eventually impairing the collective performance.Here we investigate the conditions under which social learning can be beneficial or detrimental to individuals and to the group. For that, we model problem-solving as a search task and simulate various amounts of social learning. We avoid model specific considerations by relying on a simple framework whereby individuals gradually explore the search environment -a two-dimensional landscape of solutions -while being attracted to the best solution of the group. Our results highlight a collective search dilemma: When group members learn from one another, they tend to improve their own individual performance at the expense of the collective performance. How is this dilemma affected by the structure of the search environment? By varying two structural aspects of the search environment, our results reveal that the negative effect of the dilemma is mitigated in more difficult environments. Finally, we show that single individuals can profit from a high propensity of social learning, which in turn is damaging for the other group members. As a consequence, if individuals continually adapt their behavior to maximize their own payoff, groups converge to a sub-optimal level of social learning. Unraveling these intricate social dynamics helps to understand the complex picture of collective problem-solving.

The Diversity Gap: When Diversity Matters for Knowledge

“…Frequently, computational complexity in problem solving is cashed out in terms of a rugged epistemic landscape, where individuals are likely to get stuck on local optima, but where the global optimum is hard to find (Alexander, Himmelreich, & Thompson, 2015;Almaatouq, Yin, & Watts, 2020;Bernstein, Shore, & Lazer, 2018;Lazer & Friedman, 2007;Yahosseini & Moussaïd, 2019). Experimental results in complex problem solving show that when communication is throttled, this reduces herding and maintains informational diversity, thus preventing people from converging on local optima, and boosting the group's chances of discovering the global optimum (Bernstein et al, 2018;Shirado & Christakis, 2017).…”

“…Our initial claim was that diversity is beneficial for collective problem solving (and not necessarily for epistemic performance in general), but this glossed over a key factor: The benefits of diversity are stronger for more complex problems (Bosetti et al, 2012; Bowers et al, 2000; Cooke & Kemeny, 2017; De Dreu et al, 2008; Grim et al, 2019; Hong & Page, 2001; LiCalzi & Surucu, 2012; Page, 2014; Pöyhönen, 2017; Van Dijk et al, 2012; Yahosseini & Moussaïd, 2019): “Without diversity, one cannot have much complexity. But without complexity, diversity becomes mere variation, noise about the mean” (Page, 2014, p. 268).…”

The Diversity Gap: when diversity matters for knowledge

“…A more nuanced view of problem solving: complexity matters Our initial claim was that diversity is beneficial for collective problem solving (and not necessarily for epistemic performance generally), but this glossed over a key factor: the benefits of diversity are stronger for more complex problems (Bosetti et al, 2012;Bowers et al, 2000;Cooke & Kemeny, 2017;De Dreu et al, 2008;Grim et al, 2019;Hong & Page, 2001;LiCalzi & Surucu, 2012;Page, 2014;Pöyhönen, 2017;Van Dijk et al, 2012;Yahosseini & Moussaïd, 2019). 'Without diversity, one cannot have much complexity.…”

Addressing the Dark Side of Leadership in the University System Using Community of Practice (CoP) Approach

“…Maupin et al (2020) highlights the need to consider power dynamics and methodological challenges in this context. Yahosseini (2020) introduces a novel approach to aggregating judgments, the transmission chain, which has shown promise in fostering collective intelligence. These studies collectively underscore the potential of collective problem solving as a remedy for the dark side of leadership, particularly in small-scale societies where leadership can help overcome collective action problems (Glowacki and von Rueden 2015).…”