Beyond collective intelligence: Collective adaptation.

We develop a conceptual framework for studying collective adaptation in complex socio-cognitive systems, driven by dynamic interactions of social integration strategies, social environments and problem structures. Going beyond searching for 'intelligent' collectives, we integrate research from different disciplines and outline modelling approaches that can be used to begin answering questions such as why collectives sometimes fail to reach seemingly obvious solutions, how they change their strategies and network structures in response to different problems and how we can anticipate and perhaps change future harmful societal trajectories. We discuss the importance of considering path dependence, lack of optimization and collective myopia to understand the sometimes counterintuitive outcomes of collective adaptation. We call for a transdisciplinary, quantitative and societally useful social science that can help us to understand our rapidly changing and ever more complex societies, avoid collective disasters and reach the full potential of our ability to organize in adaptive collectives.

Publisher Correction: Social learning strategies for matters of taste.

The version of the Supplementary Information file that was originally published with this Article was not the latest version provided by the authors. In the captions of Supplementary Figs. 2 and 8, the median standard error values were reported to be 0.0028 in both cases; instead, in both instances, the values should have been 0.0015. These have now been updated and the Supplementary Information file replaced.

Social learning strategies for matters of taste.

Most choices people make are about 'matters of taste', on which there is no universal, objective truth. Nevertheless, people can learn from the experiences of individuals with similar tastes who have already evaluated the available options-a potential harnessed by recommender systems. We mapped recommender system algorithms to models of human judgement and decision-making about 'matters of fact' and recast the latter as social learning strategies for matters of taste. Using computer simulations on a large-scale, empirical dataset, we studied how people could leverage the experiences of others to make better decisions. Our simulations showed that experienced individuals can benefit from relying mostly on the opinions of seemingly similar people; by contrast, inexperienced individuals cannot reliably estimate similarity and are better off picking the mainstream option despite differences in taste. Crucially, the level of experience beyond which people should switch to similarity-heavy strategies varies substantially across individuals and depends on how mainstream (or alternative) an individual's tastes are and the level of dispersion in taste similarity with the other people in the group.

Social learning strategies modify the effect of network structure on group performance.

The structure of communication networks is an important determinant of the capacity of teams, organizations and societies to solve policy, business and science problems. Yet, previous studies reached contradictory results about the relationship between network structure and performance, finding support for the superiority of both well-connected efficient and poorly connected inefficient network structures. Here we argue that understanding how communication networks affect group performance requires taking into consideration the social learning strategies of individual team members. We show that efficient networks outperform inefficient networks when individuals rely on conformity by copying the most frequent solution among their contacts. However, inefficient networks are superior when individuals follow the best member by copying the group member with the highest payoff. In addition, groups relying on conformity based on a small sample of others excel at complex tasks, while groups following the best member achieve greatest performance for simple tasks. Our findings reconcile contradictory results in the literature and have broad implications for the study of social learning across disciplines.