How social learning strategies boost or undermine decision making in groups

Social interactions resulting in emergent collective behaviour play a key role in almost all layers of society, from local, small-scale interactions, such as people crossing the street, to global, large-scale interactions, such as the spread of fake news on online platforms. In our digital and interconnected world, it is increasingly important to understand the emergence of beneficial or detrimental collective dynamics. The characteristics of such dynamics are expected to depend greatly on the nature of information individuals have personally acquired and how they learn from others. Yet, how the decision-making processes shape the resulting collective dynamics remains poorly understood. When do individuals seek more information from social sources? How do individuals reap the benefits when navigating in social environments, and when do they fail to do so? This dissertation aims to answer these questions extending established theories and frameworks from individual decision-making into the social realm. This approach allows for the operationalization of personal and social information in a theory-driven manner, thereby achieving a deeper understanding of the individual-level decision process. The first chapter provides a introductory overview of the interplay between personal information use, social learning strategies and collective dynamics, and introduces the key theories and models I will expand on in this dissertation. In Chapter 2, inspired by Brunswick's lens model, I investigate how individuals form beliefs about the meaning of ecological structures (i.e., cues). Here, participants had to categorize images based on multiple cues, the meaning of which had to be learned over trials. I showed that participants observing the same cues formed different beliefs about the cue meanings. This diversity in cue beliefs is, in turn, an important process governing the quality of social information. The greater this diversity, the more independent personal information is, and the stronger the potential for social information use. Participants, however, failed to realize the full potential of this diversity because they only changed their personal decisions if a large majority disagreed with them. Simulating different strategies of social information use, I show that this reliance on strongly agreeing majorities impedes individuals from benefiting from diversity. This chapter thus identifies diversity in cue beliefs as an important factor allowing individuals in groups to benefit from the wisdom of each other, while simultaneously highlighting the importance of the individuals' social learning strategies to exploit this diversity. Chapter 3 dives deeper into the social learning strategies individuals use. By carefully controlling the social information displayed to participants, the study in this chapter provides an in-depth analysis of social learning strategies. Participants were confronted with an estimation task. They first provided an independent estimate, after which they observed estimates of others. Using Bayesian modelling techniques, I show that the incorporation of others' opinions strongly depends on how consistent those opinions are with an individual's own opinion and the degree of agreement among others. Individuals also strongly differ in the social learning strategies they use. These results elucidate what aspects are conducive for people to change their minds and contribute to the understanding of how individuals’ social information use shapes opinion and information dynamics in our interconnected society. In Chapter 4, I embed individuals a in temporal dynamic system which allows the investigation of the use of information in interaction with the emergent collective dynamic. Here, my focus is on social interactions where multiple people make decisions sequentially and thereby are simultaneously emitters and receivers of social information. To shed light on the unfolding dynamic in such settings, I will introduce the social drift-diffusion model (DDM). The model allows the investigation of the cognitive processes underlying the integration of personal and social information dynamically over time, and the subsequent collective dynamic. Analysis of the data shows that correct information spreads when the participants’ confidence reflects accuracy and when more confident participants decide faster. Under these conditions, later-deciding participants are likely to adopt social information and thereby to amplify the correct signal provided by early-deciding participants. The social DDM successfully captures all the key dynamics observed in the social system, revealing the cognitive underpinnings of information cascades in social systems. The general principles of personal and social information use that emerge from Chapter 4 allow to investigate the optimal behaviour when deciding sequentially. In Chapter 5, I develop an agent-based version of the social DDM and embed it in evolutionary algorithms, allowing the identification of evolutionarily advantageous strategies. I show that the individuals' decision time should depend on the quality of information, with the most accurate individuals deciding first. For all later.deciding individuals it is evolutionary advantageous to imitate the (often accurate) first decision. When introducing asymmetric error costs, single individuals should develop response biases to avoid the more costly error. In groups, however, such response biases can have dramatic consequences, as these biases are likely to be amplified in the group. As a result, individuals in large groups should use much weaker response biases to benefit from social information. I conclude that individuals facing asymmetric error costs in social environments need to carefully trade off the expressed response bias and sensitivity to social information to avoid the more costly error but simultaneously benefit from the collective. Overall, this thesis deepens our understanding of social dynamics by accounting for individual-level decision-making processes across various choice problems. I show that the behaviour of individuals in social environments can significantly differ depending on the personal information individuals possess and the strategies individuals use. Furthermore, I highlight the importance of accounting for such differences to predict the emergence of beneficial or detrimental dynamics in social environments

How the cognitive mechanisms underlying fast choices influence information spread and response bias amplification in groups

Behavioural cascades through social reinforcement are ubiquitous in human and animal groups. Nonetheless, we only have a rudimentary understanding of which choices are more likely to initiate cascades. Here we investigate the role of response time (RT) asymmetries (i.e., one choice alternative being selected faster than the other) in shaping behavioural cascades by combining an empirical and modelling approach. RT asymmetries are found in a wide range of decision-making contexts, including police shooting, risky choice, and memory retrieval. How they shape collective dynamics, is, however, unknown. Applying evidence accumulation models to analyse behaviour in a sequential choice paradigm, we show that RT asymmetries crucially shape behavioural cascades. Using simulations, we show that especially start point biases (and to a less extent varying drift rates) can initiate cascades, as they lead to rapid choices for one choice alternative. Our results highlight the importance of RT asymmetries in shaping collective dynamics

Data from: Ephemeral resource availability makes wild guppies more social

Resource availability and sociality are tightly coupled. Sociality facilitates resource access in a wide range of animal species. Simultaneously, resource availability may change sociality. However, experimental evidence for resource-driven social changes in the wild, beyond local aggregations at the resource, remains scarce. Moreover, it is largely unclear how potential changes in sociality relate to the social foraging benefits obtained by individual group members. Here, we recorded immediate and prolonged changes in social dynamics following ephemeral food availability in 18 mixed-sex Trinidadian guppies (Poecilia reticulata) groups in natural rainforest pools. Using a counter-balanced within-group design, the social associations within each group was observed before, between and after ephemeral patch availability for two consecutive days. We show that groups increased their time spent socially two-fold following ephemeral food patch, but not control (empty) patch, availability. Groups with stronger foraging motivation, measured as the average proportion of fish feeding, showed a stronger increase in sociality. This resource-induced increase in sociality was still detectable the next day. Increase in the time spent socially by a group also positively correlated with the more frequent arrival at detected food patches for individual members of motivated groups, which, in turn, correlated strongly with individual food consumption. Our study causally demonstrates that changes in ephemeral resource availability can induce rapid, substantial, and prolonged changes in the social dynamics of wild fish and that this change positively correlated with individual foraging success. Further research is needed to investigate whether this social change is a cause or consequence of individual foraging success and why some groups respond more strongly than others

Survey data from Individuals fail to reap the collective benefits of diversity because of over-reliance on personal information

The reported beliefs about the cue

Choice data from Individuals fail to reap the collective benefits of diversity because of over-reliance on personal information

The decisions of the participant

Supplementary Information from Individuals fail to reap the collective benefits of diversity because of over-reliance on personal information

Supplementary Informatio