# Dynamical-System Model Predicts When Social Learners Impair Collective Performance

**Authors:** Vicky Chuqiao Yang, Mirta Galesic, Harvey McGuinness, Ani Harutyunyan  
**arXiv:** [2104.00770](https://arxiv.org/abs/2104.00770)  
**Date:** 2021-04-01  
**Summary page:** https://www.summarizepaper.com/en/paper/2104.00770v2/

## Key points

- Study by Vicky Chuqiao Yang et al. explores dynamics of collective decision-making in social systems
- Central question: Can groups effectively converge on optimal choice when some rely on learning from others?
- Challenges include multifaceted cognitive strategies, task characteristics, and social influence mechanisms
- Researchers develop mathematical framework based on dynamical system modeling
- Factors considered: proportion of social learners, merits of options, types of conformity responses
- Model predicts critical threshold where proportion of social learners leads to bi-stable state
- Below threshold, high-merit option tends to be favored; above threshold, majority may gravitate towards higher or lower merit option
- Study reconciles conflicting viewpoints on impact of social learners on collective performance
- Offers versatile mathematical framework for exploring diverse dynamics beyond binary choices

## Summary

In their study titled "Dynamical-System Model Predicts When Social Learners Impair Collective Performance," authors Vicky Chuqiao Yang, Mirta Galesic, Harvey McGuinness, and Ani Harutyunyan delve into the intricate dynamics of collective decision-making within social systems. The central question they address is whether a group can effectively converge on the optimal choice when some individuals rely on learning from others rather than independently assessing available options. This inquiry poses significant challenges due to the multifaceted nature of cognitive strategies, task characteristics, and social influence mechanisms that collectively shape decision outcomes. To tackle this complex issue, the researchers develop a comprehensive mathematical framework grounded in dynamical system modeling. By integrating various factors such as the proportion of social learners, the relative merits of different options, and the types of conformity responses present within the group, they aim to elucidate how these elements interact to influence collective decision-making in a binary choice scenario. The model's predictions offer valuable insights into the dynamics at play: notably, it identifies a critical threshold where the proportion of social learners surpasses a tipping point leading to a bi-stable state. In this state, the majority may gravitate towards either the higher- or lower-merit option based on fluctuations and initial conditions. Below this threshold, however, the high-merit option tends to be favored by most individuals in the group. Furthermore, the study sheds light on discrepancies in existing research regarding the impact of social learners on collective performance. By providing a nuanced understanding of how different variables interact within a social system during decision-making processes,this work not only reconciles conflicting viewpoints but also offers a versatile mathematical framework that can be adapted for exploring diverse dynamics beyond binary choices. Ultimately,this research contributes significantly to our comprehension of collective decision-making phenomena and paves the way for further investigations into complex social interactions across various contexts.