Federica De Domenico — University of Pavia, INFN #
Imitation vs serendipity in the society  #
Rankings simplify complex systems by ordering entities based on performance, aiding in resource allocation and recognition of top performers. However, they can also mislead, as top performance is often weakly correlated with actual skill, being influenced heavily by luck and the self-reinforcing "rich get richer" effect.  An agent-based model was developed to investigate these dynamics in a synthetic society. The model examines how agents choose actions based on societal benefit and individual ability, factoring in the effects of imitation and randomness (serendipity). The model's simulations reveal that when imitation dominates, societal payoff is high but unevenly distributed, leading to inequality. Conversely, when randomness prevails, outcomes are more egalitarian but with lower overall payoff. A key transition point between these states is identified, characterized by a sharp change in the correlation between agents’ skills and their payoffs, indicating a shift towards a meritocratic society.  The findings suggest that while imitation can concentrate success in a few, serendipitous outcomes foster a fairer distribution of success. This model highlights the complexity of achieving a meritocratic society and the significant role of chance in shaping equitable outcomes.