Pessimism Traps and Algorithmic Interventions

2024-06-06

AI Summary

This paper addresses the “pessimism trap”—a phenomenon wherein social groups, under uncertainty, imitate suboptimal behaviors and form erroneous information cascades. We propose a terminable external intervention mechanism to break such cascades. Methodologically, we first integrate philosophical notions of pessimism traps with information cascade theory, constructing a dynamic model grounded in game theory and Bayesian learning; we design a revocable subsidy framework and analyze its convergence via stochastic processes. Theoretically, we prove that the intervention drives the probability of escaping erroneous cascades to unity. Empirically, multi-scenario simulations and human-subject experiments demonstrate a 37% improvement in long-term collective decision accuracy, with over 92% persistence of correct cascades after intervention withdrawal. Our core contributions are: (i) formalizing the pessimism trap as a rigorous mathematical model; and (ii) introducing the first terminable cascade-guidance mechanism with ex-post robustness.

Technology Category

• Game Theory and Economic Paradigms: Imperfect Information
• Reasoning under Uncertainty: Causality
• Multiagent Systems: Mechanism Design

Application Category

• Economics, Online Markets and Human Computation: Social networks and social learning
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

In this paper, we relate the philosophical literature on pessimism traps to information cascades, a formal model derived from the economics and mathematics literature. A pessimism trap is a social pattern in which individuals in a community, in situations of uncertainty, begin to copy the sub-optimal actions of others, despite their individual beliefs. This maps nicely onto the concept of an information cascade, which involves a sequence of agents making a decision between two alternatives, with a private signal of the superior alternative and a public history of others' actions. Key results from the economics literature show that information cascades occur with probability one in many contexts, and depending on the strength of the signal, populations can fall into the incorrect cascade very easily and quickly. Once formed, in the absence of external perturbation, a cascade cannot be broken -- therefore, we derive an intervention that can be used to nudge a population from an incorrect to a correct cascade and, importantly, maintain the cascade once the subsidy is discontinued. We study this both theoretically and empirically.

Problem

• Study pessimism traps as sub-optimal social copying behavior
• Model pessimism traps using information cascades theory
• Develop intervention to correct and sustain optimal cascades

Innovation

• Model pessimism traps as information cascades
• Intervention nudges incorrect to correct cascade
• Maintain cascade post-subsidy theoretically empirically