A contest study to reduce attractiveness-based discrimination in social judgment

Area of Science:

• Social Psychology
• Behavioral Science
• Decision Making

Background:

• Discrimination in evaluations is a primary driver of global social inequality.
• Existing evidence on psychological interventions to prevent bias is fragmented across diverse methods and populations.
• Developing context-independent, reliable best practices for reducing discrimination remains a challenge.

Purpose of the Study:

• To solicit and evaluate psychological interventions aimed at reducing discrimination based on physical attractiveness.
• To identify effective strategies for mitigating biased evaluations in decision-making tasks.
• To understand the mechanisms through which interventions impact decision noise and bias.

Main Methods:

• A large-scale research contest involving over 20,000 participants across four data collection rounds.
• Utilized a signal detection theory approach to analyze the effectiveness of 30 solicited interventions.
• Interventions were tested on a hypothetical admissions task and later in a political affiliation discrimination domain.

Main Results:

• Two interventions successfully reduced discrimination by decreasing both decision noise and bias.
• Two other interventions reduced discrimination by targeting either noise or bias alone.
• Effective interventions often directed attention to decision-relevant criteria and away from biasing information.
• Intervention effects replicated in a political affiliation discrimination task and generalized to individuals with hiring experience.

Conclusions:

• Developing impactful, flexible, and scalable strategies for reducing discrimination requires further investment.
• Identifying reliable methods to alter discriminatory behavior is complex.
• Interventions that focus attention on relevant criteria show promise for reducing bias in evaluations.