Developing Racially Ambiguous Job Candidate Avatars with Strong versus Ambiguous Job Candidate Backgrounds in Preparation for a Field Experiment for Enhancing Inclusive Hiring and Reducing Implicit Bias

• Published in: Journal of behavioral and applied management Vol. 24; no. 1; pp. 14 - 25
• Main Authors: Trifilo, Alexa, Blau, Gary
• Format: Journal Article
• Language: English
• Published: Glendale Institute of Behavioral and Applied Management 30.03.2024
• Subjects: Baby boomers; Bias; Candidates; Data collection; Experiments; Females; Generative artificial intelligence; Hiring; Interviews; Literature reviews; Multiculturalism & pluralism; Prejudice; Qualifications; Race; Racial identity; Workforce; Workplace diversity

This study explores the utilization of generative Artificial Intelligence (AI) to create racially ambiguous avatars for job candidate interviews, aiming to enhance inclusive hiring practices and reduce implicit bias. With diversity recognized for boosting organizational performance, addressing hirin...