"Hi. I'm Molly, Your Virtual Interviewer!" -- Exploring the Impact of Race and Gender in AI-powered Virtual Interview Experiences
Shreyan Biswas, Ji-Youn Jung, Abhishek Unnam, Kuldeep Yadav, Shreyansh, Gupta, Ujwal Gadiraju

TL;DR
This study investigates how the race and gender of AI virtual interviewers influence candidate perceptions in asynchronous video interviews, revealing that candidate demographics significantly affect their experience and perceptions of fairness and privacy.
Contribution
The paper provides empirical evidence on the impact of virtual interviewer demographics on candidate perceptions, addressing a gap in understanding AI's role in bias mitigation during virtual interviews.
Findings
Candidate demographics significantly alter perceptions of the interview process.
Demographic attributes of AI interviewers do not significantly impact overall candidate experience.
Social presence and perception of the interviewer mediate perceptions of fairness and privacy.
Abstract
The persistent issue of human bias in recruitment processes poses a formidable challenge to achieving equitable hiring practices, particularly when influenced by demographic characteristics such as gender and race of both interviewers and candidates. Asynchronous Video Interviews (AVIs), powered by Artificial Intelligence (AI), have emerged as innovative tools aimed at streamlining the application screening process while potentially mitigating the impact of such biases. These AI-driven platforms present an opportunity to customize the demographic features of virtual interviewers to align with diverse applicant preferences, promising a more objective and fair evaluation. Despite their growing adoption, the implications of virtual interviewer identities on candidate experiences within AVIs remain underexplored. We aim to address this research and empirical gap in this paper. To this end,…
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Taxonomy
TopicsEthics and Social Impacts of AI · Impact of AI and Big Data on Business and Society · AI in Service Interactions
