The Purpose of the Study: The purpose of the study is to synthesize existing knowledge on the impact of AI recruiting on workplace diversity, equity, and inclusion (DEI) through a systematic literature review. The study aims to identify research trends, theoretical foundations, methods, contexts, samples, research streams, foci, and findings to provide a comprehensive understanding of the current state of research and suggest future research directions.
Papers Analyzed in This Study: The study identified a total of 574 papers from Web of Science, an enourmous database for scientific papers around the globe. After the strict exclusion and inclusion stages, this study analyzed a total of 30 identified articles published between 2018 and 2024.
The Problem of DEI: The paper highlights that despite long-standing efforts and significant investments in promoting DEI, biases in recruitment processes persist due to deep-rooted societal factors, cultural backgrounds, stereotypes, and individual characteristics. These biases manifest as subconscious discrimination, prejudice, and personal beliefs, making it difficult for organizations to alter or avoid them. The persistence of stereotyping and discrimination over the past century indicates that human-based recruitment remains embedded with biases and discrimination issues.
AI Recruiting as a Solution: AI recruiting offers an alternative path to mitigate discrimination in recruitment processes by enhancing productivity, increasing certainty, and decreasing cost and time. AI-enhanced tools can increase objectivity, consistency, and fairness in personnel recruitment and development processes. Algorithmic decision-making systems can assess each individual’s application with the same criteria and generate consistent feedback quickly, which could potentially mitigate human biases and promote DEI in recruitment.
Contribution to the Field: This study contributes to the related field by providing a comprehensive synthesis of existing research on AI recruiting and workplace DEI. It identifies four prevailing research streams (applicants, decision-makers, mixed perspectives, and algorithms) and highlights the fragmented and interdisciplinary nature of current studies. The study also points out the lack of consistency in findings and calls for more empirical research, cross-disciplinary studies, and theoretical development. By outlining key findings and proposing several future research directions, the study provides a foundation for further investigation and a deeper understanding of the implications of AI recruiting on DEI.
More on: AIS Electronic Library (AISeL) – PACIS 2024 Proceedings: AI Recruiting and Workplace Diversity, Equity, and Inclusion: A Literature Analysis and Pacific Asia Conference on Information Systems (PACIS) 2024 – CHRISTY M.K. CHEUNG
