 Case 14: How Can AI Reduce Bias in Recruiting? (Interview with Polly, a Talent Matching Platform)Roberta Pinna () and
Gianfranco Cicotto
A chapter in Strategic Human Resource Management and Employment Relations, 2022, pp 327-332 from Springer Abstract: Abstract Unconscious bias is a massive problem in the workplace, especially in recruitment, promotion, and performance management and is a significant barrier in efforts to improve diversity and inclusion. Moreover, one of the most crucial sources of competitive advantage is based on human resource efforts through attracting and retaining talented individuals. Competitiveness in recruitment has led organizations to spend more time, effort, and resources in developing tools for the efficient selection of employees with the required skills and aptitude to meet current and future organizational needs (Albert E., 2019; Stone et al., 2015). So how can technology, data, and science help? And what steps does it need to take to minimize bias through technologies like artificial intelligence (AI) rather than perpetuate it? That’s the topic for this week’s podcast, where my guest is Polly, a talent matching platform. With Polly, we will try to understand how AI and behavioral science can help companies reduce bias in recruiting and finding the right person for the right place. Date: 2022 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sptchp:978-3-030-90955-0_30 Ordering information: This item can be ordered from DOI: 10.1007/978-3-030-90955-0_30 Access Statistics for this chapter More chapters in Springer Texts in Business and Economics from Springer |
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