Aon's Assessment Solutions Consultant David Tomczak and Vivian Liu, Leadership Advisory Consultant are joined by Manuel Gonzalez, PhD Candidate, I-O Psychology at Baruch College & the Graduate Center, CUNY to discuss their research and findings on candidate reactions to the use of AI in talent assessment.
Artificial intelligence and machine learning are changing how organizations make employee selection decisions. AI-based assessments can help organizational make better decisions by processing large amounts of applicant data faster and more efficiently, which can improve improve processes for candidates and organizations.
However, despite the growing interest in automating hiring processes with AI and machine learning concerns around fairness, transparency, privacy, and insufficient human interaction persist.
David, Vivian and Manuel share how their team formulated two strategies to improve candidate reactions toward AI-driven hiring processes:
- The concern about the lack of human interaction might be improved if AI supplemented human decision-making, rather than being the sole decision-making source.
- Grounding AI/ML algorithms in well-established psychological theories could make them easier for organizations to understand, explain, and (importantly) defend.
If these two strategies could be adopted in the development of AI/ML-based talent decision-making processes, would people react more favorably toward such tools? Watch the webinar above to learn more about their research, the findings and best practices for implementing AI-augmented talent assessments.
About the AuthorFollow on Linkedin Visit Website More Content by Aon's Assessment Solutions