Stubborn Reliance on Intuition and Subjectivity in Employee Selection
Abstract
The focus of this article is on implicit beliefs that inhibit adoption of selection decision aids (e.g., paper-and-pencil tests, structured interviews, mechanical combination of predictors). Understanding these beliefs is just as important as understanding organizational constraints to the adoption of selection technologies and may be more useful for informing the design of successful interventions. One of these is the implicit belief that it is theoretically possible to achieve near-perfect precision in predicting performance on the job. That is, people have an inherent resistance to analytical approaches to selection because they fail to view selection as probabilistic and subject to error. Another is the implicit belief that prediction of human behavior is improved through experience. This myth of expertise results in an overreliance on intuition and a reluctance to undermine one’s own credibility by using a selection decision aid.
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Personnel selection remains a domain in which professional intuition is frequently valued despite evidence supporting more structured approaches.
“In recruitment, this tendency is particularly relevant because personnel selection remains a domain in which professional intuition is frequently valued despite evidence supporting more structured approaches (Highhouse 2008).”
From When Recruiters Meet Algorithms: Advice Taking and Bias in AI‐Assisted Recruitment (2026) · cites this paper as Highhouse 2008
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Hausknecht, J. P., Day, D. V., & Thomas, S. C. (2004) · Personnel Psychology · doi:10.1111/j.1744-6570.2004.00003.x · Cited by 816 · see citing works
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“…regularity, supported by decades of research, has been observed in many different domains, including forecasts of employee performance (see Highhouse, 2008), academic performance (Dawes, 1971; Dawes, 1979), prisoners’ likelihood of recidivism (Thompson, 1952; Wormith & Goldstone, 1984),…”
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Self-citationCheck the box! How to deal with automation bias in AI-based personnel selection
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“…such as paper-pencil tests, standardized interviews, or mechanical, algorithmic approaches, that have been shown to be clearly superior to so-called holistic methods, such as intuitive decisions by HR professionals (Highhouse, 2008; Kuncel et al., 2013; Nolan et al., 2016; Meijer et al., 2020).”
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When Recruiters Meet Algorithms: Advice Taking and Bias in AI‐Assisted Recruitment
Lacroux, A., & Martin Lacroux, C. (2026) · International Journal of Selection and Assessment · doi:10.1111/ijsa.70085
- Authors
- Highhouse, S.
- Affiliations
- Bowling Green State University (US)
- Corresponding author
- Highhouse, Scott
- ORCID
- Highhouse, Scott
- Venue
- Industrial and Organizational Psychology
- Publisher
- Cambridge University Press (CUP)
- Published
- 2008-09
- Volume
- 1
- Issue
- 3
- Pages
- 333-342
- ISSN
- 1754-9426 (ISSN-L)
- 1754-9434
- OpenAlex
- W2171321543
- Cited by
- 498
- References
- 3
- Citations by year
- 2026: 30 · 2025: 34 · 2024: 31 · 2023: 47 · 2022: 47 · 2021: 42 · 2020: 44 · 2019: 32 · 2018: 23 · 2017: 19 · 2016: 15 · 2015: 27 · 2014: 21 · 2013: 17 · 2012: 23
- FWCI
- 30.52
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Industrial and Organizational Psychology (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › Employer Branding and e-HRM
- Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Keywords
- personnel selection, implicit beliefs, intuition, subjectivity, structured interviews, paper-and-pencil tests, performance prediction, organizational constraints
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