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Cited by 531AI and HR TechnologiesEthics and Social Impacts of AIImpact of AI and Big Data on Business and Society

The Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance

Open access
Tong, Siliang, Jia, Nan, Luo, Xueming, Fang, Zheng·2021·Strategic Management Journal
DOI 10.1002/smj.3322
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Abstract

Companies are increasingly using artificial intelligence (AI) to provide performance feedback to employees, by tracking employee behavior at work, automating performance evaluations, and recommending job improvements. However, this application of AI has provoked much debate. On the one hand, powerful AI data analytics increase the quality of feedback, which may enhance employee productivity (“deployment effect”). On the other hand, employees may develop a negative perception of AI feedback once it is disclosed to them, thus harming their productivity (“disclosure effect”). We examine these two effects theoretically and test them empirically using data from a field experiment. We find strong evidence that both effects coexist, and that the adverse disclosure effect is mitigated by employees' tenure in the firm. These findings offer pivotal implications for management theory, practice, and public policies. Managerial abstract Artificial intelligence (AI) technologies are bound to transform how companies manage employees. We examine the use of AI to generate performance feedback for employees. We demonstrate that AI significantly increases the accuracy and consistency of the analyses of information collected, and the relevance of feedback to each employee. These advantages of AI help employees achieve greater job performance at scale, and thus create value for companies. However, our study also alerts companies to the negative effect of disclosing using AI to employee that resul…

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  • Some AI systems can provide performance feedback and help employees recognise their successes so they can develop their self-management skills.

    “Some AI systems can also provide performance feedback and help employees recognise their successes so they can develop their self -management skills (Tong et al., 2021).”

    From The Impact of Artificial Intelligence on Workers' Skills: Upskilling and Reskilling in Organisations (2023) · cites this paper as Tong et al., 2021

  • AI-controlled robots and machines can be programmed to perform tasks with a high degree of accuracy and repeatability, reducing the risk of error and improving overall quality.

    “AI -controlled robots and machines, for example, can be programmed to perform tasks with a high degree of accuracy and repeatability, reducing the risk of error and improving overall quality (Tong et al., 2021).”

    From The Impact of Artificial Intelligence on Workers' Skills: Upskilling and Reskilling in Organisations (2023) · cites this paper as Tong et al., 2021

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Research works printed but not linked: 9

  1. Agrawal Ajay McHale J. &Oettl A. (2019).Artificial intelligence scientific discovery and commercial innovation.http://www.esri.go.jp/jp/workshop/190730/esri2019_second_presenter_paper.pdf
  2. Bughin J., 2019, Your AI efforts Won't succeed unless they benefit employees, Harvard Business Review
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  6. MacCarthy M., 2020, AI needs more regulation, not less
  7. Möhlmann M. &Zalmanson L.(2017).Navigating algorithmic management and drivers. Available fromhttps://www.researchgate.net/publication/319965259
  8. National Law Review. (2019).Keeping an eye on artificial intelligence regulation and legislation. Natlawreview.Com. Available fromhttps://www.natlawreview.com/article/keeping-eye-artificial-intelligence-regulation-and-legislation
  9. Premuzic T. C., 2018, As AI makes more decisions, the nature of leadership will change, Harvard Business Review

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Authors
Tong, S., Jia, N., Luo, X., & Fang, Z.
Affiliations
  • Nanyang Technological University (SG)
  • University of Southern California (US)
  • Temple University (US)
  • Sichuan University (CN)
Corresponding author
Fang, Zheng
ORCID
Venue
Strategic Management Journal
Publisher
Wiley
Published
2021-07-12
Volume
42
Issue
9
Pages
1600-1631
ISSN
  • 0143-2095 (ISSN-L)
  • 1097-0266
DOI
10.1002/smj.3322
OpenAlex
W3181487680
Cited by
531
References
59
Citations by year
2026: 138 · 2025: 181 · 2024: 117 · 2023: 64 · 2022: 25 · 2021: 5 · 2020: 1
FWCI
51.33
Type
journal article
Language
en
Open access
Licence
Locations
  • Strategic Management Journal (publishedVersion, cc-by-nc-nd)
  • SSRN Electronic Journal (publishedVersion)
  • DR-NTU (Nanyang Technological University) (submittedVersion)
Topics
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
Keywords
artificial intelligence, performance feedback, employee performance, disclosure effects, employee perceptions of AI, employee tenure, labor productivity, internal communication

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