Algorithmic Management: The Role of AI in Managing Workforces

Successful implementation requires new competencies and ethical considerations.

Mohammad Hossein Jarrahi, Mareike Möhlmann, and Min Kyung Lee Reading Time: 9 min 

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    • With the help of digital technology, complex managerial tasks, such as the supervision of employees and assessment of job candidates, can now be taken over by machines. While still in its early stages, algorithmic management — the delegation of managerial functions to algorithms in an organization — is becoming a key part of AI-driven digital transformation in companies.

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    ACKNOWLEDGMENTS

    1. M.K. Lee, “Understanding Perception of Algorithmic Decisions: Fairness, Trust, and Emotion in Response to Algorithmic Management,” Big Data & Society 5, no. 1 (January-June 2018).

    ACKNOWLEDGMENTS

    2. M.K. Lee, “Understanding Perception of Algorithmic Decisions: Fairness, Trust, and Emotion in Response to Algorithmic Management,” Big Data & Society 5, no. 1 (January-June 2018).

    ACKNOWLEDGMENTS

    3. M.K. Lee, “Understanding Perception of Algorithmic Decisions: Fairness, Trust, and Emotion in Response to Algorithmic Management,” Big Data & Society 5, no. 1 (January-June 2018).

    ACKNOWLEDGMENTS

    4. M.K. Lee, “Understanding Perception of Algorithmic Decisions: Fairness, Trust, and Emotion in Response to Algorithmic Management,” Big Data & Society 5, no. 1 (January-June 2018).

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    About the Author

    Mohammad Hossein Jarrahi is an associate professor at the UNC School of Information and Library Science. Mareike Möhlmann is assistant professor in the Information and Process Management department at Bentley University. Min Kyung Lee is an assistant professor in the School of Information at the University of Texas at Austin.
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    Acknowledgments

    1. U. Leicht-Deobald, T. Busch, C. Schank, et al., “The Challenges of Algorithm-Based HR Decision-Making for Personal Integrity,” Journal of Business Ethics 160, no. 2 (December 2019): 377-392. 2. M. Möhlmann, L. Zalmanson, O. Henfridsson, et al., “Algorithmic Management of Work on Online Labor Platforms: When Matching Meets Control,” MIS Quarterly 45, no. 4 (December 2020): 1999-2022. 3. M.K. Lee, “Understanding Perception of Algorithmic Decisions: Fairness, Trust, and Emotion in Response to Algorithmic Management,” Big Data & Society 5, no. 1 (January-June 2018). 4. M.H. Jarrahi, G. Newlands, M.K. Lee, et al. “Algorithmic Management in a Work Context,” Big Data & Society 8, no. 2 (July 2021). 5. M. Möhlmann and O. Henfridsson, “What People Hate About Being Managed by Algorithms, According to a Study of Uber Drivers,” Harvard Business Review, Aug. 30, 2019, https://hbr.org. 6. A. Zhang, A. Boltz, C.W. Wang, et al., “Algorithmic Management Reimagined for Workers and by Workers: Centering Worker Well-Being in Gig Work,” CHI Conference on Human Factors in Computing Systems, April 29-May 5. 2022: 1-20. 7. M.H. Jarrahi, “Artificial Intelligence and the Future of Work: Human-AI Symbiosis in Organizational Decision-Making,” Business Horizons 61, no. 4 (July-August 2018): 577-586. 8. M.H. Jarrahi, S. Kenyon, A. Brown, et al., “Artificial Intelligence: A Strategy to Harness Its Power Through Organizational Learning,” Journal of Business Strategy, forthcoming. 9. P.R. Daugherty and H. James Wilson, “Human + Machine: Reimagining Work in the Age of AI” (Cambridge, Massachusetts: Harvard Business Press, 2018). 10. R. Courtland, “Bias Detectives: The Researchers Striving to Make Algorithms Fair,” Nature, June 20, 2018, www.nature.com. 11. M. Möhlmann, C. Salge, and M. Marabelli, “Algorithm Sensemaking: How Platform Workers Make Sense of Algorithmic Management,” Journal of the Association for Information Systems 24, no. 1 (May 2022). 12. K. Martin, “Ethical Implications and Accountability of Algorithms,” Journal of Business Ethics 160 (December 2019): 835-850. 13. Möhlmann, “What People Hate About Being Managed.”

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