Cited by 364Information Systems Theories and ImplementationAI and HR TechnologiesImpact of AI and Big Data on Business and Society

Augmenting the algorithm: Emerging human-in-the-loop work configurations

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Grønsund, Tor, Aanestad, Margunn·2020·The Journal of Strategic Information Systems

Abstract

How do configurations of humans and algorithms evolve as firms adopt artificial intelligence (AI) capabilities, and what are the implications for work and organization? We explored these questions through a two-year long case study of an organization in the international maritime trade that introduced automated algorithmic support for data analysis and prediction work. Drawing on a human–machine configuration perspective, we found that humans and the algorithm were configured and reconfigured in multiple ways over time as the organization dealt with the introduction of algorithmic analysis. In contrast to replacing human work, the emergent configurations required new roles and redistribution of extant expertise to augment and improve the accuracy of the algorithm. Our analysis suggests that the new configuration resembled a human-in-the-loop pattern, comprised of both the augmentation work of auditing (i.e. the generation of a ground truth and assessment of the algorithmic output against this) as well as the work of altering the algorithm and the data acquisition architecture. Our research points to the strategic importance of a human-in-the-loop pattern for organizational reflexivity to ensure that the performance of the algorithm meets the organization’s requirements and changes in the environment.

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  • The deployment of algorithmic management in organizational work introduces novel "human-machine configurations" that could transform relationships between managers and workers and their respective roles.

    “In short, the deployment of algorithmic man-agement in organizational work introduces novel “human–machine configurations” that could transform relationships between managers and workers and their respective roles (Grønsund and Aanestad, 2020).”

    From Algorithmic management in a work context (2021) · cites this paper as Grønsund and Aanestad, 2020

    The Abstract and Conclusion describe new human–algorithm configurations, emerging roles, and the redistribution of work after algorithmic support was introduced. The paper studies algorithmic support for data analysis, however, rather than specifically examining algorithmic management or changes in manager–worker relationships. (LLM, conf=0.86)

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  • AI algorithms can be considered performative: they assist in decision-making, can form organizational processes, or take autonomous decisions, leading to new organizational capabilities.

    “Simultaneously, the AI algorithms can be considered performative in the sense that they assist in decision-making, the extent to which their use can form organizational processes, or even take autonomous decisions (Faraj et al., 2018; Grønsund & Aanestad, 2020) that leads to new organization capabilities through AI.”

    From Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes (2023) · cites this paper as Grønsund & Aanestad, 2020

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2 of the 67 references couldn’t be matched to a known paper.

Research works printed but not linked: 5

  1. DalleMule, L., Davenport, T.H., 2017. What's your data strategy. Harvard Bus. Rev. 95 (3), 112-121.
  2. Galliers, R.D., Newell, S., Shanks, G., Topi, H., 2017. Datification and its human, organizational and societal effects. J. Strateg. Inf. Syst. 26 (3), 185-190.
  3. Jaton, F., 2017. We get the algorithms of our ground truths. Soc. Stud. Sci. 47 (6), 811-840.
  4. Lebovitz, S., Levina, N., Lifshitz-Assaf, H., 2019. Doubting the Diagnosis: How Artificial Intelligence Increases Ambiguity during Professional Decision Making. Available at SSRN 3480593.
  5. Mazmanian, M., Cohn, M., Dourish, P., 2014. Dynamic reconfiguration in planetary exploration. MIS Quart. 38 (3), 831-848.

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Authors
Grønsund, T., & Aanestad, M.
Affiliations
University of Oslo (NO)
Corresponding author
Grønsund, Tor
Venue
The Journal of Strategic Information Systems
Publisher
Elsevier BV
Published
2020-06
Volume
29
Issue
2
Pages
101614
ISSN
0963-8687 (ISSN-L)
OpenAlex
W3037276488
Cited by
364
References
67
Citations by year
2026: 55 · 2025: 70 · 2024: 56 · 2023: 102 · 2022: 42 · 2021: 37 · 2020: 2
FWCI
61.20
Type
journal article
Language
en
Open access
Locations
  • The Journal of Strategic Information Systems (publishedVersion, cc-by-nc-nd)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by-nc-nd)
  • NORA - Norwegian Open Research Archives (submittedVersion, other-oa)
Funders
Norges Forskningsråd
Topics
  • Social Sciences › Sociology and Political Science › Information Systems Theories and Implementation
  • Social Sciences › Business, Management and Accounting › Organizational Behavior and Human Resource Management › AI and HR Technologies
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
Keywords
human-in-the-loop, artificial intelligence adoption, algorithmic auditing, maritime trade, algorithmic prediction, data acquisition architecture, human-algorithm collaboration

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