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Cognitive Challenges in Human–Artificial Intelligence Collaboration: Investigating the Path Toward Productive Delegation

Author

Listed:
  • Andreas Fügener

    (University of Cologne, 50923 Cologne, Germany)

  • Jörn Grahl

    (University of Cologne, 50923 Cologne, Germany)

  • Alok Gupta

    (University of Minnesota, Minneapolis, Minnesota 55455)

  • Wolfgang Ketter

    (University of Cologne, 50923 Cologne, Germany; Erasmus University Rotterdam, 3062 PA Rotterdam, Netherlands)

Abstract

We study how humans make decisions when they collaborate with an artificial intelligence (AI) in a setting where humans and the AI perform classification tasks. Our experimental results suggest that humans and AI who work together can outperform the AI that outperforms humans when it works on its own. However, the combined performance improves only when the AI delegates work to humans but not when humans delegate work to the AI. The AI’s delegation performance improved even when it delegated to low-performing subjects; by contrast, humans did not delegate well and did not benefit from delegation to the AI. This bad delegation performance cannot be explained with some kind of algorithm aversion. On the contrary, subjects acted rationally in an internally consistent manner by trying to follow a proven delegation strategy and appeared to appreciate the AI support. However, human performance suffered as a result of a lack of metaknowledge—that is, humans were not able to assess their own capabilities correctly, which in turn led to poor delegation decisions. Lacking metaknowledge, in contrast to reluctance to use AI, is an unconscious trait. It fundamentally limits how well human decision makers can collaborate with AI and other algorithms. The results have implications for the future of work, the design of human–AI collaborative environments, and education in the digital age.

Suggested Citation

  • Andreas Fügener & Jörn Grahl & Alok Gupta & Wolfgang Ketter, 2022. "Cognitive Challenges in Human–Artificial Intelligence Collaboration: Investigating the Path Toward Productive Delegation," Information Systems Research, INFORMS, vol. 33(2), pages 678-696, June.
    • Handle: RePEc:inm:orisre:v:33:y:2022:i:2:p:678-696
    DOI: 10.1287/isre.2021.1079
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    14. Wang, Weisha & Wang, Yichuan & Chen, Long & Ma, Rui & Zhang, Minhao, 2024. "Justice at the Forefront: Cultivating felt accountability towards Artificial Intelligence among healthcare professionals," Social Science & Medicine, Elsevier, vol. 347(C).
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