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Ethical Management of Artificial Intelligence

Author

Listed:
  • Alfred Benedikt Brendel

    (Business Informatics, Especially Intelligent Systems and Services, Technische Universität Dresden, 01169 Dresden, Germany)

  • Milad Mirbabaie

    (Information Systems & Industrial Services, University of Bremen, 28334 Bremen, Germany)

  • Tim-Benjamin Lembcke

    (Information Management, University of Goettingen, 37073 Göttingen, Germany)

  • Lennart Hofeditz

    (Professional Communication in Electronic Media/Social Media, University of Duisburg-Essen, 47057 Duisburg, Germany)

Abstract

With artificial intelligence (AI) becoming increasingly capable of handling highly complex tasks, many AI-enabled products and services are granted a higher autonomy of decision-making, potentially exercising diverse influences on individuals and societies. While organizations and researchers have repeatedly shown the blessings of AI for humanity, serious AI-related abuses and incidents have raised pressing ethical concerns. Consequently, researchers from different disciplines widely acknowledge an ethical discourse on AI. However, managers—eager to spark ethical considerations throughout their organizations—receive limited support on how they may establish and manage AI ethics. Although research is concerned with technological-related ethics in organizations, research on the ethical management of AI is limited. Against this background, the goals of this article are to provide a starting point for research on AI-related ethical concerns and to highlight future research opportunities. We propose an ethical management of AI (EMMA) framework, focusing on three perspectives: managerial decision making, ethical considerations, and macro- as well as micro-environmental dimensions. With the EMMA framework, we provide researchers with a starting point to address the managing the ethical aspects of AI.

Suggested Citation

  • Alfred Benedikt Brendel & Milad Mirbabaie & Tim-Benjamin Lembcke & Lennart Hofeditz, 2021. "Ethical Management of Artificial Intelligence," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:4:p:1974-:d:498027
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    References listed on IDEAS

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    3. Milad Mirbabaie & Stefan Stieglitz & Nicholas R. J. Frick, 2021. "Hybrid intelligence in hospitals: towards a research agenda for collaboration," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 365-387, June.
    4. Carlos Cacciuttolo & Yaneth Vásquez & Deyvis Cano & Fernando Valenzuela, 2023. "Research Thesis for Undergraduate Engineering Programs in the Digitalization Era: Learning Strategies and Responsible Research Conduct Road to a University Education 4.0 Paradigm," Sustainability, MDPI, vol. 15(14), pages 1-27, July.
    5. Dmitry A. Ruban, 2022. "Analytical Review of Conjugation of the Ethical Bases of Artificial Intelligence Implementation and Ecologization in Corporate Governance," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 21(2), pages 390-418.
    6. Omrani, Nessrine & Rivieccio, Giorgia & Fiore, Ugo & Schiavone, Francesco & Agreda, Sergio Garcia, 2022. "To trust or not to trust? An assessment of trust in AI-based systems: Concerns, ethics and contexts," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    7. Tae Wan Kim & Fabrizio Maimone & Katherina Pattit & Alejo José Sison & Benito Teehankee, 2021. "Master and Slave: the Dialectic of Human-Artificial Intelligence Engagement," Humanistic Management Journal, Springer, vol. 6(3), pages 355-371, December.

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