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Artificial intelligence and machine learning

Author

Listed:
  • Niklas Kühl

    (Karlsruhe Institute of Technology (KIT))

  • Max Schemmer

    (Karlsruhe Institute of Technology (KIT))

  • Marc Goutier

    (Technical University of Darmstadt (TU Darmstadt))

  • Gerhard Satzger

    (Karlsruhe Institute of Technology (KIT))

Abstract

Within the last decade, the application of “artificial intelligence” and “machine learning” has become popular across multiple disciplines, especially in information systems. The two terms are still used inconsistently in academia and industry—sometimes as synonyms, sometimes with different meanings. With this work, we try to clarify the relationship between these concepts. We review the relevant literature and develop a conceptual framework to specify the role of machine learning in building (artificial) intelligent agents. Additionally, we propose a consistent typology for AI-based information systems. We contribute to a deeper understanding of the nature of both concepts and to more terminological clarity and guidance—as a starting point for interdisciplinary discussions and future research.

Suggested Citation

  • Niklas Kühl & Max Schemmer & Marc Goutier & Gerhard Satzger, 2022. "Artificial intelligence and machine learning," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2235-2244, December.
    • Handle: RePEc:spr:elmark:v:32:y:2022:i:4:d:10.1007_s12525-022-00598-0
    DOI: 10.1007/s12525-022-00598-0
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    References listed on IDEAS

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    1. Pär J. Ågerfalk, 2020. "Artificial intelligence as digital agency," European Journal of Information Systems, Taylor & Francis Journals, vol. 29(1), pages 1-8, January.
    2. Kühl, N. & Mühlthaler, M. & Goutier, Marc, 2020. "Supporting customer-oriented marketing with artificial intelligence: automatically quantifying customer needs from social media," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 130106, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Schleiffer, Ralf, 2005. "An intelligent agent model," European Journal of Operational Research, Elsevier, vol. 166(3), pages 666-693, November.
    4. Christian Engel & Philipp Ebel & Jan Marco Leimeister, 2022. "Cognitive automation," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 339-350, March.
    5. Barbara Neuhofer & Bianca Magnus & Krzysztof Celuch, 2021. "The impact of artificial intelligence on event experiences: a scenario technique approach," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 601-617, September.
    6. Oliver Müller & Iris Junglas & Jan vom Brocke & Stefan Debortoli, 2016. "Utilizing big data analytics for information systems research: challenges, promises and guidelines," European Journal of Information Systems, Taylor & Francis Journals, vol. 25(4), pages 289-302, July.
    7. Ritchie, Stephen G., 1990. "A Knowledge- Based Decision Support Architecture for Advanced Traffic Management," University of California Transportation Center, Working Papers qt9818b161, University of California Transportation Center.
    8. Rainer Alt, 2021. "Electronic Markets on the next convergence," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(1), pages 1-9, March.
    9. Scott Thiebes & Sebastian Lins & Ali Sunyaev, 2021. "Trustworthy artificial intelligence," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 447-464, June.
    10. Christian Janiesch & Patrick Zschech & Kai Heinrich, 2021. "Machine learning and deep learning," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 685-695, September.
    11. Fujii, Hidemichi & Managi, Shunsuke, 2018. "Trends and priority shifts in artificial intelligence technology invention: A global patent analysis," Economic Analysis and Policy, Elsevier, vol. 58(C), pages 60-69.
    12. Benjamin Klör & Markus Monhof & Daniel Beverungen & Sebastian Bräuer & Bjoern Niehaves & Tuure Tuunanen & Ken Peffers, 2018. "Design and evaluation of a model-driven decision support system for repurposing electric vehicle batteries," European Journal of Information Systems, Taylor & Francis Journals, vol. 27(2), pages 171-188, March.
    13. Dominik Dellermann & Nikolaus Lipusch & Philipp Ebel & Jan Marco Leimeister, 2019. "Design principles for a hybrid intelligence decision support system for business model validation," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(3), pages 423-441, September.
    14. Fabian Hunke & Daniel Heinz & Gerhard Satzger, 2022. "Creating customer value from data: foundations and archetypes of analytics-based services," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(2), pages 503-521, June.
    15. Benjamin M. Abdel-Karim & Nicolas Pfeuffer & Oliver Hinz, 2021. "Machine learning in information systems - a bibliographic review and open research issues," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 643-670, September.
    16. Frederik Ruelens & Sandro Iacovella & Bert J. Claessens & Ronnie Belmans, 2015. "Learning Agent for a Heat-Pump Thermostat with a Set-Back Strategy Using Model-Free Reinforcement Learning," Energies, MDPI, vol. 8(8), pages 1-19, August.
    17. Ritchie, Stephen G., 1990. "A Knowledge-Based Decision Support Architecture for Advanced Traffic Management," University of California Transportation Center, Working Papers qt7qv4w8kj, University of California Transportation Center.
    18. Robin Hirt & Niklas Kühl & Gerhard Satzger, 2019. "Cognitive computing for customer profiling: meta classification for gender prediction," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(1), pages 93-106, March.
    19. Rainer Alt, 2018. "Electronic Markets and current general research," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(2), pages 123-128, May.
    20. Niklas Kühl & Marius Mühlthaler & Marc Goutier, 2020. "Supporting customer-oriented marketing with artificial intelligence: automatically quantifying customer needs from social media," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(2), pages 351-367, June.
    21. Hoda Ghavamipoor & S. Alireza Hashemi Golpayegani, 2020. "A Reinforcement Learning Based Model for Adaptive Service Quality Management in E-Commerce Websites," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 62(2), pages 159-177, April.
    22. Collins, Christopher & Dennehy, Denis & Conboy, Kieran & Mikalef, Patrick, 2021. "Artificial intelligence in information systems research: A systematic literature review and research agenda," International Journal of Information Management, Elsevier, vol. 60(C).
    23. Shu He & Huaxia Rui & Andrew B. Whinston, 2018. "Social Media Strategies in Product-Harm Crises," Information Systems Research, INFORMS, vol. 29(2), pages 362-380, June.
    24. Andreas Hein & Jörg Weking & Maximilian Schreieck & Manuel Wiesche & Markus Böhm & Helmut Krcmar, 2019. "Value co-creation practices in business-to-business platform ecosystems," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(3), pages 503-518, September.
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    3. Goutier, Marc & Diebel, Christopher & Adam, Martin & Benlian, Alexander, 2024. "Proactive and Reactive Help from Intelligent Agents in Identity-Relevant Tasks," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 142985, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).

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    More about this item

    Keywords

    Machine learning; Artificial intelligence; Terminology; Framework;
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    JEL classification:

    • C0 - Mathematical and Quantitative Methods - - General

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