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Artificial intelligence and machine learning

Author

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  • Kühl, Niklas
  • Schemmer, Max
  • Goutier, Marc
  • Satzger, Gerhard

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

  • Kühl, Niklas & Schemmer, Max & Goutier, Marc & Satzger, Gerhard, 2025. "Artificial intelligence and machine learning," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 153962, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    • Handle: RePEc:dar:wpaper:153962
    DOI: 10.1007/s12525-022-00598-0
    Note: for complete metadata visit http://tubiblio.ulb.tu-darmstadt.de/153962/
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    References listed on IDEAS

    as
    1. 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).
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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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