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Artificial Intelligence and the Management Science Practitioner: Rational Choice and Artificial Intelligence

Author

Listed:
  • Varghese S. Jacob

    (Faculty of Accounting and Management Information Systems, The Ohio State University, 1775 College Road, Columbus, Ohio 43210-1399)

  • James C. Moore

    (Krannert Graduate School of Management, Purdue University, West Lafayette, Indiana 47907)

  • Andrew B. Whinston

    (Krannert Graduate School of Management and Department of Computer Science, Purdue University, Purdue University, West Lafayette, Indiana 47907)

Abstract

Current research in AI, while focusing on the practical problems associated with knowledge engineering and design issues, has not addressed a key question: What is a theoretical basis for AI? This paper addresses the issue of defining a theoretical basis for AI and thus illustrating the common bonds between AI, computer science, economics, psychology, management science, and operations research (MS/OR).

Suggested Citation

  • Varghese S. Jacob & James C. Moore & Andrew B. Whinston, 1988. "Artificial Intelligence and the Management Science Practitioner: Rational Choice and Artificial Intelligence," Interfaces, INFORMS, vol. 18(4), pages 24-35, August.
    • Handle: RePEc:inm:orinte:v:18:y:1988:i:4:p:24-35
    DOI: 10.1287/inte.18.4.24
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    Cited by:

    1. Osório, António (António Miguel) & Pinto, Alberto Adrego, 2019. "Information, uncertainty and the manipulability of artifcial intelligence autonomous vehicles systems," Working Papers 2072/376028, Universitat Rovira i Virgili, Department of Economics.
    2. Alina Köchling & Marius Claus Wehner, 2020. "Discriminated by an algorithm: a systematic review of discrimination and fairness by algorithmic decision-making in the context of HR recruitment and HR development," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 795-848, November.

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