Management in the Age of Machine Intelligence
Richard E. Saouma, Todd R. Zenger, Anthony Joseph Casey, Anna Deréky, Joshua S. Gans, Eirik Sjåholm Knudsen, Lasse B. Lien, Kyle J. Mayer, Stefano Brusoni, Russ McBride, Georg von Krogh, Robert Joseph Wuebker · Academy of Management Proceedings · 2018
The purpose of this panel symposium is to explore the implications of machine learning and algorithmic organization on management theory. We have gathered together a diverse collection of scholars contributing to the fields of economics, strategy, organization theory, and law who will provide a series of brief presentations to prime our panel discussion/audience Q&A session. Panel presentations frame our session by exploring the potential impact of machine learning and algorithmic organization on contracting design, organizational boundaries (and new organizational forms), strategic decision making (including hybrid decision-making and governance), and human capital management. Presenters and topics are detailed below in the session agenda. Each presenter is currently engaged in the development of work that uses the current interest in machine learning/AI as a fulcrum to examine topics of conceptual and practical interest to management, strategy, and organizations scholars. A subsequent panel discussion attempts to synthesize these insights and push our collective thinking forward as we jointly try to divine where, precisely, are boundaries between machine intelligence and organizations…if, in fact, such boundaries even exist.