Paradoxes of AI in Organizations

Abstract

Divergent and often contradictory findings suggest that the study of AI in organizations is rife with paradox, persistent contradictions between interdependent elements (Schad, Lewis, Raisch, & Smith, 2016); And yet, management research has thus far fallen short in capturing the complexity of AI’s organizational and societal implications (Raisch & Krakowski, 2021). Given the sheer preponderance of contradictory perspectives in the management literature on AI, such a meta-theoretical approach offers substantive opportunity for capturing the full richness of the dynamic interactions between AI and organizational contexts. For this symposium session, we hope to shine a spotlight on the tensions evoked by AI in organizations and encourage openness to complexity in the rapidly growing literature on AI’s role in organizational systems. Specifically, our presentations will discuss the interdependencies and tensions involved in navigating over-reliance and under-reliance on AI, control and empowerment of employees via AI-powered systems, collaboration and competition with AI as a counterpart, scientific and commercial demands in AI development, and learning and performance goals in implementing AI tools on an organizational level. Navigating Complexity and Tensions in AI Governance in Healthcare Author: Elisabeth Yang; Yale University When Doing the Right Thing is a Moving Target: How Ethical Concerns Evolve as AI Progresses Author: Emmanuelle Vaast; McGill University Algorithmic Frenemies: When Cooperating While Competing with Generative AI Facilitates Learning Author: Benjamin Stephen Poag; New York University Author: Batia Mishan Wiesenfeld; New York University How Does Information Transparency Influence Employees on a Digital Work Platform? Author: Yan Zhang; Beyond Technology: How Organizations Shape Human-AI Collaboration Author: Nan Jia; University of Southern California Author: Albert Choi Roh; University of Southern California

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