Machines as teammates: A research agenda on AI in team collaboration

作者：Isabella Seeber, Eva Bittner, Robert O. Briggs, Triparna de Vreede, Gert‐Jan de Vreede, Aaron Elkins, Ronald Maier, Alexander Benedikt Merz, Sarah Oeste-Reiß, Nils Randrup, Gerhard Schwabe, Matthias Söllner · 发表于：Information & Management · 年份：2019 · DOI：10.1016/j.im.2019.103174 · 被引用次数：769 · 研究领域：Information Systems Theories and Implementation、Team Dynamics and Performance、Ethics and Social Impacts of AI

What if artificial intelligence (AI) machines became teammates rather than tools? This paper reports on an international initiative by 65 collaboration scientists to develop a research agenda for exploring the potential risks and benefits of machines as teammates (MaT). They generated 819 research questions. A subteam of 12 converged them to a research agenda comprising three design areas – Machine artifact, Collaboration, and Institution – and 17 dualities – significant effects with the potential for benefit or harm. The MaT research agenda offers a structure and archetypal research questions to organize early thought and research in this new area of study.