| Abstract |
Despite AI’s proven decision-making performance, adoption remains low in uncertain, repetitive business environments. Decision-makers often doubt optimal AI recommendations when short-term outcomes suffer from randomness (e.g., supply or demand fluctuations). This randomness leads to a cycle of distrust in the optimal AI recommendations, as users increasingly discount AI advice after observing poor short-term results. Two proposed solutions to increase AI adoption are providing deductive reasoning through explanations or inductive reasoning through ‘side-by-side’ performance benchmarking. While empirical studies demonstrate that these solutions can improve reliance and trust, most focus on tasks evaluated solely by the AI’s prediction accuracy. However, accuracy proves insufficient in uncertain environments when errors impact objectives differently. Such everyday decision environments create a critical gap in understanding how these solutions affect AI adoption in repetitive managerial decision-making.
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| Biography |
Professor Bin Gu is Everett W. Lord Distinguished Faculty Scholar, Professor and Department Chair of Information Systems at the Questrom School of Business, Boston University.
Professor Gu’s research interests are in using information technologies and artificial intelligence to address information asymmetry and social inequity in business and society. He examines more specifically information asymmetry and social inequity in fintech, digital platforms, the future of work, online social media, social network, and online retailing. His work has appeared in leading business academic journals including Management Science, MIS Quarterly, Information Systems Research, Journal of Management Information Systems and others and has received over 16000 citations. Professor Gu was awarded the INFORMS Information Systems Society Distinguished Fellow Award in 2022 for his outstanding intellectual contributions to the information systems discipline.
Professor Gu obtained his PhD and MA degrees from the Wharton School of Business at University of Pennsylvania and his BEng degrees in International Business and Computer Science from Shanghai Jiaotong University. Before joining Boston University, Professor Gu was the Gladys Davis Distinguished Professor and associate dean of China Programs at the W.P. Carey School of Business at Arizona State University. He also previously served on the faculty of Shanghai Advanced Institute of Finance (sabbatical) and the University of Texas at Austin. Before coming to academia, Professor Gu worked for Arthur Andersen as a consultant.
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