Maytal Saar-Tsechansky
University of Texas at Austin
Title: The Case for Value-Driven AI Advisors & How to Produce Them
报告摘要: Recent studies highlight the potential of AI to improve high-stakes human decisions in critical domains like healthcare. Despite these promising prospects, AI systems to advice experts in such contexts often fail to deliver tangible value to organizations. In this talk, I will first argue how key properties of AI-assisted high-stakes decision-making contexts are crucial to inform the development of AI advisors that meaningfully benefit decision-makers and organizations. State-of-the-art AI for advising experts is produced independently of the experts and of the organization they intend to benefit. However, I will demonstrate why idiosyncratic properties of these environments, such as an expert’s decision-making behaviors, the patterns shaping experts’ discretion of AI counsel, and the organization’s tolerance of the inherent costs of engagement with AI to improve high-stakes decisions are crucial to inform the development of effective human-AI teams that benefit organizations. I will then present a framework that builds on these understandings to generate personalized and organizationally-aware AI advisors and will share results on its performance. Our results demonstrate not only the opportunity to amplify high-stakes decision-making in high-stakes settings, but also underscore our framework’s effectiveness at producing efficient advisors with the necessary properties to catalyze the widespread adoption of AI-assisted advising in organizations. I will conclude with a proposed AI research agenda in business for advancing impactful human-AI collaboration.
Maytal Saar-Tsechansky is the Mary John and Ralph Spence Centennial Professor at the McCombs School of Business at the University of Texas at Austin, and a co-founder of Sweetch, an AI-based health company. Her research focuses on advancing AI to improve decision-making and to benefit people, organizations, and society. Her recent work focuses on human-AI collaboration and trustworthy AI with the overarching goal of bringing to bear human, organizational, and societal goals and constraints to catalyze AI systems’ positive impact in the world. Beyond AI, Maytal’s research aspires to make a positive impact in the world and includes challenges such as mitigation of partisan animosity and promoting democratic attitudes. Her work has been published in leading venues, including Science, Journal of Machine Learning Research, Journal of Finance, and Management Science, and has been supported by government and industry.
Maytal has led the University of Texas at Austin’s Translational AI initiative and is an academic board member of the university’s Machine Learning Lab.
Michael Barrett
Cambridge Judge Business School (CJBS)
Title: Trust and Agency in the Age of AI: A Relational Perspective on Emerging Technologies for Future Transformation
报告摘要: How are emerging technologies, such as AI and other digital innovations, reshaping the boundaries of organizations and transforming the way we work and live? Smart cities are envisioning ambitious opportunities, including concepts like a “City in the Sky,” flying taxis, driverless cars, and innovative business models centered around a Low Altitude Economy. Similarly, the Smart Hospital of the Future aims to redefine the boundaries of care across communities, homes, and hospitals, leveraging a suite of digital technologies—AI, digital twins, and remote care tools—to reorganize how care (prevention, diagnosis, and prediction) is delivered and by whom. While the realization of these and other contemporary visions remains uncertain, a critical factor will be our understanding of trust in AI. Our research highlights the importance of expanding the concept of trust beyond individual interactions to encompass trust at the ecosystem level. It also underscores the need to better understand the interplay between trust and distrust dynamics. In this talk, we adopt a relational perspective on emerging technologies to examine the evolving nature of trust and its implications for agency in the Age of AI, with important consequences for practice and policy.
Michael Barrett is a Vice Dean and Professor of Information Systems & Innovation Studies at Cambridge Judge Business School (CJBS). He is also Distinguished Visiting Professor of Innovation at the House of Innovation, Stockholm School of Economics. Michael is Academic Director of Cambridge Digital Innovation and conducts research focus on digital innovation and transformation. Focal areas of research include: trajectories of emerging digital technologies, digital health and new models of healthcare, and how digital innovation is enabling financial and social inclusion in developing countries. Professor Barrett is Editor-in-Chief of Information and Organization and has held senior editorial roles at MIS Quarterly, Information Systems Research, Information and Organization, and the Journal of the Association of Information Systems. Michael has served as Vice Dean of Research, Vice Dean of Programmes at CJBS, and was the founding Head of the Organization Theory and Information Systems group.