16.07.2024
Title: Algorithmic Resignation
Speaker: Umang Bhatt, Assistant Professor & Faculty Fellow at the Center for Data Science at New York University and Research Associate in Safe and Ethical AI at the Alan Turing Institute
When: Friday, July 19, at 10:30am
Where: Physical room will be announced shortly or via Zoom (link here)
This talk will discuss algorithmic resignation, a strategic approach for managing the use of AI systems within organizations. Algorithmic resignation involves the deliberate and informed disengagement from AI assistance in certain scenarios, by embedding governance mechanisms directly into AI systems. Our proposal is not merely about disuse of AI but includes guiding when and how these systems should be used or avoided. We discuss the multifaceted benefits of algorithmic resignation, spanning economic efficiency, reputational gains, and legal compliance. Using techniques like barring access to AI outputs selectively or providing explicit disclaimers on system performance, algorithmic resignation not only mitigates risks associated with AI but also leverages its benefits, ensuring the responsible and effective use of AI systems. We close with a concrete setting wherein users, based on their expertise and organizational cost constraints, are barred from accessing large language models in Q&A settings. We find that personalizing the disengagement of algorithmic assistance can be learned online, using contextual bandits, and can improve performance in practice.
Umang Bhatt is an Assistant Professor & Faculty Fellow at the Center for Data Science at New York University and a Research Associate in Safe and Ethical AI at the Alan Turing Institute. He completed his PhD in the Machine Learning Group at the University of Cambridge. His research lies in human-AI collaboration, AI governance, and algorithmic transparency. Umang builds tools for routing decision-makers to appropriate forms of decision support and for capturing how AI systems are used in practical decision-making contexts. His work has been supported by a JP Morgan PhD Fellowship and a Mozilla Fellowship. Previously, he was a Research Fellow at the Partnership on AI, a Fellow at Harvard's Center for Research on Computation and Society, and an Advisor to the Responsible AI Institute. Umang received his MS and BS in Electrical and Computer Engineering from Carnegie Mellon University.