Aarti Singh

Summary

From expert based AI systems in 1970s to deep self-supervised systems in 2020s, the development of AI has swung from complete to no reliance on human input. While self-supervised learning has enabled fast and scalable evaluation, and led to significant advances in AI capabilities, the resulting systems are increasingly disconnected from human values and expectations. Achieving alignment between AI and human goals is thus a central challenge that is rapidly gaining renewed interest and importance as AI technologies are proliferating with a direct impact on individuals and society. The adoption success or failure of these technologies critically hinges on their ability to complement humans at either the individual, organizational and/or societal level. This course will provide an overview of the challenges in achieving human-centered AI, recent attempts at achieving human-AI alignment and the opportunities that lie ahead. Key focus will be on highlighting the role of concepts in social & decision science that AI researchers should pay attention to as they work to develop human-centered AI.

Syllabus

Part II: Opportunities: Cognitive AI, Human-AI Complementarity, Testbeds

References

Pre-requisites

Basic introduction to machine learning.

Short bio

Aarti Singh is the FORE Systems Professor in the Machine Learning Department at Carnegie Mellon University and Director of the NSF AI Institute for Societal Decision Making. Her research focuses on designing principled interactive algorithms for learning and decision making with application to scientific and societal domains. Her work is recognized by an NSF Career Award, a United States Air Force Young Investigator Award, A. Nico Habermann Faculty Chair Award, Harold A. Peterson Best Dissertation Award, and multiple paper awards. She has served on the National Academy of Sciences (NAS) Board on Mathematical Sciences and Analytics, NAS Committee on Applied and Theoretical Statistics, World Economic Forum expert network, lead expert on multiple NSF, NAS and ONR/NIST study committees, General Chair and Program Chair for ICML & AISTATS, Associate Editor for IEEE Transactions on Information Theory, and Action Editor for Journal of Machine Learning Research.