Hariharan Subramonyam
ABSTRACT
The focus of intelligent systems is on "making things easy'' through automation. However, for many cognitive tasks---such as learning, creativity, or sensemaking---there is such a thing as too easy or too automated. Current human-AI design principles, as well as general usability guidelines, prioritize automation, and efficient task execution over human effort. However, this type of advice may not be suitable for designing systems that need to balance automation with other cognitive goals. In these cases, designers lack the necessary tools that will allow them to consider the trade-offs between automation, AI assistance, and human-effort. My dissertation looks at using models from cognitive psychology to inform the design of intelligent systems. The first system, Florum, looks at automation after human-effort as a strategy to facilitate learning from science text. The second system, TakeToons, explores automation as a complementary strategy to human-effort to support creative animation tasks. A third set, SmartCues and Affinity Lens use AI as a last-mile optimization strategy for human sensemaking tasks. Based on these systems, I am looking to develop a design framework that (1) classifies threats across different levels of design including automation, user interface, expectations from AI, and cognition and (2) offers ways to validate design decisions.
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- Hariharan Subramonyam, Steven M Drucker, and Eytan Adar. 2019. Affinity Lens: Data-Assisted Affinity Diagramming with Augmented Reality. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. ACM, 398.Google ScholarDigital Library
- Hariharan Subramonyam, Wilmot Li, Eytan Adar, and Mira Dontcheva. 2018. TakeToons: Script-driven Performance Animation. In The 31st Annual ACM Symposium on User Interface Software and Technology. ACM, 663--674.Google ScholarDigital Library
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Index Terms
- Designing Interactive Intelligent Systems for Human Learning, Creativity, and Sensemaking
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