no code implementations • 27 Apr 2022 • Marissa Radensky, Dustin Burson, Rajya Bhaiya, Daniel S. Weld
An important goal in the field of human-AI interaction is to help users more appropriately trust AI systems' decisions.
no code implementations • 27 Sep 2021 • Marissa Radensky, Doug Downey, Kyle Lo, Zoran Popović, Daniel S. Weld
However, we note that the two explanation approaches may be better compared in the context of a higher-stakes or more opaque domain.
no code implementations • NeurIPS Workshop AI4Scien 2021 • Jason Portenoy, Marissa Radensky, Jevin West, Eric Horvitz, Daniel Weld, Tom Hope
We also demonstrate an approach for displaying information about authors, boosting the ability to understand the work of new, unfamiliar scholars.
no code implementations • 30 Aug 2019 • Toby Jia-Jun Li, Marissa Radensky, Justin Jia, Kirielle Singarajah, Tom M. Mitchell, Brad A. Myers
In this paper, we describe a new multi-modal domain-independent approach that combines natural language programming and programming-by-demonstration to allow users to first naturally describe tasks and associated conditions at a high level, and then collaborate with the agent to recursively resolve any ambiguities or vagueness through conversations and demonstrations.
Human-Computer Interaction