Teachable AI (TAI) systems can significantly reduce the burden to create AI systems that empower non-programmers to author AI models. Our goal is the build teachable AI agents that can be taught rather than programmed, however, using natural human interactions. The Natural Training Interaction (NTI) testbed is a system that lets us observe teaching and learning interactions between multiple participants; including humans and AI agents. Studying these interactions will enable us to understand the patterns and modalities that are deemed effective when transferring knowledge between participants. We aim to eventually build TAI systems that utilize these natural interaction patterns - to build human-centered AI technologies.

Relevant Publications

Gupta, A., MacLellan, C.J. (2021). Designing Teachable Systems for Intelligent Tutor Authoring. AAAI2021 Spring Symposium on Artificial Intelligence for K-12 Education.

MacLellan, C.J., Harpstead, E., Marinier III, R. P., Koedinger, K.R. (2018). A Framework for Natural Cognitive System Training Interactions. Advances in Cognitive Systems, 6, 177-192.

Sheline, R. & MacLellan., C.J. (2018). Investigating Machine-Learning Interaction with Wizard-of-Oz Experiments. In Proceedings of the NeurIPS 2018 Workshop on Learning by Instruction.