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Explanatory Debugging: Supporting End-User Debugging of Machine-Learned Programs

TitleExplanatory Debugging: Supporting End-User Debugging of Machine-Learned Programs
Publication TypeConference Paper
Year of Publication2010
AuthorsKulesza, T., S. Stumpf, M. M. Burnett, W-K. Wong, Y. Riche, T. Moore, I. Oberst, A. Shinsel, and K. McIntosh
Conference Name2010 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)
Pagination41 - 48
Date Published09/2010
PublisherIEEE
Conference LocationLeganes, Madrid, Spain
ISBN Number978-1-4244-7621-3
Keywordsend-user debugging, HCI, machine learning
Abstract

Many machine-learning algorithms learn rules of behavior from individual end users, such as task-oriented desktop organizers and handwriting recognizers. These rules form a "program" that tells the computer what to do when future inputs arrive. Little research has explored how an end user can debug these programs when they make mistakes. We present our progress toward enabling end users to debug these learned programs via a Natural Programming methodology. We began with a formative study exploring how users reason about and correct a text-classification program. From the results, we derived and prototyped a concept based on "explanatory debugging," then empirically evaluated it. Our results contribute methods for exposing a learned program's logic to end users and for eliciting user corrections to improve the program's predictions.

DOI10.1109/VLHCC.2010.15