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Investigating Explainability of Generative AI for Code through Scenario-based Design


Feb 10, 2022
Jiao Sun, Q. Vera Liao, Michael Muller, Mayank Agarwal, Stephanie Houde, Kartik Talamadupula, Justin D. Weisz


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Using Document Similarity Methods to create Parallel Datasets for Code Translation


Oct 11, 2021
Mayank Agarwal, Kartik Talamadupula, Fernando Martinez, Stephanie Houde, Michael Muller, John Richards, Steven I Ross, Justin D. Weisz


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Expanding Explainability: Towards Social Transparency in AI systems


Jan 12, 2021
Upol Ehsan, Q. Vera Liao, Michael Muller, Mark O. Riedl, Justin D. Weisz

* Accepted to CHI2021 

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Do's and Don'ts for Human and Digital Worker Integration


Oct 15, 2020
Vinod Muthusamy, Merve Unuvar, Hagen Völzer, Justin D. Weisz


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AutoAIViz: Opening the Blackbox of Automated Artificial Intelligence with Conditional Parallel Coordinates


Jan 17, 2020
Daniel Karl I. Weidele, Justin D. Weisz, Eno Oduor, Michael Muller, Josh Andres, Alexander Gray, Dakuo Wang

* 5 pages, 1 figure, IUI2020 

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Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI


Sep 05, 2019
Dakuo Wang, Justin D. Weisz, Michael Muller, Parikshit Ram, Werner Geyer, Casey Dugan, Yla Tausczik, Horst Samulowitz, Alexander Gray


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