User Interaction Dataset for JAIR 2024 paper "Opening the Analogical Portal to Explainability: Can Analogies Help Laypeople in AI-assisted Decision Making?"

DOI:10.4121/19a75bf7-2825-4c22-96a2-e55eecac0fec.v1
The DOI displayed above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
DOI: 10.4121/19a75bf7-2825-4c22-96a2-e55eecac0fec

Datacite citation style

He, Gaole; Balayn, Agathe; Buijsman, Stefan; Jie Yang; Gadiraju, Ujwal (2025): User Interaction Dataset for JAIR 2024 paper "Opening the Analogical Portal to Explainability: Can Analogies Help Laypeople in AI-assisted Decision Making?". Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/19a75bf7-2825-4c22-96a2-e55eecac0fec.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

This repo contains all code and data for the paper "Opening the Analogical Portal to Explainability: Can Analogies Help Laypeople in AI-assisted Decision Making?" We collected user decision making with AI assistants in a skin cancer detection scenario. Specifically, we provide concept-level explanations generated with post-hoc XAI methods and analogy-based explanations to elucidate the importance of concepts. User interfaces built upon flask is also provided.

History

  • 2025-02-06 first online, published, posted

Publisher

4TU.ResearchData

Format

table/csv

Organizations

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science, Department of Software Technology, Web Information Systems Group

DATA

Files (5)