Counterfactual Explanation Analytics: Empowering Lay Users to Take Action Against Consequential Automated Decisions
Summary: FACET introduces interactive, robust counterfactual region explanations rather than static points, modeling realistic recourse options. Its visual analytics let nontechnical users compare alternatives and construct personalized, actionable plans for favorable automated decisions. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Peter M. VanNostrand (Worcester Polytechnic Institute)
- 2. Dennis M. Hofmann (Worcester Polytechnic Institute)
- 3. Lei Ma (Worcester Polytechnic Institute)
- 4. Belisha Genin (Worcester Polytechnic Institute)
- 5. Randy Huang (Worcester Polytechnic Institute)
- 6. Elke A. Rundensteiner (Worcester Polytechnic Institute)
BibTeX Citation
@article{vannostrand_vldb24,
title = {{Counterfactual Explanation Analytics: Empowering Lay Users to Take Action Against Consequential Automated Decisions}},
author = {VanNostrand, Peter M. and Hofmann, Dennis M. and Ma, Lei and Genin, Belisha and Huang, Randy and Rundensteiner, Elke A.},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {12},
pages = {4349--4352},
doi = {10.14778/3685800.3685872},
url = {https://doi.org/10.14778/3685800.3685872},
year = {2024}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 85 | The X-tree: An Index Structure for High-Dimensional Data | 1996 | VLDB | 0.00035405879 |
| 6,079 | FACET: Robust Counterfactual Explanation Analytics | 2023 | SIGMOD | 5.9850223e-05 |
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