Generating Interpretable Data-Based Explanations for Fairness Debugging using Gopher

Summary: Gopher generates compact, interpretable, causal explanations for ML fairness by identifying the top-k coherent training-data subsets that are root causes. It quantifies removal/updating effects on bias, outlines an end-to-end architecture, and provides open-source code and a demo. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h02005ebf0d803d20
Venue: SIGMOD
Year: 2022
Pagerank: 5.5498988e-05
Overall Rank: 7,334 | 50.70%
DOI: 10.1145/3514221.3520170

Incoming Non-self Citations Over Time

Authors

1. Jiongli Zhu (University of California San Diego)
2. Romila Pradhan (Purdue University)
3. Boris Glavic (Illinois Institute of Technology)
4. Babak Salimi (University of California San Diego)

BibTeX Citation

@inproceedings{zhu_sigmod22,
        title = {{Generating Interpretable Data-Based Explanations for Fairness Debugging using Gopher}},
        author = {Zhu, Jiongli and Pradhan, Romila and Glavic, Boris and Salimi, Babak},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3520170},
        url = {https://dl.acm.org/doi/10.1145/3514221.3520170},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
11,142	CausalExplain: Causal Explanations of Black-box Models with Training Data Subsets	2025	SIGMOD	4.9793485e-05
11,211	Understanding the Black Box: A Deep Empirical Dive into Shapley Value Approximations for Tabular Data	2025	SIGMOD	4.9793485e-05

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
1,941	Interpretable Data-Based Explanations for Fairness Debugging	2022	SIGMOD	9.3297671e-05
2,326	SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging	2021	SIGMOD	8.6309237e-05
3,063	Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals	2021	SIGMOD	7.6912904e-05

Semantically Similar Papers

#	Overall Rank	Paper	Year	Venue
1	6,845	Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification	2022	SIGMOD
2	13,772	DENOUNCER: Detection of Unfairness in Classifiers	2021	VLDB
3	11,142	CausalExplain: Causal Explanations of Black-box Models with Training Data Subsets	2025	SIGMOD
4	13,628	Interactive Fairness Auditing: Leveraging AVOIR for Dynamic Evaluation and Mitigation	2025	SIGMOD
5	4,719	OmniFair: A Declarative System for Model-Agnostic Group Fairness in Machine Learning	2021	SIGMOD
6	6,771	Causal Feature Selection for Algorithmic Fairness	2022	SIGMOD
7	803	Interventional Fairness : Causal Database Repair for Algorithmic Fairness	2019	SIGMOD
8	3,745	Automated Feature Engineering for Algorithmic Fairness	2021	VLDB
9	11,671	Reconstructing and Querying ML Pipeline Intermediates	2023	CIDR
10	1,941	Interpretable Data-Based Explanations for Fairness Debugging	2022	SIGMOD