Panel: A Debate on Data and Algorithmic Ethics
Summary: Panel debating whether fairness, accountability, and transparency constitute core data-management research problems. Highlights databases’ responsibility for biased data/model pipelines and calls for systems research at the intersection of data infrastructure, algorithmic ethics, and policy. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Julia Stoyanovich (Drexel University)
- 2. Bill Howe (University of Washington)
- 3. HV Jagadish (University of Michigan)
- 4. Gerome Miklau (University of Massachusetts Amherst)
BibTeX Citation
@article{stoyanovich_vldb18,
title = {{Panel: A Debate on Data and Algorithmic Ethics}},
author = {Stoyanovich, Julia and Howe, Bill and Jagadish, HV and Miklau, Gerome},
journal = {PVLDB},
series = {{VLDB} '18},
volume = {11},
number = {12},
pages = {2165--2167},
doi = {10.14778/3229863.3240494},
url = {https://doi.org/10.14778/3229863.3240494},
year = {2018}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,745 | Automated Feature Engineering for Algorithmic Fairness | 2021 | VLDB | 7.055875e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 1 of 1 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,692 | A Nutritional Label for Rankings | 2018 | SIGMOD | 5.7070994e-05 |
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