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)

Paper ID: 11916
Venue: VLDB
Year: 2018
Pagerank: 5.5957178e-05
Overall Rank: 7,566 | 48.10%
DOI: 10.14778/3229863.3240494

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
3,905	Automated Feature Engineering for Algorithmic Fairness	2021	VLDB	7.029145e-05

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
6,577	A Nutritional Label for Rankings	2018	SIGMOD	5.8364579e-05

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