Bidding Strategies with Gender Nondiscrimination: Constraints for Online Ad Auctions
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Abstract (arXiv)
Interactions between bids to show ads online can lead to an advertiser's ad being shown to more men than women even when the advertiser does not target towards men. We design bidding strategies that advertisers can use to avoid such emergent discrimination without having to modify the auction mechanism. We mathematically analyze the strategies to determine the additional cost to the advertiser for avoiding discrimination, proving our strategies to be optimal in some settings. We use simulations to understand other settings.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Sep 2019.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 2.
4 papers.
- 2021A Sociotechnical View of Algorithmic Fairnesscited by 24
- 2023Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Toolscited by 7
- 2022Towards Trustworthy AI-Empowered Real-Time Bidding for Online Advertisement Auctioningcited by 4
- 2023Trading-off price for data quality to achieve fair online allocationcited by 2
- 2023Toward Operationalizing Pipeline-aware ML Fairness: A Research Agenda for Developing Practical Guidelines and Tools29 Sep 2023
- 2023Trading-off price for data quality to achieve fair online allocation23 Jun 2023
- 2022Towards Trustworthy AI-Empowered Real-Time Bidding for Online Advertisement Auctioning21 Sep 2022
- 2021A Sociotechnical View of Algorithmic Fairness27 Sep 2021