Ethical implications of fairness interventions
What might be hidden behind engineering choices
Bibliographic Data
| ID | 21703507 |
|---|---|
| Authors | Andrea Aler Tubella (0000-0002-8423-8029, Umeå University, corresponding author), Flavia Barsotti (0000-0002-7567-2640, ING Bank), Rüya Gökhan Koçer (0000-0001-8058-1113, ING Bank), Julian Alfredo Mendez (0000-0002-7383-0529, Umeå University) |
| Year | 2022 |
| Volume | 24 |
| Issue | 1 |
| Publication date | 2022-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Ethics and Information Technology (JOURNAL) |
| Journal identifiers | ISSN: 1388-1957 • E-ISSN: 1572-8439 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s10676-022-09636-z |
| OpenAlex | W4221036405 |
| Language | EN |
| Citations received | 3 |
| References cited | 9 |
The importance of fairness in machine learning models is widely acknowledged, and ongoing academic debate revolves around how to determine the appropriate fairness definition, and how to tackle the trade-off between fairness and model performance. In this paper we argue that besides these concerns, there can be ethical implications behind seemingly purely technical choices in fairness interventions in a typical model development pipeline. As an example we show that the technical choice between in-processing and post-processing is not necessarily value-free and may have serious implications in terms of who will be affected by the specific fairness intervention. The paper reveals how assessing the technical choices in terms of their ethical consequences can contribute to the design of fair models and to the related societal discussions
Economics · Management science · Positive economics · Psychological intervention · Adversarial Robustness in Machine Learning · Computer Science · Ethics and Social Impacts of AI · Explainable Artificial Intelligence (XAI · Psychology
| Unique citing works | 3 |
|---|---|
| Citations per year | 1 |
| Citation span | 2023 - 2025 (3) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 3 |