Algorithmic Fairness and Base Rate Tracking
Bibliographic Data
| ID | 6325500 |
|---|---|
| Authors | Benjamin Eva (0000-0002-3764-3398, corresponding author) |
| Year | 2022 |
| Volume | 50 |
| Issue | 2 |
| Pages | 239-266 |
| Publication date | 2022-03-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Philosophy & Public Affairs (JOURNAL) |
| Journal identifiers | ISSN: 0048-3915 • E-ISSN: 1088-4963 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/papa.12211 |
| OpenAlex | W4220951533 |
| Language | EN |
| Citations received | 16 |
Base (topology · Sociology · Tracking (education · Computer Science · Ethics and Social Impacts of AI · Mathematics
Perpetuating Advantage
Algorithmic Fairness Criteria as Evidence
Dirty data labeled dirt cheap
On the site of predictive justice
Is explainable AI responsible AI
The ideals program in algorithmic fairness
Opening up new possibilities for algorithmic fairness
Spanning and Spacing
Comparative Base Rate Tracking
New Possibilities for Fair Algorithms
Spanning in and Spacing out? A Reply to Eva
Statistical evidence and algorithmic decision-making
Fairness and randomness in decision-making
Equalized odds is a requirement of algorithmic fairness
Does calibration mean what they say it means; or, the reference class problem rises again
Broomean(ish) Algorithmic Fairness
| Unique citing works | 16 |
|---|---|
| Citations per year | 5,33 |
| Citation span | 2023 - 2026 (4) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 16 |