Fairness, explainability and in-between
Understanding the impact of different explanation methods on non-expert users’ perceptions of fairness toward an algorithmic system
Bibliographic Data
| ID | 21703416 |
|---|---|
| Authors | Avital Shulner-Tal (0000-0003-2091-2966, University of Haifa, corresponding author), Tsvi Kuflik (0000-0003-0096-4240, University of Haifa), Doron Kliger (0000-0001-7649-8464, University of Haifa) |
| Year | 2022 |
| Volume | 24 |
| Issue | 1 |
| Publication date | 2022-03-01 |
| 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/s10676-022-09623-4 |
| OpenAlex | W4210377637 |
| Language | EN |
| Citations received | 8 |
| References cited | 27 |
Audit · Business · Certification · Computer security · Perception · System Justification · Artificial Intelligence in Healthcare and Education · Computer Science · Ethics and Social Impacts of AI · Explainable Artificial Intelligence (XAI · Psychology · Social Psychology
User‐Centered Evaluation of Explainable Artificial Intelligence (XAI)
Understanding the dilemma of explainable artificial intelligence
Policy advice and best practices on bias and fairness in AI
Personalizing explanations in AI-based decisions
Explainable AI and trust
Human Centricity in the Relationship Between Explainability and Trust in AI
Fairness perceptions of algorithmic decision-making
The effect of algorithmic management and workers’ coping behavior
Peeking Inside the Black-Box
European Union Regulations on Algorithmic Decision Making and a “Right to Explanation”
Explainable AI
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
Explainable Artificial Intelligence (XAI)
A Survey of Methods for Explaining Black Box Models
| Citations per year | 2 |
|---|---|
| Citation span | 2022 - 2026 (5) |
| Highly cited | No |