Fairness perceptions of algorithmic decision-making: A systematic review of the empirical literature
University of Amsterdam · Heinrich Heine University Düsseldorf
Abstract
Algorithmic decision-making increasingly shapes people's daily lives. Given that such autonomous systems can cause severe harm to individuals and social groups, fairness concerns have arisen. A human-centric approach demanded by scholars and policymakers requires considering people's fairness perceptions when designing and implementing algorithmic decision-making. We provide a comprehensive, systematic literature review synthesizing the existing empirical insights on perceptions of algorithmic fairness from 58 empirical studies spanning multiple domains and scientific disciplines. Through thorough coding, we systemize the current empirical literature along four dimensions: (1) algorithmic predictors, (2) human…
Citation impact
- FWCI
- 45.02
- Percentile
- 100%
- References
- 97
Authors
4Topics & keywords
- Empirical research
- Computer science
- Harm
- Perception
- Management science
- Data science
- Coding (social sciences)
- Group decision-making
- Peace, Justice and strong institutions