Mitigating Bias in Algorithmic Systems - A Fish-Eye View
Creators
- 1. Open University of Cyprus
- 2. Open University of Cyprus & CYENS
- 3. National University of Mongolia
- 4. University of Trento
- 5. University of Haifa
Description
Mitigating bias in algorithmic systems is a critical issue drawing attention across communities within the information and computer sciences. Given the complexity of the problem and the involvement of multiple stakeholders – including developers, end users and third-parties – there is a need to understand the landscape of the sources of bias, and the solutions being proposed to address them, from a broad, cross-domain perspective. This survey provides a “fish-eye view,” examining approaches across four areas of research. The literature describes three steps toward a comprehensive treatment – bias detection, fairness management and explainability management – and underscores the need to work from within the system as well as from the perspective of stakeholders in the broader context.
Files
CSUR-2022.pdf
Files
(742.4 kB)
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