Published September 14, 2018
| Version Accepted pre-print
Conference paper
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Addressing Social Bias in Information Retrieval
Creators
- 1. Open University of Cyprus, Nicosia,Cyprus and Research Centre on Interactive Media Smart Systems and Emerging Technologies, Nicosia, Cyprus
Description
Journalists and researchers alike have claimed that IR systems are socially biased, returning results to users that perpetuate gender
and racial stereotypes. In this position paper, I argue that IR researchers and in particular, evaluation communities such as CLEF, can and should address such concerns. Using as a guide the Principles for Algorithmic Transparency and Accountability recently put forward by the Association for Computing Machinery, I provide examples of techniques for examining social biases in IR systems and in particular, search engines.
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References
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