Observing and Recommending from a Social Web with Biases

2016/04/25 by Steffen Staab, Staab, Steffen, Sophie Stalla-Bourdillon +3 · 1 citation
Computer Science · Social Sciences · #Imbalanced Data Classification Techniques #Ethics and Social Impacts of AI #Privacy-Preserving Technologies in Data

paper · pdf · doi:10.48550/arxiv.1604.07180

Abstract

The research question this report addresses is: how, and to what extent, those directly involved with the design, development and employment of a specific black box algorithm can be certain that it is not unlawfully discriminating (directly and/or indirectly) against particular persons with protected characteristics (e.g. gender, race and ethnicity)?

Cited by

• Ethical Considerations in Artificial Intelligence Courses

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• Discrimination in machine learning algorithms
• Fairness-aware machine learning: a perspective
• Oxford Handbook on AI Ethics Book Chapter on Race and Gender
• Protected Grounds and the System of Non-Discrimination Law in the Context of Algorithmic Decision-Making and Artificial Intelligence
• Strengthening legal protection against discrimination by algorithms and artificial intelligence