Bias and Discrimination in AI: a cross-disciplinary perspective

• URL: http://arxiv.org/abs/2008.07309v1
• Date: Tue, 11 Aug 2020 10:02:04 GMT
• Title: Bias and Discrimination in AI: a cross-disciplinary perspective
• Authors: Xavier Ferrer, Tom van Nuenen, Jose M. Such, Mark Cot\'e and Natalia Criado
• Abstract summary: We show that finding solutions to bias and discrimination in AI requires robust cross-disciplinary collaborations. We survey relevant literature about bias and discrimination in AI from an interdisciplinary perspective that embeds technical, legal, social and ethical dimensions.
• Score: 5.190307793476366
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: With the widespread and pervasive use of Artificial Intelligence (AI) for automated decision-making systems, AI bias is becoming more apparent and problematic. One of its negative consequences is discrimination: the unfair, or unequal treatment of individuals based on certain characteristics. However, the relationship between bias and discrimination is not always clear. In this paper, we survey relevant literature about bias and discrimination in AI from an interdisciplinary perspective that embeds technical, legal, social and ethical dimensions. We show that finding solutions to bias and discrimination in AI requires robust cross-disciplinary collaborations.

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