Jose M. Such
With the widespread and pervasive use of AI for automated decision-making systems, AI bias is becoming more apparent and problematic. One of its negative consequences is discrimination: the unfair, unequal, or simply different treatment of individuals based on certain characteristics. However, the relationship between bias and discrimination is still unclear. In this talk, I will discuss current research we are conducting under the frame of an EPSRC-funded project about bias and discrimination in AI from an interdisciplinary perspective that embeds technical, legal, social and ethical dimensions. I will show that finding solutions to bias and discrimination in AI requires robust cross-disciplinary collaborations that will advance on the task of making AI more transparent and explainable to help assess whether AI systems discriminate against users and how to mitigate that.