Standardization on Bias in Artificial Intelligence as Industry Support

Abstract

Industry strives for trustworthy Artificial Intelligence (AI) systems through recognizing and implementing Responsible AI principles. Solutions supporting that goal are of the utmost interest in that context. Standardization is an essential element here, as it provides a platform for industry to discuss and facilitate not only the development of practical rules and requirements but also ways to implement AI based systems. One of Responsible AI principles is fairness, and bias is a serious obstacle against it. First, we explain the concept of Responsible AI and highlight results of our analysis on bias and fairness in ongoing international standardization works and AI Act (AIA). We identified a gap between the principles defined by high-level studies, including the AIA, and their practical implementations, and differences within standardization and research works. Second, we draw a standardization map for AI works. Finally, we state how international standardization bodies may fill this gap?

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