A design perspective on how to tackle gender biases when developing AI-driven systems

Abstract

A growing awareness of bias in artificial intelligence (AI) systems has recently emerged, leading to an increased number of publications discussing ethics in AI. Nevertheless, the specific issue of gender bias remains under-discussed. How can design contribute to preventing the emergence of gender bias in AI-driven systems? To answer this question, we investigated the current state of AI ethical guidelines within the European Union. The results revealed that most guidelines do not acknowledge gender bias but address discrimination. This raised our concerns, as addressing multiple biases simultaneously might not effectively mitigate any of them due to their often-unconscious nature. Furthermore, our results revealed a lack of quantitative evidence supporting the effectiveness of bias prevention implementation methods and solutions. In conclusion, based on our analysis, we propose four recommendations for designing effective guidelines to tackle gender biases in AI. Moreover, we stress the central role of diversity in embedding the gender perspective from the beginning in any design activity.