From Bias to Balance: Navigating Gender Inclusion in AI

Abstract

This chapter explores the intersection of Artificial Intelligence (AI) and gender, highlighting the potential of AI to revolutionize various sectors while also risking the perpetuation of existing gender biases. The focus is on the challenges and strategies for achieving gender inclusivity within AI systems. By examining the progress made by organizations in addressing gender bias, the chapter identifies key technical, ethical, legal, and social barriers and outlines approaches for integrating gender inclusivity throughout the AI lifecycle. Utilizing a narrative literature review supplemented by industry case studies, the chapter critically analyzes selected literature to address these issues. The findings underscore persistent challenges in identifying and mitigating gender bias in AI systems alongside complex ethical and legal implications. Nevertheless, notable advancements in gender-specific algorithm design and inclusive data practices are highlighted. The chapter concludes that achieving gender inclusivity in AI requires a coordinated effort across developers, researchers, and policymakers, offering actionable recommendations to ensure AI systems are fair, transparent, and equitable, thus contributing to a more just and inclusive society.