As artificial intelligence systems become increasingly integrated into decision-making across industry, concerns about algorithmic bias and its societal impacts are growing. This paper presents research emerging from a Master of Education project focused on addressing gender disparities in computer science and reframes it within the context of ethical AI development. It argues that a key component of addressing bias in these algorithms must begin with inclusive, equity-driven computer science education at the K–12 level. By fostering equity in computer science classrooms, we can address a root cause of algorithmic and systemic biases that later surface in AI systems and computing more broadly. This project draws on critical feminist theory, social justice curriculum design and inclusive pedagogical practices to examine how gender exclusion and underrepresentation in computing equity-driven educational approaches can disrupt bias.
