The integration of Generative AI in education presents both opportunities and challenges for advancing gender equity in STEM fields. To maximize these opportunities while addressing potential challenges, we've developed a comprehensive framework that emphasizes the crucial interconnection between teachers, school leadership, and parents. This tripartite collaboration is essential because students' success in STEM is shaped by the synergy of classroom experiences, institutional policies, and home environment. 

Our AI and Gender Framework provides structured guidance for these key stakeholders to create an ecosystem where girls can thrive in STEM education through AI-enabled learning. The framework addresses three critical dimensions:

For teachers, the framework emphasizes developing AI competency alongside inclusive classroom practices. This includes understanding how to identify and mitigate gender biases in AI systems, implementing engaging pedagogical approaches, and fostering an environment where girls see AI as an empowering tool rather than a barrier. Teachers are positioned to directly influence students' attitudes toward AI while ensuring equitable participation and recognition in STEM activities.

School leadership plays a pivotal role through policy development and institutional support. The framework guides leaders in establishing clear digital vision, creating dedicated AI leadership positions, and developing robust guidelines for ethical AI use. Their role in forming partnerships with industry experts and academics ensures that girls have access to real-world role models and opportunities in AI and STEM fields.

Parents contribute by fostering an AI-aware home environment that challenges gender stereotypes and provides active engagement with AI technologies. The framework helps parents recognize and address their own unconscious biases while serving as role models who encourage their daughters' interest in STEM and AI.

What sets this framework apart is its holistic approach to addressing unconscious gender biases at multiple levels. Rather than treating bias as a single-dimensional issue, it recognizes that gender disparities in STEM are perpetuated through subtle interactions across educational and social contexts. By explicitly mapping these interactions and providing targeted strategies for each stakeholder group, the framework creates multiple reinforcing pathways for change.

The ultimate goal is to transform AI education from a potential barrier into a catalyst for gender equity in STEM. When teachers, school leaders, and parents align their efforts through this framework, they create an environment where girls don't just participate in AI education – they see themselves as future leaders and innovators in the field. This shared vision, supported by concrete strategies and collaborative action, paves the way for a more inclusive and equitable STEM future.

The Gender Equity in AI Schools Framework was developed by T. Keane, T. Wang, M. Cerovac, C. Tipple (2025) arising from the research conducted as part of this project.

This Framework can be cited as: Keane, T., Wang, T., Cerovac, M., & Tipple. C. (2025). Gender Equity in AI Schools Framework. https://aigendertoolkit.com/GenderEquityFramework.html