The Gender Code: Global AI Governance Frameworks Show Growing, yet Inconsistent, Gender Integration

The increasing influence of artificial intelligence demands careful consideration of its societal impacts, and a critical area of concern is gender equity, as AI systems can perpetuate and amplify existing inequalities. Jelena Cupac undertakes a comprehensive analysis of international efforts to address these issues within the emerging landscape of AI governance, examining binding regulations like the EU AI Act, ethical guidelines from UNESCO, and global initiatives such as the Global Partnership on AI. This research demonstrates a growing, though uneven, integration of gender concerns into these frameworks, revealing a shift towards inclusivity and diversity, but also highlighting persistent gaps in consistent treatment and enforcement. By advocating for intersectional, enforceable, and inclusive governance, this work contributes significantly to the ethical AI debate, and argues for a future where AI promotes genuine equity rather than reinforcing existing societal biases.

AI Governance, Gender, and Inclusivity Trends

This study investigates how international AI governance frameworks address gender issues and potential harms, employing a detailed analysis of binding regulations, soft law instruments, and global initiatives. The work reveals a growing emphasis on inclusivity and diversity, alongside a shift toward explicit gender-related provisions within these governance documents. The study conceptualizes AI by referencing advancements initiated in 2012, when deep neural networks began delivering significantly improved results across various classification tasks, relying on vast datasets to identify complex patterns and make autonomous decisions.

Researchers highlight that despite its transformative potential, AI is fundamentally conservative, relying on historical data and often reproducing existing societal structures and biases. Several cases demonstrate this, including research with Word2Vec in 2016, which revealed how AI systems can encode and amplify gender stereotypes. The study also details Amazon’s abandoned AI hiring tool from 2018, which penalized resumes referencing women’s organizations, and builds upon the 2018 work of Buolamwini and Gebru, exposing racial and gender disparities in facial recognition software. This analysis emphasizes the importance of intersectionality, acknowledging how overlapping forms of discrimination create unique experiences of marginalization. AI gender harm stems not solely from biased datasets, but also from the decisions of human creators, dominant cultural values, and structural inequalities embedded within the development process, contributing to ethical AI debates and highlighting the importance of gender-sensitive governance.

AI Ethics, Equity and Societal Impact

This analysis outlines the core arguments and themes concerning ethical and equitable AI governance. It emphasizes that the development and deployment of artificial intelligence require robust frameworks not only for technical safety, but also to ensure systems are just and do not exacerbate existing societal inequalities, particularly those based on gender. AI systems are created by humans and therefore reflect human biases, and ignoring these biases leads to harmful outcomes. Bias in AI systems is a recurring theme, stemming from biased data, a lack of diversity within the AI development field, and the opacity of some algorithms.

The study highlights the risk of AI perpetuating gender inequality, citing examples such as AI-powered recruiting tools discriminating against women and systems reinforcing harmful gender stereotypes. A fragmented landscape of AI governance requires international cooperation, a multi-stakeholder approach involving governments, industry, civil society, and academia, and a focus on broader societal harm rather than solely individual privacy or safety. The rise of anti-gender movements and illiberal politics poses a threat to the development of ethical AI. Solutions include promoting diversity and inclusion in AI, creating inclusive work environments, developing ethical guidelines and standards, enhancing algorithmic transparency and accountability, focusing on data quality and bias mitigation, strengthening international cooperation, adopting a holistic approach to governance, and addressing the political context.

The study emphasizes the need to move beyond individual harm and focus on systemic and societal harms caused by AI, recognizing that data is not neutral and its collection, processing, and use have real-world consequences. Key actors and initiatives include UNESCO, the European Union, the G7 and G20, the OECD, the Alan Turing Institute, and the United Nations. The text presents a compelling case for the urgent need for ethical and equitable AI governance, highlighting the risks of bias and inequality and proposing a range of solutions requiring concerted action from governments, industry, and civil society.

AI Governance, Gender Equality, and Emerging Gaps

This study offers a comprehensive analysis of international efforts to govern artificial intelligence with attention to gender equality and the prevention of gender-based harms. The analysis demonstrates a growing integration of gender considerations into broader human rights frameworks and a discernible shift toward explicitly including gender-related provisions within AI governance. However, the research also reveals critical gaps in current approaches, including inconsistencies in how gender is treated and limited engagement with intersectionality.

The study emphasizes the need for enforceable mechanisms to ensure that stated commitments to gender equality translate into meaningful outcomes, moving beyond symbolic gestures. While progress has been made in recognizing the importance of gender-sensitive AI governance, further development is needed to strengthen inclusivity and prevent the reinforcement of existing inequalities. Future work should prioritize addressing these gaps and developing more robust, intersectional, and enforceable frameworks to ensure a just and equitable future with artificial intelligence.