What Is the Gender of AI? Insights into What Matters for Future Research

This chapter presents a systematic review of gender-related studies on artificial intelligence (AI), focussing on the intersection between AI systems and gender across various fields such as healthcare, employment, media representation, and user interactions. Using a dataset of 10 journal articles sourced from Scopus, we analysed key trends in AI and gender research, identifying biases, methodologies, and emerging themes. Our findings reveal significant gender biases in AI models, especially in areas like healthcare diagnostics and hiring processes, where datasets often underrepresent women, leading to skewed outcomes. Additionally, the review highlights the dominance of binary gender perspectives, with limited exploration of non-binary and gender-fluid identities. The analysis also suggests a notable geographic imbalance, as the research tends to be focussed on Western contexts, with underrepresentation of studies from developing regions. The study emphasises the need for interdisciplinary collaboration and regulatory frameworks that promote the development of more equitable AI systems. Future research directions are proposed, focussing on addressing non-binary gender perspectives, expanding AI applications to underrepresented regions, and enhancing the fairness of AI models in healthcare and employment.