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AI Gender Biases in Women’s Healthcare: Perspectives from the United Kingdom and the European Legal Space

  • Pin Lean Lau

摘要

This paper engages with a key debate surrounding artificial intelligence in health and medicine, with an emphasis on women’s healthcare. In particular, the paper seeks to capture the lack of gender parity where women’s health is concerned, a consequence of systemic biases and discrimination in both historical and contemporary medical and health data. The existing literature review demonstrates that there is not only a gender data gap in AI technologies and data science fields—but there is also a gender data gap in women’s healthcare that results in algorithmic gender bias, impacting negatively on women’s healthcare experiences, treatment protocols, and finally, rights in health. On this basis, the article seeks to offer a concise exploration of the gender-related aspects of medicine and healthcare, shedding light on the biases encountered by women in the context of AI-driven healthcare. Subsequently, it conducts a doctrinal comparative law examination of the existing legislative landscape to scrutinise whether current supranational AI regulations or legal frameworks explicitly encompass the protection of fundamental rights for female patients in the realm of health AI. The scope of this analysis encompasses the legal framework governing AI-driven technologies within the European Union (EU), the Council of Europe (CoE), and, to a limited extent, the United Kingdom (UK). Lastly, this paper explores the potential utility of data feminism (that draws on intersectionality theory) as an additional tool for advancing gender equity in healthcare.