This chapter offers a critical assessment of the under-represented gendered dimensions of techno-science, specifically focusing on technologies driven by artificial intelligence (AI) within the context of women’s healthcare in the European legal space. Firstly, it enquires into the gendered dimensions of medicine and healthcare, and demonstrates the centrality of androcentrism and the existence of biases in women’s healthcare and medical data. Secondly, it highlights the FemTech revolution and the harmful implications of AI algorithmic biases against women, and investigates whether existing supranational AI legislation or legal frameworks adequately protect the fundamental rights of patients in health or medical FemTech and AI. This assessment looks to the European Union Artificial Intelligence Act and the Council of Europe Zero Draft Framework Convention on Artificial Intelligence, Human Rights, Democracy, and the Rule of Law for this purpose. Thirdly, it seeks to recommend the co-creation of effective stewardship as one of the solutions to health equality for women. Viewed through the lens of data feminism, effectiveness means acknowledging privilege versus oppression in the access to and quality of women’s healthcare, and identifying approaches that look towards dismantling inequitable power structures that influence the dynamics of bias and under-representation in women’s healthcare.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

The FemTech Jacquerie: Situating Co-creation for Efficient Stewardship in Women’s Health Vis-À-Vis the European Union Artificial Intelligence Act

  • Pin Lean Lau

摘要

This chapter offers a critical assessment of the under-represented gendered dimensions of techno-science, specifically focusing on technologies driven by artificial intelligence (AI) within the context of women’s healthcare in the European legal space. Firstly, it enquires into the gendered dimensions of medicine and healthcare, and demonstrates the centrality of androcentrism and the existence of biases in women’s healthcare and medical data. Secondly, it highlights the FemTech revolution and the harmful implications of AI algorithmic biases against women, and investigates whether existing supranational AI legislation or legal frameworks adequately protect the fundamental rights of patients in health or medical FemTech and AI. This assessment looks to the European Union Artificial Intelligence Act and the Council of Europe Zero Draft Framework Convention on Artificial Intelligence, Human Rights, Democracy, and the Rule of Law for this purpose. Thirdly, it seeks to recommend the co-creation of effective stewardship as one of the solutions to health equality for women. Viewed through the lens of data feminism, effectiveness means acknowledging privilege versus oppression in the access to and quality of women’s healthcare, and identifying approaches that look towards dismantling inequitable power structures that influence the dynamics of bias and under-representation in women’s healthcare.