Data Feminism in AI-Enabled Healthcare: A Pathway to Equitable Health Outcomes

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Data Feminism in AI-Enabled Healthcare: A Pathway to Equitable Health Outcomes

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    By Ubaida Abdulai

    Data Scientist / Programs Manager at Because She Can LBG.

    Abstract:

    Artificial Intelligence(AI) continues to improve patient care, treatment planning and disease diagnosis using existing data collected over the years. However, there are several valid concerns regarding bias, equality, equity and the ethical use of data that are frequently brought up by the increased dependence on AI. In this presentation, I will discuss how data feminism, an approach that integrates feminist principles with data science, can be leveraged to ensure that, rather than perpetuating current disparities, AI-enabled healthcare improves social justice and equity.

    This talk will start with an overview of data feminism, focusing mainly on its core principles: challenging power dynamics, amplifying the voices of marginalised groups and challenging the myth of objectivity. The underrepresentation of marginalised groups in health data, biased algorithms and unequal access to technology are some problems I will discuss concerning AI-enabled healthcare.

    A case study will be used to demonstrate how data feminism can be applied in AI-enabled healthcare to identify and reduce bias. The case study focuses on how AI algorithms used for detecting breast cancer through mammograms have shown varying levels of accuracy across different demographic groups, usually underperforming for women of colour who are commonly underrepresented in training data. I will also discuss the ethical implications of AI in healthcare, advocating for data practices that prioritise patient autonomy, consent, and trust.

    The goal of this talk is to demonstrate how data feminism can be adapted to create AI-enabled healthcare technologies that are more inclusive, equitable, and accurate than existing ones. By the end of the session, participants will have a deeper understanding of how to incorporate feminist principles into their work and gain the tools needed to develop AI solutions that enhance equitable access to healthcare for everyone

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