AI-powered healthcare promises to solve current problems, offering more efficient, unbiased and accurate care to its users. This chapter seeks to ground the promises of AI discourses within concerns of epistemic injustice in healthcare and unpack the roles of knowledge creation, control and use within the medical AI app context. We begin by underscoring the impact of inequality on knowledge production, particularly in relation to the female body, and the epistemic injustice it gives rise to. We then spotlight the current narrative that AI can serve as a remedy for epistemic injustice by providing insights into patient data, which is collected and input by the patient. This data is positioned as objective, opening up avenues for AI to delve into medical conditions and, at an individual level, empower people by tracking their medical journeys. However, we argue that such applications may inadvertently shift the burden of proof from the practitioner to the user, potentially creating additional barriers to healthcare and exacerbating existing inequality and injustice. This chapter not only delves into these potential pitfalls but also emphasises the crucial role of ethical frameworks in fostering justice in the emerging knowledge systems within and about AI in the healthcare context.

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

Critical Epistemologies of AI Healthcare Apps

  • Milena Ivanova,
  • Aisha Sobey

摘要

AI-powered healthcare promises to solve current problems, offering more efficient, unbiased and accurate care to its users. This chapter seeks to ground the promises of AI discourses within concerns of epistemic injustice in healthcare and unpack the roles of knowledge creation, control and use within the medical AI app context. We begin by underscoring the impact of inequality on knowledge production, particularly in relation to the female body, and the epistemic injustice it gives rise to. We then spotlight the current narrative that AI can serve as a remedy for epistemic injustice by providing insights into patient data, which is collected and input by the patient. This data is positioned as objective, opening up avenues for AI to delve into medical conditions and, at an individual level, empower people by tracking their medical journeys. However, we argue that such applications may inadvertently shift the burden of proof from the practitioner to the user, potentially creating additional barriers to healthcare and exacerbating existing inequality and injustice. This chapter not only delves into these potential pitfalls but also emphasises the crucial role of ethical frameworks in fostering justice in the emerging knowledge systems within and about AI in the healthcare context.