Olawade, David B., Bolarinwa, Obasanjo ORCID: https://orcid.org/0000-0002-9208-6408, Adebisi, Yusuff Adebayo and Shongwe, Sinegugu (2024) The Role of Artificial Intelligence in Enhancing Healthcare for People with Disabilities. Social Science & Medicine, 364 (117560).

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Abstract

The integration of artificial intelligence (AI) in healthcare delivery represents a transformative opportunity to enhance the lives of people living with disabilities. AI-driven technologies, such as assistive devices, conversational agents, and rehabilitation tools, can mitigate health disparities, improve diagnostic accuracy, and facilitate effective communication with healthcare providers, fostering more equitable healthcare environments. This commentary explores these applications while addressing the ethical challenges and limitations associated with AI deployment. Specific challenges, such as algorithmic bias, privacy risks with patient data, and the complexity of designing inclusive technologies, are discussed to provide a balanced perspective. For example, biased diagnostic tools may lead to inequitable care, and privacy breaches can compromise sensitive data. Key areas of focus include personalised care through AI-powered systems, the design of inclusive AI technologies incorporating continuous feedback loops and partnerships with advocacy groups, and the development of AI-enabled robotics for physical assistance. This commentary paper emphasises the importance of addressing these limitations alongside advancing ethical AI practices and ensuring continuous user involvement to meet the diverse needs of people living with disabilities, ultimately promoting greater independence and participation in society. Ultimately, while AI holds transformative potential in advancing equitable and inclusive healthcare for people with disabilities, addressing ethical challenges, overcoming limitations, and fostering user-centred design are essential to fully realise its benefits and ensure these innovations promote autonomy, accessibility, and well-being.

Item Type:	Article
Status:	Published
DOI:	10.1016/j.socscimed.2024.117560
School/Department:	London Campus
URI:	https://ray.yorksj.ac.uk/id/eprint/11123

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