Addressing Data Inequalities for Artificial Intelligence Technologies in Healthcare: Ways Forward for Policymaking

Gross, Nicole (2024) Addressing Data Inequalities for Artificial Intelligence Technologies in Healthcare: Ways Forward for Policymaking. Project Report. Dublin City Community Coop.

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Abstract

This policy paper was written based on a multi-method data collection [1], gathering information from academic journals, archival materials/grey literature and policy documents; participative insights (including 9 events); and 18 in-depth interviews with stakeholders working in civic society organizations, policy experts and Artificial Intelligence (AI) experts. The T&C and Privacy Policies of five popular AI engines were also reviewed.

The paper provides an overview of the promises and perils of generative AI technologies in healthcare. AI promises to change healthcare in previously unimaginable ways. Ireland advocates for the implementation and utilization of AI-based technologies to enhance public health and ensure that healthcare is more inclusive and accessible. However, previous research and experience clearly show that big tech companies dominate this space and their surveillance capitalist business models prioritize profit over social justice. This collaborative research, conducted in partnership with the Dublin Inner City Community Co-operative Society [2], delves into the power dynamics, political implications, and justice concerns surrounding data generation, utilization, and ownership in healthcare.

The paper gathers key recommendations for both the EU and its Member States, with a special focus on Ireland, given its significant role as the home to numerous big tech companies and a major controller of European users' data. The paper explores the tensions between the potential of generative AI and the dynamics of digital capitalism in Europe, and also looks at what impacts AI controversies are making in fostering data justice in healthcare. The recommendations explore what can be done to build moral (healthcare) data markets. The full list of recommendations is available in Section 6.

Item Type:	Monograph (Project Report)
Additional Information:	[1] Gross, N and Geiger, S (2023). A Multimethod Qualitative Approach to Exploring Multisided Platform Business Models in Health Care. In Sage Research Methods: Business. New York: SAGE Publications Ltd. [2] Dublin City Community Co-op, About us, Available at https://dublincitycommunitycoop.ie/
Subjects:	Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence B Philosophy. Psychology. Religion > BJ Ethics > Conduct of life > Reliability > Information integrity > Data integrity R Medicine > Healthcare Industry H Social Sciences > HD Industries. Land use. Labor > Specific Industries > I.T. Industry
Divisions:	School of Business > Staff Research and Publications
Depositing User:	Tamara Malone
Date Deposited:	27 Nov 2024 13:42
Last Modified:	27 Nov 2024 13:42
URI:	https://norma.ncirl.ie/id/eprint/7204

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