Artificial intelligence (AI) is poised to transform healthcare, with potential applications ranging from managing supply chains to interpreting medical images. However, as this AI in healthcare revolution unfolds, researchers warn that unless AI development and deployment address fundamental structural issues, its impact may be limited. This blog explores the promises and pitfalls of AI in public health, and the need for a thoughtful, ethical governance framework to ensure these technologies serve the greater good.
The Allure and Risks of AI in Public Health
Proponents of AI in healthcare envision a future where the technology helps manage supply chains, monitor disease outbreaks, make diagnoses, and even reduce disparities in access to care. However, others warn of potential issues, such as privacy concerns, algorithmic biases, and a lack of transparency in AI decision-making.
Researchers Lucia Vitale and Leah Shipton argue that the hype around AI tools could distract from more fundamental structural problems in global public health. For example, they note that most AI development in healthcare focuses on treating disease, rather than addressing the underlying social and political determinants of health, such as access to healthy food and safe living environments.
Repeating Past Patterns: The Politics of Avoidance
Vitale and Shipton’s analysis suggests that AI is poised to become the latest in a long line of technological ‘silver bullets’ that fail to create lasting change in public health. They warn that AI could continue or exacerbate historical patterns of harm and exploitation, with ownership and profits concentrated in high-income countries while low- and middle-income nations may be targeted for data extraction or risky experimentation.
Additionally, they predict that lax regulation and a focus on intellectual property rights and corporate incentives could prioritize industry profits over equitable and affordable public access to new AI-powered treatments and tools. This could lead to a continued overlooking of the needs of the world’s poorest populations.
Harnessing AI to Improve Healthcare Systems
Despite these concerns, Vitale and Shipton do identify a potential bright spot for AI in healthcare: using the technology to improve the healthcare system itself. For example, AI could be used to allocate resources more efficiently across hospitals, provide triage support, or expand the capabilities of general practitioners in underserved areas.
However, the researchers caution that the impact of these applications is not guaranteed. Depending on how and where they are deployed, AI tools could either successfully fill gaps in care or lead to the displacement of existing healthcare workers. To maximize the benefits and minimize the harms, Vitale and Shipton argue that robust regulation and ethical governance frameworks must be put in place before AI expands further into the health sector.
