Michael Fortune
13 March 2026
As we wrap up our series on AI in healthcare, we’re diving into the ethically charged waters of integrating AI into medical practices. It’s not just about technology itself; it’s about how we ensure this technology promotes health equity and is used responsibly. So let’s unpack the complexities surrounding this vital issue. One glaring concern in the world of healthcare AI is algorithmic bias. A recent review looking at FDA-approved medical devices reveals a troubling trend. Out of nearly 700 devices, a mere 3.6% reported race and ethnicity data. Even more concerning, 99.1% didn’t provide socioeconomic information, and 81.6% failed to disclose the ages of individuals in studies. What does this mean for patients? Essentially, if AI systems are trained on non-representative data, they might not work effectively for everyone, particularly those from underserved communities. This lack of representation could exacerbate the very healthcare disparities we’re trying to reduce. Become a supporter of this podcast: https://www.spreaker.com/podcast/conspiracy-theories-exploring-the-unseen--5194379/support.
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