AI algorithms have the potential to improve health monitoring for older adults, but data gaps risk widening health inequities. Healthcare algorithms are largely built from data that exclude older adults, women, people of color, and those from rural and low-income communities. Innovators, entrepreneurs, and investors can help bridge this gap by prioritizing solutions that address data acquisition for underrepresented populations, navigating the democratization of AI in healthcare, and prioritizing equity as a competitive lever. Equitable AI is a necessity for the millions of older Americans who remain unseen within current frameworks. There is an opportunity to fund robust data foundations to ensure the needs of older and marginalized adults are no longer overlooked and underserved.
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Quiet Neglect: Algorithmic Bias in Healthcare Is Hurting Older Adults
