8 Ways to Prevent Ageism in Artificial Intelligence

That's according to a recent World Health Organization policy brief explaining that data used by A.I. in healthcare can be unrepresentative of older people. A.I. is a product of its algorithms, the brief explains, and can draw ageist conclusions if the data that feeds the algorithms is skewed toward younger individuals. This could affect, for example, telehealth tools used to predict illness or major health events in a patient. It could also provide inaccurate data for drug development. Ultimately, not including older adults in the development process for A.I. can make it harder to get them to adopt new A.I. applications in the future.