YouTube’s recommendation algorithm may exacerbate health disparities, expert suggests

YouTube’s recommendation algorithm, which privileges popular and engaging videos, may contribute to health disparities, according to information systems professor Anjana Susarla, PhD.

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A recent study evaluating the most popular online videos about COVID-19 discovered that 25 percent of videos contained misinformation. YouTube’s algorithm makes recommendations based on users’ health literacy, which refers to their ability to acquire and understand basic health information, but it usually does not take into account the validity of the information within the videos. 

The most popular videos feature easy-to-understand information that is often not medically valid, so the algorithm can lead users with lower health literacy toward questionable content. Users with higher health literacy are more likely to be led to videos from reputable sources, such as hospitals and federal health agencies.

The algorithm’s bias could be especially problematic for people of color in the U.S., as studies have shown that limited health literacy disproportionately affects their communities. 

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The predictive analytics tools hospitals are using to forecast COVID-19 case surges
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