Recommendation Algorithms, a Neglected Opportunity for Public Health

Abstract

The public discussion on artificial intelligence for public health often revolves around future applications like drug discovery or personalized medicine. But already deployed artificial intelligence for content recommendation, especially on social networks, arguably plays a far greater role. After all, such algorithms are used on a daily basis by billions of users worldwide. In this paper, we argue that, left unchecked, this enormous influence of recommendation algorithms poses serious risks for public health, e.g., in terms of misinformation and mental health. But more importantly, we argue that this enormous influence also yields a fabulous opportunity to provide quality information and to encourage healthier habits at scale. We also discuss the philosophical, technical and socio-economical challenges to seize this immense opportunity, and sketch the outlines of potential solutions. In particular, we argue that it would be extremely helpful if public and private institutions could publicly take a stand, as this may then generate the necessary social, economical and political pressure to massively invest in the research, development and deployment of the potential solutions

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