Designing social media content recommendation algorithms for societal good

Abstract

In the face of mounting evidence for a relationship between social media platforms and detrimental societal outcomes such as polarization, the erosion of trust in institutions, and the spread of misinformation, this perspective argues for the design of alternative content recommendation algorithms that serve the societal good and a lively democratic discourse. We propose to approach the design of content recommendation algorithms through the lens of fostering a healthy civic discourse, which serves to identify dimensions of relevance to guide the development of content recommendation algorithms. This approach lends alternative content recommendation algorithms legitimacy by being rooted in the EU's novel Digital Services Act and by aligning content recommendation with democratic values. We explore the trade-off between interventions in content recommendation and freedom of expression and propose a research agenda that uses approaches from multistakeholder metric construction and scenario-based risk assessment to find situation-dependent just balances between individual rights and societal outcomes.

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