Designing Recommender Systems to Depolarize.

📖 Description

To appear in First Monday, September 2021 Designing Recommender Systems to Depolarize Jonathan Stray Center for Human-Compatible AI University of California at Berkeley [email removed] Abstract Polarization is implicated in the erosion of democracy and the progression to violence, which makes the polarization properties of large algorithmic content selection systems (recommender systems) a matter of concern for peace and security. While algorithm-driven social media does not seem to be a primary driver of polarization at the country level, it could be a useful intervention point in polarized societies. This paper examines algorithmic depolarization interventions with the goal of conflict transformation: not suppressing or eliminating conflict but moving towards more constructive conflict. Algorithmic intervention is considered at three stages: which content is available (moderation), how content is selected and personalized (ranking), and content presentation and contro...

📊 Game Impacts

💭 Reactions

🔗 Sources

• [1] https://arxiv.org/abs/2107.04953