πŸ”¬

Designing Recommender Systems to Depolarize.

πŸ“… 2021
technical research breakthrough
πŸ”΅ Rare

πŸ“– 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 address redacted] 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...

πŸ“Š Game Impacts

Not verified in game

Which variables this event was proposed to move, and in which direction. The magnitudes are held in the corpus but are not shown here, because they have not been verified against the shipped game. They come from pdoom-data. They describe what an event was proposed to do, not what the shipped game does with it. Most events in the corpus are flavour: they are shown for colour and do not move any game variable. Only a small minority reach the systems below, and several of the variables listed here are not read by the game at all yet. Treat this table as a design proposal under review, not as a measurement of play. Corrections and arguments are welcome — the suggestion links at the foot of this page go straight to the data repo.

Variable Direction Condition
Research proposed: up Always
Papers proposed: up Always
Vibey Doom proposed: up Always

πŸ’­ Reactions

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πŸ”— Sources

🏷️ Event Metadata

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