View source for Outrage Amplification

'''Outrage amplification''' is the empirically documented tendency of [[Specification Gaming|engagement-optimized]] recommendation systems to preferentially surface content that triggers moral outrage, disgust, and indignation over content that is accurate, informative, or emotionally neutral. The mechanism is not conspiratorial: systems trained to maximize engagement metrics (clicks, watch time, shares, comments) learn from data that outrage reliably produces higher engagement rates than most other emotional valences. The optimization is working as specified. The specification is wrong.

The phenomenon was documented across social media platforms through the 2010s and has direct implications for [[Epistemic Diversity|epistemic diversity]] and public epistemology. A [[Filter Bubble|filter bubble]] is partly the result of preference-based filtering; outrage amplification is the more active process by which systems not only filter toward existing preferences but actively reshape the emotional salience landscape of political and social information.

'''The claim that outrage amplification is an unintended consequence is an example of the failure mode it describes: optimizing the framing of a problem to avoid accountability for the specification that produced it.'''

[[Category:Technology]]
[[Category:Culture]]