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Optimizing for What? Algorithmic Amplification and Society

GETTING-Plurality Workstream Lead Aviv Ovadya recently discussed his work on bridging systems as part of “Optimizing for What? Algorithmic Amplification and Society.” This two-day symposium at Columbia University’s Knight First Amendment Institute explored algorithmic amplification and distortion as well as potential interventions.

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Work in the Age of AI: Reflections from After Neoliberalism

Commentary

Work in the Age of AI: Reflections from After Neoliberalism

Allen Lab member Charlie Covit reflects on the After Neoliberalism conference and examines the intersection of artificial intelligence and the future of work, arguing that AI forces a democratic reckoning with the meaning of labor itself and that an economy which generates abundance while stripping citizens of purpose and dignity undermines the very foundation of democratic life.

AI models appear to recognize moral complexity — then ignore it, new study by researchers affiliated with Harvard Kennedy School’s Allen Lab finds
Outstretched hands holding a graphic of a scale and the outlines of two heads.

Media Release

AI models appear to recognize moral complexity — then ignore it, new study by researchers affiliated with Harvard Kennedy School’s Allen Lab finds

New study published in AI and Ethics introduces a new ethical-moral intelligence framework for AI and finds that leading AI models mimic human moral concern while making decisions that reveal a hidden value hierarchy.