Substantive LLM reframing boosts cross-partisan receptivity to news headlines without backfire, but models overestimate effect sizes and lack fidelity in modeling human psychological responses.
URL https://www.science.org/ doi/10.1126/science.aea3884
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Attitude-congruent AI dialogues reduce immediate affective and opinion polarization more than incongruent ones, while incongruent dialogues increase cognitive trait empathy over two weeks.
citing papers explorer
-
Can AI Debias the News? LLM Interventions Improve Cross-Partisan Receptivity but LLMs Overestimate Their Own Effectiveness
Substantive LLM reframing boosts cross-partisan receptivity to news headlines without backfire, but models overestimate effect sizes and lack fidelity in modeling human psychological responses.
-
Divergent Paths to Depolarization: Dialogue Design Determines the Prosocial Benefits of AI-Assisted Political Argumentation
Attitude-congruent AI dialogues reduce immediate affective and opinion polarization more than incongruent ones, while incongruent dialogues increase cognitive trait empathy over two weeks.