US EditionStudy: AI Tool Reduces Political Polarization on X
The AI browser extension lowered hostile political content on X feeds, improving users’ attitudes toward opposing parties by two points, equal to three years of U.S. affective polarization change.
- In a 10-day field experiment, the Stanford-led research team tested an AI-powered browser extension that reorders X feeds to downrank antidemocratic posts with over 1,200 participants during the 2024 U.S. presidential campaign, publishing results Thursday in Science.
- Faced with limited access to proprietary ranking systems, researchers developed a tool to study how social media algorithms steer exposure to antidemocratic attitudes and partisan animosity and to give researchers and end users more control over feed ranking without platform operators' cooperation.
- Survey responses showed participants warmed toward the opposing political party by two points on a 1–100 scale and reported less anger and sadness during use, though emotional effects faded after.
- Researchers argue that platforms could reduce polarization by downranking hostile content, and the team released the tool's code to enable user-controlled algorithms and policy interventions.
- The researchers note the study was limited to browser users and did not measure long-term impact, while authors warn results may not generalize to other platforms and countries.
37 Articles
37 Articles
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