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Evidence record 2143 · automatically gathered

Fact-checking at a crossroads: Fact checkers’ perspectives on Community Notes, AI integration, and design recommendations

Social media platforms are increasingly using community-based verification systems, such as Community Notes, and AI systems to flag and contextualize potentially misleading content at scale. While these approaches promise speed and broad coverage, concerns about accuracy, bias, and transparency persist. Drawing on interviews with 29 fact checkers, we find that practitioners see community-based verification and AI Note Writers as complementary tools that can support, but not replace, professional

Record details

Published: 7 July 2026
Source: HKS Misinformation Review
Category: Research
Topics: Bias & fairness · Transparency
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Same publisher byline · Shared topic: Transparency

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Trustworthy Machine Learning through the Lens of Combinatorial Optimization: Survey and Research Perspectives

arXiv fairness query · 8 July 2026

Shared topic: Bias & fairness · Shared topic: Transparency

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arXiv · 8 July 2026

Shared topic: Bias & fairness · Shared topic: Transparency

Who Gets Missed in the Tail? Thresholded Subgroup Underdiagnosis in Long-Tailed Chest X-ray Classification

arXiv fairness query · 4 July 2026

How to cite this record

ethics.ai (7 July 2026), “Fact-checking at a crossroads: Fact checkers’ perspectives on Community Notes, AI integration, and design recommendations,” evidence record 2143, https://ethics.ai/record/2143 (originally published by HKS Misinformation Review).

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