4 papers
AI Fact-Checking in the Wild: A Field Evaluation of LLM-Written Community Notes on X
Haiwen Li, Michiel A. Bakker
Large language models (LLMs) show promising capabilities for fact-checking, yet prior work evaluates them only in controlled offline settings using benchmarks or crowdworker judgme…
The Rise of AI Search: Implications for Information Markets and Human Judgement at Scale
Sinan Aral, Haiwen Li, Rui Zuo
We executed 24,000 search queries in 243 countries, generating 2.8 million AI and traditional search results in 2024 and 2025. We found a rapid global expansion of AI search and ke…
Scaling Human Judgment in Community Notes with LLMs
Haiwen Li, Soham De, Manon Revel +6
This paper argues for a new paradigm for Community Notes in the LLM era: an open ecosystem where both humans and LLMs can write notes, and the decision of which notes are helpful e…
Human Trust in AI Search: A Large-Scale Experiment
Haiwen Li, Sinan Aral
Large Language Models (LLMs) increasingly power generative search engines which, in turn, drive human information seeking and decision making at scale. The extent to which humans t…