Experiments on 250 participants show LLM-assisted survey responses range from under 10% on Prolific to over 80% on Mechanical Turk, with identifiable characteristics and partial mitigation effects.
Delving into LLM-assisted writ- ing in biomedical publications through excess vocab- ulary.Science Advances, 11(27):eadt3813, July 2025
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Authors propose a four-stage framework to analyze opportunities and risks of generative AI across the health information journey from public sources to clinical care.
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A Penny for Your Prompts: Experiments Detecting and Mitigating LLM Usage by Survey Respondents
Experiments on 250 participants show LLM-assisted survey responses range from under 10% on Prolific to over 80% on Mechanical Turk, with identifiable characteristics and partial mitigation effects.
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Opportunities and Risks of Generative AI through the Health Information Journey
Authors propose a four-stage framework to analyze opportunities and risks of generative AI across the health information journey from public sources to clinical care.