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Simon J. Blanchard, Aaron M. Garvey, Laura O'Laughlin
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2024
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The persuasion knowledge model: how people cope with persuasion attempts
10.1086/209380 · doi-reference
Lower artificial intelligence literacy predicts greater AI receptivity
10.1177/00222429251314491 · doi-reference
AI–human hybrids for marketing research: leveraging large language models (LLMs) as collaborators
10.1177/00222429241276529 · doi-reference
New tools, new rules: a practical guide to effective and responsible generative AI use for surveys and experiments in research
10.1177/00222429251349882 · doi-reference
What large language models know and what people think they know
10.1038/s42256-024-00976-7 · doi-reference
Knowledge does not protect against illusory truth
10.1037/xge0000098 · doi-reference
Effects of perceptual fluency on judgments of truth
10.1006/ccog.1999.0386 · doi-reference
Polite AI mitigates user susceptibility to AI hallucinations
10.1080/00140139.2024.2434604 · doi-reference
Navigating the jagged technological frontier: field experimental evidence of the effects of artificial intelligence on knowledge worker productivity and quality
10.1287/orsc.2025.21838 · doi-reference
Reliability of LLMs as medical assistants for the general public: a randomized preregistered study
10.1038/s41591-025-04074-y · doi-reference
Explanations can reduce overreliance on AI systems during decision-making
10.1145/3579605 · doi-reference
On the conversational persuasiveness of GPT-4
10.1038/s41562-025-02194-6 · doi-reference
Countering AI-generated misinformation with pre-emptive source discreditation and debunking
10.1098/rsos.242148 · doi-reference
“ChatGPT can make mistakes” warnings fail: a randomized controlled trial
10.1111/medu.70056 · doi-reference
To trust or to think: cognitive forcing functions can reduce overreliance on AI in AI-assisted decision-making
10.1145/3449287 · doi-reference
From algorithm aversion to AI dependence: deskilling, upskilling, and emerging addictions in the GenAI age
10.1002/arcp.70008 · doi-reference
Documenting the truth-default: the low frequency of spontaneous unprompted veracity assessments in deception detection
10.1093/hcr/hqz001 · doi-reference
Detecting hallucinations in large language models using semantic entropy
10.1038/s41586-024-07421-0 · doi-reference
Three challenges for AI-assisted decision-making
10.1177/17456916231181102 · doi-reference
Improving human-AI collaboration with descriptions of AI behavior
10.1145/3579612 · doi-reference
Trust in automation: designing for appropriate reliance
10.1518/hfes.46.1.50.30392 · doi-reference
Survey of hallucination in natural language generation
10.1145/3571730 · doi-reference