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AI Hallucinations and User Beliefs
paperAuthors
Richard Pak·Ericka Rovira·Anne Collins McLaughlin
Credibility Rating
3/5
Good(3)Good quality. Reputable source with community review or editorial standards, but less rigorous than peer-reviewed venues.
Rating inherited from publication venue: arXiv
This is an ArXiv search results page, not a specific paper; users should treat it as a starting point for literature review on hallucination and trust, and navigate to individual papers for substantive findings. Original tags suggesting manipulation and mental health may reflect niche papers in the result set.
Metadata
Importance: 35/100arxiv preprintreference
Summary
This ArXiv search query aggregates research papers examining AI hallucinations and their effects on user trust and beliefs. The collection likely spans empirical studies, theoretical frameworks, and mitigation strategies related to how false or fabricated AI outputs influence human decision-making and trust calibration.
Key Points
- •AI hallucinations refer to confident but factually incorrect or fabricated outputs from language models, posing significant reliability risks.
- •User trust in AI systems can be miscalibrated when hallucinations go undetected, leading to downstream harms in high-stakes domains.
- •Research in this area examines both the technical causes of hallucinations and their psychological/behavioral effects on users.
- •Mitigation strategies include improved model training, retrieval-augmented generation, uncertainty quantification, and user education.
- •The intersection of hallucination and trust is critical for AI deployment safety, especially in medical, legal, and financial contexts.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| AI-Induced Cyber Psychosis | Risk | 37.0 |
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0fa043c58eaf8c1f | Stable ID: ZjAyNmI3ZD