The DOI matches its Crossref record.
Correction: Generative AI can effectively manipulate data
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LLMs can generate highly credible misinformation, particularly when personalized or tailored to user identities.
“First, LLMs can generate highly credible misinformation, particularly when personalized or tailored to user identities (Gabriel et al. 2024; Kim et al. 2024; Menz et al. 2024).”
From Generative AI and misinformation: a scoping review of the role of generative AI in the generation, detection, mitigation, and impact of misinformation (2026) · cites this paper as Kim et al. 2024
The corrected Table 1 caption (p. 1) says GPT-4 fabricated recovery-time data and manipulated it to achieve statistical and clinical significance, supporting the claim that an LLM can produce misleading material. The correction does not address whether such material is highly credible or whether it is personalized or tailored to user identities. (LLM, conf=0.83)
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Park, S., & Nan, X. (2026) · AI & SOCIETY · doi:10.1007/s00146-025-02620-3 · Cited by 58
Alipour, P., & Gallegos, E. E. (2025) · Artificial Intelligence Review · doi:10.1007/s10462-025-11137-6 · Cited by 11
Metadata
- Authors
- Kim, J. J. H., Srivatsa, A. V., Nahass, G. R., Rusanov, T., Hwang, S., Kim, S., Solomon, I., Lee, T. H., Kadkol, S., Ajilore, O., & Dai, Y.
- Affiliations
- University of Illinois Chicago (US)
- Icahn School of Medicine at Mount Sinai (US)
- Columbia University (US)
- Johns Hopkins University (US)
- Corresponding author
- Kim, Jeff J. H.
- ORCID
- Venue
- AI and Ethics
- Published
- 2024-12-06
- Volume
- 5
- Issue
- 5
- Pages
- 4533-4533
- ISSN
- 2730-5953 (ISSN-L)
- 2730-5961
- OpenAlex
- W4405119378
- Cited by
- 1
- References
- 0
- Citations by year
- 2025: 1
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- AI and Ethics (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Adversarial Robustness in Machine Learning
- Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
- Keywords
- generative AI, data manipulation, data integrity
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