Generative AI can effectively manipulate data
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
ChatGPT-4.0 can alter the sentiment and content of interview transcripts while maintaining stylistic consistency.
“alter the sentiment and content of interview transcripts while maintaining stylistic consistency”
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
Methods for bypassing built-in safeguards through prompt engineering and iterative refinement were identified.
“The study also identified methods for bypassing built-in safeguards through prompt engineering and iterative refinement”
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
ChatGPT-4.0 can adjust interdependent economic indicators based on fabricated inputs.
“adjust interdependent economic indicators based on fabricated inputs”
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
Adobe Firefly can insert visual fabrications, such as inserting liquid water into a Mars rover image.
“Adobe Firefly, a visual generative model, successfully inserted visual fabrications, such as inserting liquid water into a Mars rover image.”
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
ChatGPT-4.0 can manipulate numerical datasets to achieve statistically or clinically significant outcomes.
“ChatGPT-4.0 was able to manipulate numerical datasets to achieve statistically or clinically significant outcomes”
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
Cites
Lund, B. D., Wang, T., Mannuru, N. R., Nie, B., Shimray, S., & Wang, Z. (2023) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24750 · Cited by 919 · see citing works
Fabrication and errors in the bibliographic citations generated by ChatGPT
Walters, W. H., & Wilder, E. I. (2023) · Scientific Reports · doi:10.1038/s41598-023-41032-5 · Cited by 499 · see citing works
Using AI to write scholarly publications
Hosseini, M., Rasmussen, L. M., & Resnik, D. B. (2024) · Accountability in Research · doi:10.1080/08989621.2023.2168535 · Cited by 286 · cited 1× · see citing works
“Previous stud - ies also have revealed that tools like ChatGPT possess the capability to create deceptive research manuscripts and citations [ 10–12 ].”
Flagged first, then by citations
Cited by
Sorted by citations
Park, S., & Nan, X. (2026) · AI & SOCIETY · doi:10.1007/s00146-025-02620-3 · Cited by 58 · see citing works
“Some studies examined multiple domains, including politics, health, economics, science, religion, ethical dilemmas, and pseudoscience (Kim et al. 2024; Kumar et al. 2024; Węcel et al. 2023).”
Influential
- 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
- 2024-09-02
- Volume
- 5
- Issue
- 5
- Pages
- 4515-4529
- ISSN
- 2730-5953 (ISSN-L)
- 2730-5961
- OpenAlex
- W4402135203
- Cited by
- 15
- References
- 3
- Citations by year
- 2026: 7 · 2025: 8
- FWCI
- 6.25
- Type
- journal article
- Language
- en
- Update notices
- Open access
- closed
- Licence
- Locations
- AI and Ethics (publishedVersion)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Keywords
- generative AI, data manipulation, GPT-4, Adobe Firefly, synthetic data, economic indicators, interview transcripts, image editing, AI ethics, responsible AI use, mitigation measures
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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