Conference & Journal Paper
Why and How People Check Generative AI Output for Mistakes
Patrick Gage Kelley, Derrick Feldmann, Reena Jana, Colleen Thompson-Kuhn, Allison Woodruff
Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES '26), 2026
October 2026
Abstract
Generative AI output can contain errors, such as hallucinations, non-responsive results, or otherwise inaccurate or potentially harmful content. To explore the public's emerging understanding, attitudes, and behavior regarding such mistakes, we ran an online survey in the United States with 1,503 respondents, with a representative sample of the population. We report high public awareness of generative AI mistakes. Further, many respondents report checking generative AI output, for example, by comparing results with other online resources. We conclude with guidance for explanations and in-product disclosures about generative AI mistakes.
- ai
- generative ai
- mistakes
- warnings
- digital literacy
- ai literacy
Cite this paper
@inproceedings{kelley2026why,
title = {Why and How People Check Generative AI Output for Mistakes},
author = {Kelley, Patrick Gage and Feldmann, Derrick and Jana, Reena and Thompson-Kuhn, Colleen and Woodruff, Allison},
year = {2026},
booktitle = {Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES '26), 2026},
url = {https://pgk.io/papers/2026-why-and-how-people-check-generative-ai-output-for-mistakes/},
}