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Cited by 196Topic ModelingNatural Language Processing TechniquesEthics and Social Impacts of AI

AI Hallucinations: A Misnomer Worth Clarifying

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Maleki, Negar, Padmanabhan, Balaji, Dutta, Kaushik·2024·2024 IEEE Conference on Artificial Intelligence (CAI)
DOI 10.1109/cai59869.2024.00033
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Abstract

As large language models continue to advance in Artificial Intelligence (AI), text generation systems have been shown to suffer from a problematic phenomenon often termed as "hallucination." However, with AI’s increasing presence across various domains, including medicine, concerns have arisen regarding the use of the term itself. In this study, we conducted a systematic review to identify papers defining "AI hallucination" across fourteen databases. We present and analyze definitions obtained from all databases, categorize them based on their applications, and extract key points within each category. Our results highlight a lack of consistency in how the term is used, but also help identify several alternative terms in the literature. We discuss the implications of these findings and call for a more unified effort to bring consistency to this important contemporary AI issue, which can significantly affect multiple domains.

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  • LLMs hallucinate, i.e., produce plausible-sounding but false or fallacious statements.

    “First, they hallucinate, i.e., produce plausiblesounding but false or fallacious statements (Kalai and Vempala, 2024;Maleki et al., 2024).”

    From There is no such thing as conscious artificial intelligence (2025) · cites this paper as Maleki et al., 2024

  • Generative AI can produce incorrect or hallucinated content.

    “the reality is that generative AI can produce incorrect [Longwell et al., 2024] or hallucinated content [Maleki et al., 2024].”

    From How AI Impacts Skill Formation (2026) · cites this paper as Maleki et al., 2024

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Authors
Maleki, N., Padmanabhan, B., & Dutta, K.
Affiliations
  • University of South Florida (US)
  • University of Maryland, College Park (US)
ORCID
Venue
2024 IEEE Conference on Artificial Intelligence (CAI)
Publisher
IEEE
Published
2024-06-25
Pages
133-138
DOI
10.1109/cai59869.2024.00033
OpenAlex
W4401110692
Cited by
194
References
31
Citations by year
2026: 78 · 2025: 92 · 2024: 23 · 2020: 1
FWCI
56.96
Type
conference paper
Language
en
Open access
Licence
Locations
  • IEEE Conference on Artificial Intelligence (CAI) (publishedVersion)
  • arXiv (Cornell University) (submittedVersion, other-oa)
  • arXiv (Cornell University)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
  • Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
AI hallucination, terminology, large language models, text generation, artificial intelligence in healthcare, terminology standardization

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