Ask ChatGPT: caveats and mitigations for individual users of AI chatbots

As ChatGPT and other Large Language Model (LLM)-based AI chatbots become increasingly integrated into daily life, important safety and well-being concerns arise. What concerns and risks do these systems pose for individual users? What potential harms might they cause, and how can these be mitigated? In this work, we conduct a structured qualitative risk analysis of AI chatbot use at the individual level to address these questions. We begin by explaining how LLM-based AI chatbots work, providing foundational context to help readers understand the inherent limitations of these systems. We then identify a range of risks associated with individual use, including hallucinations, intrinsic biases, sycophantic behavior, cognitive offloading and potential decline, social isolation, and privacy leakage. Finally, we propose key mitigation strategies to address these concerns. Our goal is to raise awareness of the safety and societal implications of AI chatbot use, and to empower individuals to protect cognitive integrity, safeguard privacy, and promote more responsible and beneficial human–AI interaction.

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Publication Details

Journal
AI and Ethics
Published
2026-04-01
DOI
https://doi.org/10.1007/s43681-026-01089-0
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Ask ChatGPT: caveats and mitigations for individual users of AI chatbots

ChuanYu Wang, Murat Kantarcioglu
AI and Ethics
Artificial Intelligence in Healthcare and Education
article

Ask ChatGPT: caveats and mitigations for individual users of AI chatbots

ChuanYu Wang, Murat Kantarcioglu
article en

Abstract

As ChatGPT and other Large Language Model (LLM)-based AI chatbots become increasingly integrated into daily life, important safety and well-being concerns arise. What concerns and risks do these systems pose for individual users? What potential harms might they cause, and how can these be mitigated? In this work, we conduct a structured qualitative risk analysis of AI chatbot use at the individual level to address these questions. We begin by explaining how LLM-based AI chatbots work, providing foundational context to help readers understand the inherent limitations of these systems. We then identify a range of risks associated with individual use, including hallucinations, intrinsic biases, sycophantic behavior, cognitive offloading and potential decline, social isolation, and privacy leakage. Finally, we propose key mitigation strategies to address these concerns. Our goal is to raise awareness of the safety and societal implications of AI chatbot use, and to empower individuals to protect cognitive integrity, safeguard privacy, and promote more responsible and beneficial human–AI interaction.

AI and EthicsVol. 6(2)
The University of Texas at Dallas (US), Virginia Tech (US)
Reduced inequalities
Openalex Percentile: Top 7%
Artificial Intelligence in Healthcare and Education
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