ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health
By L. De Angelis, Francesco Baglivo, Guglielmo Arzilli, G. Privitera, Paolo Ferragina, Alberto Eugenio Tozzi, Caterina Rizzo. Frontiers in Public Health, 2023
584 citations recorded by the source corpus.
Large Language Models (LLMs) have recently gathered attention with the release of ChatGPT, a user-centered chatbot released by OpenAI. In this perspective article, we retrace the evolution of LLMs to understand the revolution brought by ChatGPT in the artificial intelligence (AI) field. The opportunities offered by LLMs in supporting scientific research are multiple and various models have already been tested in Natural Language Processing (NLP) tasks in this domain. The impact of ChatGPT has been huge for the general public and the research community, with many authors using the chatbot to write part of their articles and some papers even listing ChatGPT as an author. Alarming ethical and practical challenges emerge from the use of LLMs, particularly in the medical field for the potential impact on public health. Infodemic is a trending topic in public health and the ability of LLMs to rapidly produce vast amounts of text could leverage misinformation spread at an unprecedented scale, this could create an “AI-driven infodemic,” a novel public health threat. Policies to contrast this phenomenon need to be rapidly elaborated, the inability to accurately detect artificial-intelligence-produced text is an unresolved issue.
Subfields: Health Informatics, Radiology, Nuclear Medicine and Imaging, Sociology and Political Science
View Paper: https://www.semanticscholar.org/paper/12594b6afe01461384d2856d2bf44f1cf8533e3e
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Citations in the corpus
- Cultural bias and cultural alignment of large language models (2023, background): “…Mistral, and LLaMA, which are trained on Internet-scale textual data to process text and produce human-sounding language, are increasingly used by people in all aspects of their life, including education [32], medicine and public health [13, 45], as well as creative and opinion writing [50, 29].”
- Investigating the Impact of User Trust on the Adoption and Use of ChatGPT: Survey Analysis (2023, unknown): “Among these concerns is the potential for its exploitation for malicious purposes, such as social engineering attacks or other forms of fraud [20].”
- The effects of over-reliance on AI dialogue systems on students' cognitive abilities: a systematic review (2024, background): “De Angelis et al. (2023) found that the rise of journals that neglect essential quality controls, like verifying for plagiarism or ensuring ethical standards, might result in a significant influx of AI-generated articles within the scientific realm.”
- Defending ChatGPT against jailbreak attack via self-reminders (2023, unknown): “They can also be used to generate and disseminate misinformation on social media platforms, leading to serious social and political consequences 21,22 .”
- The ethics of ChatGPT in medicine and healthcare: a systematic review on Large Language Models (LLMs) (2024, background): “21 Consequently, there is a noticeable demand for ethical guidelines, evidenced within the literature surrounding healthcare applications of LLMs. 49,63,67,73,74,77,78,81 While we concur with the need for such guidance, our analysis suggests that the real challenge lies not in the articulation of…”
- Mobile Game Evaluation Method Based on Data Mining of Affective Time Series (2025, unknown): “See Section 3.6.”