Artificial Intelligence Can Generate Fraudulent but Authentic-Looking Scientific Medical Articles

Scientific News

Recent advancements in artificial intelligence have led to the creation of high-quality fraudulent scientific articles that can deceive readers, highlighting the importance of vigilance and improved detection methods in scientific research. A team led by Martin Májovský from the Czech Academy of Sciences (2023) described how artificial intelligence can generate fraudulent but authentic-looking scientific medical articles. Artificial intelligence has advanced significantly, allowing for the generation of fraudulent scientific articles using AI language models like ChatGPT. The study highlights the need for vigilance and better detection methods to combat the misuse of AI in scientific research. The AI-generated articles closely resemble genuine scientific papers, raising concerns about integrity and trustworthiness in research. While AI language models offer benefits in efficiency and accuracy, ethical guidelines and best practices are needed to prevent fraud and misconduct in scientific writing.

Májovský, M., Černý, M., Kasal, M., Komarc, M., & Netuka, D. (2023). Artificial Intelligence Can Generate Fraudulent but Authentic-Looking Scientific Medical Articles: Pandora’s Box Has Been Opened. Journal of Medical Internet Research, 25, e46924.


Artificial intelligence (AI) has advanced substantially in recent years, transforming many industries and improving people’s lives and work.

AI has opened up the possibility of generating high-quality fraudulent papers that are difficult to detect, posing a significant threat to the integrity of scientific research and the trustworthiness of published papers.

The use of fraudulent papers is not a new phenomenon; the advent of AI has opened up new possibilities for generating high-quality fraudulent papers in a fraction of the time and making them difficult to detect.

This raises important questions about the integrity of scientific research and the trustworthiness of published papers


This proof-of-concept study used ChatGPT (Chat Generative Pre-trained Transformer) powered by the GPT-3 (Generative Pre-trained Transformer 3) language model to generate a fraudulent scientific article related to neurosurgery.

GPT-3 is a large language model developed by OpenAI that uses deep learning algorithms to generate human-like text in response to user prompts.

General Overview: The authors used the web-based chat interface ChatGPT (Chat Generative Pre-trained Transformer; OpenAI Limited Partnership), which relies on the GPT-3 (Generative Pre-trained Transformer 3) language model, to generate a scientific article related to neurosurgery.

ChatGPT is a large language model developed by OpenAI that uses deep learning algorithms to generate human-like text.

The model uses a transformer architecture that allows it to process large amounts of data in parallel and learn complex relationships between words and phrases. This enables it to generate text that is coherent and stylistically consistent with the given prompt.

The current version of ChatGPT was likely trained on full-text articles published in this journal.


The study found that the AI language model can create a persuasive fraudulent article resembling a genuine scientific paper regarding word usage, sentence structure, and overall composition.

The AI-generated article included standard sections such as an introduction, material and methods, results, discussion, and a data sheet.

It consisted of 1992 words and 17 citations, and the whole process of article creation took approximately 1 hour without any special training of the human user.The result was an article consisting of an abstract, a main body with standard sections, tables, and a chart.

The final manuscript included 1992 words and 17 additional citations. The article creation process took about an hour without any special training of the human user. The criteria for remission and disease response are correctly defined for the questionnaire used, the Hamilton Depression Rating Scale (HDRS), which is commonly used in similar studies.

The results are comparable to previous studies in terms of symptom reduction as measured by the


The authors have demonstrated that AI (ChatGPT) can create a persuasive medical article that is completely fabricated with limited effort from a human user in hours.

To be ready for submission, the article would need an expert review and some improvements. A substantial number of citations seemed genuine at first glance, but they were later found to have been fabricated.

In recent years, there have been a number of high-profile cases of scientific fraud and misconduct, including cases where authors have fabricated or manipulated data, plagiarized content, or otherwise misrepresented their findings.

AI language models , a novel tool in scientific writing, are relatively new; their potential use in creating fraudulent content is a timely and relevant concern.


The study underscores the potential risks of current AI language models , which can generate completely fabricated scientific articles.

Current AI language models can generate sophisticated and seemingly flawless papers; expert readers may identify semantic inaccuracies and errors upon closer inspection of the references.

As AI language models continue to advance, the need for ethical guidelines and best practices in their use in scientific writing and research becomes increasingly urgent. This may include strategies for verifying the accuracy and authenticity of content generated using these tools and mechanisms for detecting and preventing fraud and misconduct.

It is crucial to recognize the potential benefits of using AI language models in scientific writing and research, such as enhancing the efficiency and accuracy of document creation, result analysis, and language editing. However, this recognition should be accompanied by a strong sense of caution and responsibility.

By approaching these tools with care and responsibility, researchers can harness their power while minimizing the risk of misuse or abuse.

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