Skip to main content

Artificial hallucination: GPT on LSD?

A Correspondence to this article was published on 10 May 2023

The Original Article was published on 25 February 2023

To the Editor,

In the following, we will comment on the publication of Salvagno et al. [1], as we not only share the enthusiasm but also the concerns about the potential risks of Generative Pre-trained Transformer (GPT) in scientific writing, automated draft generation and article summarisation. In fact, their paper sparked an immediate interest to try this disruptive technology ourselves, using the identical prompt (command or action sentence used to communicate with ChatGPT) as Salvagno et al., referring to the discussion of the paper by Suverein et al. "Early Extracorporeal Cardiopulmonary Resuscitation for Refractory Out-of-Hospital Cardiac Arrest" [2]. Unfortunately, the same prompt provided by Salvagno et al. [1] resulted in a completely different response from ChatGPT. Even after correcting the typo made by the authors—"Sovereign" instead of "Suverein"—we obtained the following result (Fig. 1).

Fig. 1
figure 1

ChatGPT's response to the prompt provided in the publication by Salvagno et al. [3]

Additionally, a prompt asking for a summary of each paper did not correspond to the original publications [2, 4, 5] and contained incorrect information about the study period and the participants. Even more disturbing, the command "regenerate response" leads to different results and conclusions [3]. So the question arises whether artificial intelligence could suffer from artificial hallucination, and if so, what is the pathogenesis of this hallucination?

In general, “hallucinations” of ChatGPT or similar large language models (LLMs) are characterized by generated content that is not representative or senseless to the provided source, e.g. due to errors in encoding and decoding between text and representations. However, it should be noted that artificial hallucination is not a new phenomenon as discussed in [6]. Although in a more visual note it first appeared in 1968 as a malfunction of the supercomputer HAL9000 in the movie “2001: A Space Odyssey” [7]. For those who do not recall: The American spaceship Discovery One is on a mission to Jupiter, with mission pilots and scientists. The supercomputer HAL9000 is controlling most of the operations. As the journey continues, a conflict arises between HAL9000 and the astronauts concerning a malfunction of an antenna. While mission control sides with the astronauts and confirms that the computer has made a mistake, HAL9000, however, continues to blame any problem on human errors.

But why does ChatGPT communicate the result of the prompt, like HAL9000, as a confident statement that is not true? What are the underlying reasons for ChatGPT to give different answers to the same prompt? Is it operating under the influence?

Let's take a closer look at the given publication [1]:

  1. (1)

    Regarding the paper by Suverein et al. published in 2023, ChatGPT attempts to generate an output that is consistent with what would be expected based on the training dataset. Since the ChatGPT's knowledge cutoff date is September 2021 it is unable to discuss a research paper published in 2023. Hence, any forward-looking statement beyond September 2021 will most likely not be true but rather a hallucination unrelated to the 2023 publication. It consists only of sentences based on relationships of preceding words, that lead to some nonsensical content and potentially cause anything from misunderstanding to misinformation.

  2. (2)

    In addition, ChatGPT is unable to search the web and does not yet have access to the National Library of Medicine or other relevant sources with up-to-date information. This can easily be checked by asking for the current time of a specific location. Asking for the local time while writing this manuscript at 3:30 PM CET on Sunday, March 12th, 2023 ChatGPT answered: “The current time in Germany is 11:45 AM CET (Central European Time) on Wednesday, April 8th, 2020”.

  3. (3)

    Another reason for artificial hallucinations may be that ChatGPT and other LLM do not know where the AI is getting its specific responses from. By looking at different sources with varying information, the same prompt can lead to different answers and conclusions. So source control is lacking.

  4. (4)

    In addition, the “temperature” of an LLM affects the output and the extent of the artificial hallucination. “Temperature” can be translated as the degree of confidence a LLM has in its most likely response. A higher temperature makes the answer less confident. ChatGPT uses a temperature of 0.7 for its predictions, allowing the model to generate more diverse responses, or in other words, to “hallucinate.”

In our opinion, LLMs such as ChatGPT will have a substantial impact on medical information processing, but as new technologies they should be critically questioned. Even more importantly, the limits and risks of these technologies should be understood by the users, including those working at the bedside. A prerequisite for using LLM in a productive manner is to avoid fundamental errors like those on board of the spaceship Discovery One, where a computer overruled human intelligence and the obvious reality. Hence, the results of LLMs should be evaluated by medical experts before they are used in research or clinical practice. ChatGPT makes one quickly forget that despite its enormous computational power and incredible database it is still not intelligent but merely programmed to recognize patterns and compile sentences based on probability calculations.

As LLMs can hallucinate artificially, we should remember the words of LSD advocate Timothy Leary: “Think for yourself and question authority.” This also applies to ChatGPT!

Availability of data and materials

Not applicable.


  1. Salvagno M, Taccone FS, Gerli AG. Can artificial intelligence help for scientific writing? Crit Care. 2023;27:75.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Suverein MM, Delnoij TSR, Lorusso R, Brandon Bravo Bruinsma GJ, Otterspoor L, Elzo Kraemer CV, et al. Early extracorporeal CPR for refractory out-of-hospital cardiac arrest. N Engl J Med. 2023;388:299–309.

    Article  PubMed  Google Scholar 

  3. Website [Internet]. Chat GPT. [cited 2023 Mar 13]. Available from:

  4. Belohlavek J, Smalcova J, Rob D, Franek O, Smid O, Pokorna M, et al. Effect of intra-arrest transport, extracorporeal cardiopulmonary resuscitation, and immediate invasive assessment and treatment on functional neurologic outcome in refractory out-of-hospital cardiac arrest: a randomized clinical trial. JAMA. 2022;327:737–47.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Yannopoulos D, Bartos J, Raveendran G, Walser E, Connett J, Murray TA, et al. Advanced reperfusion strategies for patients with out-of-hospital cardiac arrest and refractory ventricular fibrillation (ARREST): a phase 2, single centre, open-label, randomised controlled trial. Lancet. 2020;396:1807–16.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Ji Z, Lee N, Frieske R, Yu T, Su D, Xu Y, et al. Survey of hallucination in natural language generation. ACM Comput Surv. 2023.

    Article  Google Scholar 

  7. Website [Internet]. Available from: Fuller R. 2001: A Space Odyssey, screenplay by Stanley Kubrick and Arthur C. Clarke. Directed and produced by Stanley Kubrick; presented by Metro-Goldwyn-Mayer. 1968; 143 minutes [Internet]. Theology Today. 1968. p. 277–80. Available from:

Download references


Not applicable.

Author information

Authors and Affiliations



GB drafted the manuscript with contributions from JTK and EG. All authors contributed to the review and editing of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Gernot Beutel.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Competing interests

GB is a founding Member of the Working Party “Artificial Intelligence" of the German Society of Hematology and Medical Oncology. The other authors do not have any potential competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Beutel, G., Geerits, E. & Kielstein, J.T. Artificial hallucination: GPT on LSD?. Crit Care 27, 148 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: