Evidence map›Paper›PMID 37680954›Full record

ReviewFrontiers in big data2023

Universal skepticism of ChatGPT: a review of early literature on chat generative pre-trained transformer.

Casey Watters, Michal K Lemanski

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in big data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Article
  6. Review
  7. To trust or not to trust: evaluating the reliability and safety of AI responses to laryngeal cancer queries.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2024
    Article
  8. Article
  9. Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Casey WattersFaculty of Law, Bond University, Gold Coast, QLD, Australia.
Michal K LemanskiInstitute for Human Resource Management, WU Vienna, Vienna, Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

ChatGPT, a new language model developed by OpenAI, has garnered significant attention in various fields since its release. This literature review provides an overview of early ChatGPT literature across multiple disciplines, exploring its applications, limitations, and ethical considerations. The review encompasses Scopus-indexed publications from November 2022 to April 2023 and includes 156 articles related to ChatGPT. The findings reveal a predominance of negative sentiment across disciplines, though subject-specific attitudes must be considered. The review highlights the implications of ChatGPT in many fields including healthcare, raising concerns about employment opportunities and ethical considerations. While ChatGPT holds promise for improved communication, further research is needed to address its capabilities and limitations. This literature review provides insights into early research on ChatGPT, informing future investigations and practical applications of chatbot technology, as well as development and usage of generative AI.

Indexed as

AIartificial intelligenceChatGPTdisruptive technologyGPTlarge language model (LLM)transformer

Identifiers

PMID37680954
PMCPMC10482048

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.