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Enregistrement W4378173236 · doi:10.1093/asj/sjad162

Preservation of Human Creativity in Plastic Surgery Research on ChatGPT

2023· letter· en· W4378173236 sur OpenAlexaff
Jad Abi‐Rafeh, Hong Hao Xu, Roy Kazan

Notice bibliographique

RevueAesthetic Surgery Journal · 2023
Typeletter
Langueen
DomaineMedicine
ThématiqueArtificial Intelligence in Healthcare and Education
Établissements canadiensUniversité LavalMcGill UniversityMcGill University Health Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineCreativityPlastic surgerySurgerySocial psychology

Résumé

récupéré en direct d'OpenAlex

We read with great interest the latest series by Gupta et al published in Aesthetic Surgery Journal, examining and reporting on promising yet concerning applications of ChatGPT (OpenAI, San Francisco, CA) in scholarly practice.1‐4 ChatGPT is a novel large language and artificial intelligence (AI) model recently released by OpenAI, which has proven capable of interpreting, synthesizing, and outputting information in the form of traditional human text.1‐7 AI represents a rapidly evolving technology within the field of computer science, providing computer systems with the ability to emulate human intelligence and perform human-like tasks.2 Taken together, AI and ChatGPT bring infinite potential through a confluence of capabilities in autonomous perception, knowledge synthesis, as well as inference of information. Unsurprisingly, plastic surgeons have been drawn to the potential for innovation that AI and ChatGPT can bestow upon our specialty. Indeed, publications on the potential role of ChatGPT in plastic surgery have been on the rise. As of May 15, 2023, 19 articles have been published investigating or postulating applications of ChatGPT in plastic surgery. Eight studies (42%) appear to be published by the same group of authors: Gupta et al. and Najafali et al.1‐7 Novelty in research lies not in new permutations of the same idea, but in novel propositions and methodologies with the potential to improve and advance practice, independently of what has been previously published. In a letter published in February 2023, Gupta et al reported on ChatGPT's ability to generate novel systematic review ideas in the field of aesthetic surgery, with variable and imperfect performance demonstrated according to specific topics examined (general aesthetic surgery vs rhinoplasty vs blepharoplasty).1 In March 2023, Gupta et al published again on ChatGPT's ability to generate novel systematic review ideas; this time, for 6 surgical and 6 nonsurgical procedures in aesthetic surgery, again, with variable and imperfect performance reported.2 In the same month, they published in a different journal on ChatGPT's ability to again generate systematic review ideas, now with relevance to different subspecialties in plastic surgery, including cosmetic surgery, craniofacial surgery, microsurgery, and hand surgery.3 They once again reported variable and imperfect performance. Now, and most recently, Gupta et al have published again on ChatGPT's ability, in its new version ChatGPT-4, to generate systematic review ideas, for the same topics previously examined1,4 Again, they report variable and imperfect performance.4 In parallel, Najafali et al published a letter in March 2023, in response to Gupta et al, accentuating the significant ethical limitations associated with the use of ChatGPT in research and scholarly practice, urging “caution when using ChatGPT.”5 Nonetheless, in April 2023, Najafali et al published on ChatGPT's ability to write an entire systematic review on vaginoplasty,6 and later that month, on ChatGPT's ability to write grant applications.7 When analyzing the literature, we must question the value new publications bring to our specialty. The ability of ChatGPT to generate novel systematic review ideas with reference to topics it is provided with has clearly been established, as has its ability to engage in (potentially unethical) scholarly activities, which Najafali et al caution against,5 but also publish on.6,7 Research into the applications of ChatGPT may be stratified and approached with reference to the target emulated human behavior, and the person ChatGPT may be of assistance to in these demonstrated applications. Examples from the former classification include creative thinking, critical thinking, data curation, data analysis, writing, or communication, to name a few. Examples of categories within the latter group include applications that assist the plastic surgeon in her capacity as a researcher/scholar, the plastic surgeon in her capacity as a clinician, the plastic surgery patient, or the plastic surgeon educator and/or trainee. The 6 aforementioned studies all investigate and report on the same capabilities of ChatGPT, the same target emulated human behaviors, and the same (controversial and potentially unethical) applications “assisting” the plastic surgeon researcher/scholar. Regardless of permutations and replications, the conclusion remains the same—ChatGPT is capable of generating systematic review ideas with variable and imperfect performance, and can engage in different levels of scientific writing under human direction. So then, we must ask, what benefit does the next publication bring relative to the prior? The overarching goal of research into AI and ChatGPT remains directed towards closing the gap between postulated utility and adoption. As researchers, the potential that AI can bring to our specialty, and to our patients, is what drives us. To inch our specialty closer to the promise and potential of AI, we must work towards widespread adoption. But before we can achieve this, we must design rigorous and methodologically sound studies on applications of ChatGPT across the array of aforementioned categories of applications. Its performance then needs to be validated and objectively assessed with reference to the highest human standards of care and ethics. Only then will we know whether this technology, in its present form, is suitable for adoption, or whether further developments, refinements, and regulations are necessary—guided by our findings. Creativity may already be endangered by the infringement of AI into academic and scholarly activities. Let us not facilitate this process by maintaining the highest standards of human critical and creative thinking, which have and continue to define our specialty. We commend the authors on their demonstrated passion and productivity through their work, and look forward to future studies they will produce in line with the recommendations provided herein. The authors declared no potential conflicts of interest with respect to the research, authorship, and publication of this article. The authors received no financial support for the research, authorship, and publication of this article.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,003
score de la tête « metaresearch » (Gemma)0,014
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: Méthodes · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,997
Score d'incertitude au seuil0,023

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0030,014
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0020,005
Communication savante0,0020,002
Science ouverte0,0010,002
Intégrité de la recherche0,0070,008
Charge utile insuffisante (le modèle a refusé de juger)0,0070,002

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,579
Tête enseignante GPT0,510
Écart entre enseignants0,069 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Devis d'étudeSans objet
DomaineMéthodes
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations14
Publié2023
Routes d'admission1
Résumé présentnon

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