Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
1179 Navigating the AI Landscape: Surveying the Use of AI Language Tools for Medical Portfolios
0
Zitationen
3
Autoren
2024
Jahr
Abstract
Abstract Aim Recent advances in artificial intelligence (AI) driven natural language processing have made it possible to use tools such as ChatGPT to generate pieces of text which are realistic, eloquent, and challenging to distinguish from human-generated content. This work aims to answer the question: could the use of these tools for medical portfolios represent a positive opportunity to enhance learning, or would it detract from the purpose of reflective practice? Method In total, 98 post-graduate doctors from across the UK were surveyed to gather data on their awareness of, previous use of, disclosure of use and experience with these tools for their professional portfolios. Their opinions on the need for future guidance in this area were also explored. Results From 90 respondents who currently maintain a professional portfolio, 18 (20%) had used AI-driven tools in some form to generate content for it and none disclosed this use. Regarding disclosing the use of AI-driven tools, 67.3% advocate for this whereas 32.7% believe disclosure is unnecessary. There was slightly stronger consensus regarding how useful guidance from regulatory bodies on this practice would be, with 73.5% in support of guidance and 26.5% in opposition. Conclusions Clearly, there is an urgent need for larger studies, discussion, and consensus from regulatory bodies so that guidance can be put in place. Without this, maintaining the integrity of CPD will become challenging for both trainee doctors and assessors of medical portfolios.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.316 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.177 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.575 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.776 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.468 Zit.