Mortlock R, Lucas C
Graduate School of Health, Faculty of Health, University of Technology, Sydney, Australia.
School of Population Health, Faculty of Medicine and Health, University of NSW, Sydney, Australia.
Explor Res Clin Soc Pharm. 2024 Jul 18;15:100481. doi: 10.1016/j.rcsop.2024.100481. eCollection 2024 Sep.
Generative artificial intelligence (Gen-AI), exemplified by the widely adopted ChatGPT, has garnered significant attention in recent years. Its application spans various health education domains, including pharmacy, where its potential benefits and drawbacks have become increasingly apparent. Despite the growing adoption of Gen-AIsuch as ChatGPT in pharmacy education, there remains a critical need to assess and mitigate associated risks. This review exploresthe literature and potential strategies for mitigating risks associated with the integration of Gen-AI in pharmacy education.
To conduct a scoping review to identify implications of Gen-AI in pharmacy education, identify its use and emerging evidence, with a particular focus on strategies which mitigate potential risks to academic integrity.
A scoping review strategy was employed in accordance with the PRISMA-ScR guidelines. Databases searched includedPubMed, ERIC [Education Resources Information Center], Scopus and ProQuestfrom August 2023 to 20 February 2024 and included all relevant records from 1 January 2000 to 20 February 2024 relating specifically to LLM use within pharmacy education. A grey literature search was also conducted due to the emerging nature of this topic. Policies, procedures, and documents from institutions such as universities and colleges, including standards, guidelines, and policy documents, were hand searched and reviewed in their most updated form. These documents were not published in the scientific literature or indexed in academic search engines.
Articles ( = 12) were derived from the scientific data bases and Records ( = 9) derived from the grey literature. Potential use and benefits of Gen-AI within pharmacy education were identified in all included published articles however there was a paucity of published articles related the degree of consideration to the potential risks to academic integrity. Grey literature recordsheld the largest proportion of risk mitigation strategies largely focusing on increased academic and student education and training relating to the ethical use of Gen-AI as well considerations for redesigning of current assessments likely to be a risk for Gen-AI use to academic integrity.
Drawing upon existing literature, this review highlights the importance of evidence-based approaches to address the challenges posed by Gen-AI such as ChatGPT in pharmacy education settings. Additionally, whilst mitigation strategies are suggested, primarily drawn from the grey literature, there is a paucity of traditionally published scientific literature outlining strategies for the practical and ethical implementation of Gen-AI within pharmacy education. Further research related to the responsible and ethical use of Gen-AIin pharmacy curricula; and studies related to strategies adopted to mitigate risks to academic integrity would be beneficial.
以广泛应用的ChatGPT为代表的生成式人工智能（Gen-AI）近年来备受关注。其应用涵盖了包括药学在内的各个健康教育领域，其潜在的益处和弊端也日益明显。尽管ChatGPT等生成式人工智能在药学教育中的应用越来越广泛，但仍迫切需要评估和降低相关风险。本综述探讨了有关文献以及减轻药学教育中整合生成式人工智能相关风险的潜在策略。
进行一项范围综述，以确定生成式人工智能在药学教育中的影响，确定其用途和新出现的证据，特别关注减轻对学术诚信潜在风险的策略。
根据PRISMA-ScR指南采用范围综述策略。检索的数据库包括2023年8月至2024年2月20日期间的PubMed、教育资源信息中心（ERIC）、Scopus和ProQuest，纳入了2000年1月1日至2024年2月20日期间专门与药学教育中使用大语言模型相关的所有记录。由于该主题的新颖性，还进行了灰色文献检索。对大学等机构的政策、程序和文件，包括标准、指南和政策文件，进行了手工检索并以最新形式进行审查。这些文件未发表在科学文献中，也未在学术搜索引擎中索引。
从科学数据库中获取了12篇文章，从灰色文献中获取了9条记录。在所有纳入的已发表文章中都确定了生成式人工智能在药学教育中的潜在用途和益处，然而，关于对学术诚信潜在风险考虑程度的已发表文章很少。灰色文献记录中风险缓解策略的比例最大，主要集中在加强与生成式人工智能道德使用相关的学术和学生教育及培训，以及重新设计当前评估，因为这些评估可能对学术诚信构成生成式人工智能使用风险。
借鉴现有文献，本综述强调了采用循证方法应对生成式人工智能（如ChatGPT）在药学教育环境中带来的挑战的重要性。此外，虽然提出了缓解策略，主要来自灰色文献，但缺乏传统发表的科学文献来概述在药学教育中实际和道德地实施生成式人工智能的策略。开展与药学课程中负责任和道德地使用生成式人工智能相关的进一步研究，以及与为减轻学术诚信风险而采取的策略相关的研究将是有益的。
