Qualitative Health Research, Год журнала: 2023, Номер 33(13), С. 1135 - 1139
Опубликована: Окт. 28, 2023
Язык: Английский
Qualitative Health Research, Год журнала: 2023, Номер 33(13), С. 1135 - 1139
Опубликована: Окт. 28, 2023
Язык: Английский
The Lancet Digital Health, Год журнала: 2024, Номер 6(6), С. e428 - e432
Опубликована: Апрель 23, 2024
With the rapid growth of interest in and use large language models (LLMs) across various industries, we are facing some crucial profound ethical concerns, especially medical field. The unique technical architecture purported emergent abilities LLMs differentiate them substantially from other artificial intelligence (AI) natural processing techniques used, necessitating a nuanced understanding LLM ethics. In this Viewpoint, highlight concerns stemming perspectives users, developers, regulators, notably focusing on data privacy rights use, provenance, intellectual property contamination, broad applications plasticity LLMs. A comprehensive framework mitigating strategies will be imperative for responsible integration into practice, ensuring alignment with principles safeguarding against potential societal risks.
Язык: Английский
Процитировано
82Frontiers in Artificial Intelligence, Год журнала: 2024, Номер 6
Опубликована: Янв. 5, 2024
This paper presents a comprehensive analysis of the scholarly footprint ChatGPT, an AI language model, using bibliometric and scientometric methods. The study zooms in on early outbreak phase from when ChatGPT was launched November 2022 to June 2023. It aims understand evolution research output, citation patterns, collaborative networks, application domains, future directions related ChatGPT. By retrieving data Scopus database, 533 relevant articles were identified for analysis. findings reveal prominent publication venues, influential authors, countries contributing research. Collaborative networks among researchers institutions are visualized, highlighting patterns co-authorship. domains such as customer support content generation, examined. Moreover, identifies emerging keywords potential areas exploration. methodology employed includes extraction, various indicators, visualization techniques Sankey diagrams. provides valuable insights into ChatGPT's academia offers guidance further advancements. stimulates discussions, collaborations, innovations enhance capabilities impact across domains.
Язык: Английский
Процитировано
27International Transactions in Operational Research, Год журнала: 2024, Номер unknown
Опубликована: Июль 31, 2024
Abstract Artificial intelligence (AI) as a disruptive technology is not new. However, its recent evolution, engineered by technological transformation, big data analytics, and quantum computing, produces conversational generative AI (CGAI/GenAI) human‐like chatbots that disrupt conventional operations methods in different fields. This study investigates the scientific landscape of CGAI human–chatbot interaction/collaboration evaluates use cases, benefits, challenges, policy implications for multidisciplinary education allied industry operations. The publications trend showed just 4% ( n = 75) occurred during 2006–2018, while 2019–2023 experienced astronomical growth 1763 or 96%). prominent cases (e.g., ChatGPT) teaching, learning, research activities computer science (multidisciplinary AI; 32%), medical/healthcare (17%), engineering (7%), business fields (6%). intellectual structure shows strong collaboration among eminent sources business, information systems, other areas. thematic highlights including improved user experience human–computer interaction, programs/code generation, systems creation. Widespread usefulness teachers, researchers, learners includes syllabi/course content testing aids, academic writing. concerns about abuse misuse (plagiarism, integrity, privacy violations) issues misinformation, danger self‐diagnoses, patient applications are prominent. Formulating strategies policies to address potential challenges teaching/learning practice priorities. Developing discipline‐based automatic detection GenAI contents check proposed. In operational/operations areas, proper CGAI/GenAI integration with modeling decision support requires further studies.
Язык: Английский
Процитировано
23Innovations in Education and Teaching International, Год журнала: 2024, Номер unknown, С. 1 - 13
Опубликована: Фев. 18, 2024
Язык: Английский
Процитировано
22AI and Ethics, Год журнала: 2024, Номер unknown
Опубликована: Янв. 3, 2024
Язык: Английский
Процитировано
21AI & Society, Год журнала: 2024, Номер 39(6), С. 3017 - 3029
Опубликована: Янв. 12, 2024
Язык: Английский
Процитировано
12Journal of Pediatric Ophthalmology & Strabismus, Год журнала: 2024, Номер 61(5), С. 325 - 331
Опубликована: Апрель 25, 2024
To evaluate the understandability, actionability, and readability of responses provided by website American Association for Pediatric Ophthalmology Strabismus (AAPOS), ChatGPT-3.5, Bard, Bing Chat about amblyopia appropriateness generated chatbots.
Язык: Английский
Процитировано
11Frontiers in Education, Год журнала: 2024, Номер 9
Опубликована: Авг. 7, 2024
Background The use of ChatGPT among university students has gained a recent popularity. current study aimed to assess the factors driving attitude and usage as an example generative artificial intelligence (genAI) in United Arab Emirates (UAE). Methods This cross-sectional was based on previously validated Technology Acceptance Model (TAM)-based survey instrument termed TAME-ChatGPT. self-administered e-survey distributed by emails for enrolled UAE universities during September–December 2023 using convenience-based approach. Assessment demographic academic variables, TAME-ChatGPT constructs’ roles conducted univariate followed multivariate analyses. Results final sample comprised 608 participants, 91.0% whom heard while 85.4% used before study. Univariate analysis indicated that positive associated with three constructs namely, lower perceived risks, anxiety, higher scores technology/social influence. For usage, being male, nationality, point grade average (GPA) well four usefulness, risks use, behavior/cognitive construct ease-of-use construct. In analysis, only explained variance towards (80.8%) its (76.9%). Conclusion findings is commonplace UAE. determinants included cognitive behavioral factors, ease determined These should be considered understanding motivators successful adoption genAI including education.
Язык: Английский
Процитировано
11Neurocomputing, Год журнала: 2024, Номер 582, С. 127468 - 127468
Опубликована: Март 12, 2024
Язык: Английский
Процитировано
10Facial Plastic Surgery & Aesthetic Medicine, Год журнала: 2023, Номер 26(3), С. 270 - 275
Опубликована: Ноя. 20, 2023
Large language models, such as ChatGPT, hold tremendous promise to bridge gaps in patient education and enhance the decision-making resources available online for patients seeking nasal surgery.
Язык: Английский
Процитировано
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