Annals of Biomedical Engineering, Год журнала: 2023, Номер 52(2), С. 130 - 133
Опубликована: Июнь 28, 2023
Язык: Английский
Education Sciences, Год журнала: 2023, Номер 13(4), С. 410 - 410
Опубликована: Апрель 18, 2023
An artificial intelligence-based chatbot, ChatGPT, was launched in November 2022 and is capable of generating cohesive informative human-like responses to user input. This rapid review the literature aims enrich our understanding ChatGPT’s capabilities across subject domains, how it can be used education, potential issues raised by researchers during first three months its release (i.e., December February 2023). A search relevant databases Google Scholar yielded 50 articles for content analysis open coding, axial selective coding). The findings this suggest that performance varied ranging from outstanding (e.g., economics) satisfactory programming) unsatisfactory mathematics). Although ChatGPT has serve as an assistant instructors generate course materials provide suggestions) a virtual tutor students answer questions facilitate collaboration), there were challenges associated with use incorrect or fake information bypassing plagiarism detectors). Immediate action should taken update assessment methods institutional policies schools universities. Instructor training student education are also essential respond impact on educational environment.
Язык: Английский
Процитировано
1042
Innovations in Education and Teaching International, Год журнала: 2023, Номер 61(3), С. 460 - 474
Опубликована: Март 27, 2023
ChatGPT is an AI tool that has sparked debates about its potential implications for education. We used the SWOT analysis framework to outline ChatGPT's strengths and weaknesses discuss opportunities threats The include using a sophisticated natural language model generate plausible answers, self-improving capability, providing personalised real-time responses. As such, can increase access information, facilitate complex learning, decrease teaching workload, thereby making key processes tasks more efficient. are lack of deep understanding, difficulty in evaluating quality responses, risk bias discrimination, higher-order thinking skills. Threats education understanding context, threatening academic integrity, perpetuating discrimination education, democratising plagiarism, declining high-order cognitive provide agenda educational practice research times ChatGPT.
Язык: Английский
Процитировано
639
npj Digital Medicine, Год журнала: 2023, Номер 6(1)
Опубликована: Июль 6, 2023
The rapid advancements in artificial intelligence (AI) have led to the development of sophisticated large language models (LLMs) such as GPT-4 and Bard. potential implementation LLMs healthcare settings has already garnered considerable attention because their diverse applications that include facilitating clinical documentation, obtaining insurance pre-authorization, summarizing research papers, or working a chatbot answer questions for patients about specific data concerns. While offering transformative potential, warrant very cautious approach since these are trained differently from AI-based medical technologies regulated already, especially within critical context caring patients. newest version, GPT-4, was released March, 2023, brings potentials this technology support multiple tasks; risks mishandling results it provides varying reliability new level. Besides being an advanced LLM, will be able read texts on images analyze those images. regulation generative AI medicine without damaging exciting is timely challenge ensure safety, maintain ethical standards, protect patient privacy. We argue regulatory oversight should assure professionals can use causing harm compromising This paper summarizes our practical recommendations what we expect regulators bring vision reality.
Язык: Английский
Процитировано
509
British Journal of Educational Technology, Год журнала: 2023, Номер 55(1), С. 90 - 112
Опубликована: Авг. 6, 2023
Abstract Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate laborious process of generating and analysing textual content. While various been developed a range educational tasks (eg, question generation, feedback provision, essay grading), there are concerns regarding practicality ethicality these innovations. Such may hinder future research adoption LLMs‐based in authentic contexts. To address this, we conducted systematic scoping review 118 peer‐reviewed papers published since 2017 pinpoint current state on using LLMs support tasks. The findings revealed 53 use cases for automating education tasks, categorised into nine main categories: profiling/labelling, detection, grading, teaching support, prediction, knowledge representation, feedback, content recommendation. Additionally, also identified several practical ethical challenges, including low technological readiness, lack replicability transparency insufficient privacy beneficence considerations. were summarised three recommendations studies, updating existing with state‐of‐the‐art GPT‐3/4), embracing initiative open‐sourcing models/systems, adopting human‐centred approach throughout developmental process. As intersection AI is continuously evolving, this study can serve as an essential reference point researchers, allowing them leverage strengths, learn from limitations, uncover opportunities enabled by ChatGPT other generative models. Practitioner notes What currently known about topic Generating text‐based time‐consuming Large capable efficiently unprecedented amount completing complex natural processing generation increasingly used develop technologies that aim analysis content, such automated scoring. paper adds A comprehensive list different could potentially benefit through automation. structured assessment seven important aspects established frameworks. Three studies implement Implications practice and/or policy Updating further reduce manual effort required adapting reporting standards empirical aims need be improved. Adopting contribute resolving challenges education.
Язык: Английский
Процитировано
210
Narra J, Год журнала: 2023, Номер 3(1), С. e103 - e103
Опубликована: Март 29, 2023
Since its public release in November 2022, ChatGPT has gained a widespread attention and received mixed responses the academia. Promising applications of university education been suggested; however, several concerns were raised. The aim this descriptive study was to investigate pros cons use medical, dental, pharmacy, health education. Based on expert panel discussion review existing literature, specific concise prompts constructed generated 25 February 2023. Out data suggested that medical education, benefits included possibility improving personalized learning, clinical reasoning understanding complex concepts. listed context dental improved skills through step-by-step instructions interactive content, with instant feedback student techniques. In pharmacy advantages possible explanations subjects deployment tools aiding develop for patient counselling. providing case scenarios, besides analysis literature review. limitations based ChatGPT-generated content common across all investigated healthcare disciplines privacy issues, risk generating biased inaccurate deterioration critical thinking communication among students. deemed partially helpful by panel. However, important points regarding missed including: plagiarism, copyright academic dishonesty, lack personal emotional interactions necessary developing proper conclusion, despite promising prospects drawbacks should be addressed implementation guidelines ensure exploiting innovative technology.
Язык: Английский
Процитировано
192
Опубликована: Июль 10, 2023
<p>Within the vast expanse of computerized language processing, a revolutionary entity known as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to comprehend intricate linguistic patterns and conjure coherent contextually fitting responses. models are type artificial intelligence (AI) that have emerged powerful tools for wide range tasks, including natural processing (NLP), machine translation, question-answering. This survey paper provides comprehensive overview LLMs, their history, architecture, training methods, applications, challenges. The begins by discussing fundamental concepts generative AI architecture pre- trained transformers (GPT). It then an history evolution over time, different methods been used train them. discusses applications medical, education, finance, engineering. also how LLMs shaping future they can be solve real-world problems. challenges associated with deploying scenarios, ethical considerations, model biases, interpretability, computational resource requirements. highlights techniques enhancing robustness controllability addressing bias, fairness, generation quality issues. Finally, concludes highlighting LLM research need addressed order make more reliable useful. is intended provide researchers, practitioners, enthusiasts understanding evolution, By consolidating state-of-the-art knowledge field, this serves valuable further advancements development utilization applications. GitHub repo project available at https://github.com/anas-zafar/LLM-Survey</p>
Язык: Английский
Процитировано
176
JMIR Human Factors, Год журнала: 2023, Номер 10, С. e47564 - e47564
Опубликована: Май 9, 2023
With the rapid advancement of artificial intelligence (AI) technologies, AI-powered chatbots, such as Chat Generative Pretrained Transformer (ChatGPT), have emerged potential tools for various applications, including health care. However, ChatGPT is not specifically designed care purposes, and its use self-diagnosis raises concerns regarding adoption's risks benefits. Users are increasingly inclined to self-diagnosis, necessitating a deeper understanding factors driving this trend.
Язык: Английский
Процитировано
163
Internet of Things and Cyber-Physical Systems, Год журнала: 2023, Номер 3, С. 262 - 271
Опубликована: Янв. 1, 2023
Artificial intelligence (AI) and machine learning have changed the nature of scientific inquiry in recent years. Of these, development virtual assistants has accelerated greatly past few years, with ChatGPT becoming a prominent AI language model. In this study, we examine foundations, vision, research challenges ChatGPT. This article investigates into background technology behind it, as well its popular applications. Moreover, discuss advantages bringing everything together through Internet Things (IoT). Further, speculate on future by considering various possibilities for study development, such energy-efficiency, cybersecurity, enhancing applicability to additional technologies (Robotics Computer Vision), strengthening human-AI communications, bridging technological gap. Finally, important ethics current trends
Язык: Английский
Процитировано
156
AI, Год журнала: 2023, Номер 4(2), С. 375 - 384
Опубликована: Апрель 10, 2023
ChatGPT is an AI-powered chatbot platform that enables human users to converse with machines. It utilizes natural language processing and machine learning algorithms, transforming how people interact AI technology. offers significant advantages over previous similar tools, its potential for application in various fields has generated attention anticipation. However, some experts are wary of ChatGPT, citing ethical implications. Therefore, this paper shows transform marketing shape future if certain considerations taken into account. First, we argue ChatGPT-based tools can help marketers create content faster potentially quality creators. also assist conducting more efficient research understanding customers better, automating customer service, improving efficiency. Then discuss implications risks marketers, consumers, other stakeholders, essential marketing; doing so revolutionize while avoiding harm stakeholders.
Язык: Английский
Процитировано
126
Scientific Reports, Год журнала: 2023, Номер 13(1)
Опубликована: Сен. 15, 2023
Abstract The release and rapid diffusion of ChatGPT have caught the attention educators worldwide. Some are enthusiastic about its potential to support learning. Others concerned how it might circumvent learning opportunities or contribute misinformation. To better understand reactions concerning education, we analyzed Twitter data (16,830,997 tweets from 5,541,457 users). Based on topic modeling sentiment analysis, provide an overview global perceptions regarding education. triggered a massive response Twitter, with education being most tweeted content topic. Topics ranged specific (e.g., cheating) broad opportunities), which were discussed mixed sentiment. We traced that authority decisions may influence public opinions. average reaction using cheat in exams) differs discussions teaching–learning researchers likely be more interested as intelligent partner). This study provides insights into people's when new groundbreaking technology is released implications for scientific policy communication rapidly changing circumstances.
Язык: Английский
Процитировано
113