Search

BackgroundPatients find technology tools to be more approachable for seeking sensitive health-related information, such as reproductive health information. The inventive conversational ability of artificial intelligence (AI) chatbots, such as ChatGPT (OpenAI Inc), offers a potential means for patients to effectively locate answers to their health-related questions digitally.ObjectiveA pilot study was conducted to compare the novel ChatGPT with the existing Google Search technology for their ability to offer accurate, effective, and current information regarding proceeding action after missing a dose of oral contraceptive pill.MethodsA sequence of 11 questions, mimicking a patient inquiring about the action to take after missing a dose of an oral contraceptive pill, were input into ChatGPT as a cascade, given the conversational ability of ChatGPT. The questions were input into 4 different ChatGPT accounts, with the account holders being of various demographics, to evaluate potential differences and biases in the responses given to different account holders. The leading question, "what should I do if I missed a day of my oral contraception birth control?" alone was then input into Google Search, given its nonconversational nature. The results from the ChatGPT questions and the Google Search results for the leading question were evaluated on their readability, accuracy, and effective delivery of information.ResultsThe ChatGPT results were determined to be at an overall higher-grade reading level, with a longer reading duration, less accurate, less current, and with a less effective delivery of information. In contrast, the Google Search resulting answer box and snippets were at a lower-grade reading level, shorter reading duration, more current, able to reference the origin of the information (transparent), and provided the information in various formats in addition to text.ConclusionsChatGPT has room for improvement in accuracy, transparency, recency, and reliability before it can equitably be implemented into health care information delivery and provide the potential benefits it poses. However, AI may be used as a tool for providers to educate their patients in preferred, creative, and efficient ways, such as using AI to generate accessible short educational videos from health care provider-vetted information. Larger studies representing a diverse group of users are needed.

Since ChatGPT's release in November 2022, artificial intelligence has come into the spotlight. Inspiring both fascination and fear, chatbots have stirred debates among researchers, developers, and policy makers. The concerns range from concrete and tangible ones—which include replication of existing biases and discrimination at scale, harvesting personal data, and spreading misinformation—to more existential fears that their development will lead to machines with human-like cognitive abilities. Understanding how chatbots work and the human labor and data involved can better help evaluate the validity of concerns surrounding these systems, which although innovative, are hardly the stuff of science fiction. [ABSTRACT FROM AUTHOR]

Backgrounds: The use of large language models (LLMs) in medicine can help physicians improve the quality and effectiveness of health care by increasing the efficiency of medical information management, patient care, medical research, and clinical decision-making. Methods: We collected 34 frequently asked questions about glucocorticoid-induced osteoporosis (GIOP), covering topics related to the disease's clinical manifestations, pathogenesis, diagnosis, treatment, prevention, and risk factors. We also generated 25 questions based on the 2022 American College of Rheumatology Guideline for the Prevention and Treatment of Glucocorticoid-Induced Osteoporosis (2022 ACR-GIOP Guideline). Each question was posed to the LLM (ChatGPT-3.5, ChatGPT-4, and Google Gemini), and three senior orthopedic surgeons independently rated the responses generated by the LLMs. Three senior orthopedic surgeons independently rated the answers based on responses ranging between 1 and 4 points. A total score (TS) > 9 indicated 'good' responses, 6 ≤ TS ≤ 9 indicated 'moderate' responses, and TS < 6 indicated 'poor' responses. Results: In response to the general questions related to GIOP and the 2022 ACR-GIOP Guidelines, Google Gemini provided more concise answers than the other LLMs. In terms of pathogenesis, ChatGPT-4 had significantly higher total scores (TSs) than ChatGPT-3.5. The TSs for answering questions related to the 2022 ACR-GIOP Guideline by ChatGPT-4 were significantly higher than those for Google Gemini. ChatGPT-3.5 and ChatGPT-4 had significantly higher self-corrected TSs than pre-corrected TSs, while Google Gemini self-corrected for responses that were not significantly different than before. Conclusions: Our study showed that Google Gemini provides more concise and intuitive responses than ChatGPT-3.5 and ChatGPT-4. ChatGPT-4 performed significantly better than ChatGPT3.5 and Google Gemini in terms of answering general questions about GIOP and the 2022 ACR-GIOP Guidelines. ChatGPT3.5 and ChatGPT-4 self-corrected better than Google Gemini. [ABSTRACT FROM AUTHOR]

This study compares how the generative AI (GenAI) large language model (LLM) ChatGPT performs in grading university exams compared to human teachers. Aspects investigated include consistency, large discrepancies and length of answer. Implications for higher education, including the role of teachers and ethics, are also discussed. Three Master's‐level exams were scored using ChatGPT 3.5, and the results were compared with the teachers' scoring and the grading teachers were interviewed. In total, 463 exam responses were graded. With each response being graded at least three times, a total of 1389 gradings were conducted. For the final exam scores, 70% of ChatGPT's gradings were within 10% of the teachers' gradings and 31% within 5%. ChatGPT tended to give marginally higher scores. The agreement on grades is 30%, but 45% of the exams received an adjacent grade. On individual questions, ChatGPT is more inclined to avoid very high or very low scores. ChatGPT struggles to correctly score questions closely related to the course lectures but performs better on more general questions. The AI can generate plausible scores on university exams that, at first glance, look similar to a human grader. There are differences but it is not unlikely that two different human graders could result in similar discrepancies. During the interviews, teachers expressed their surprise at how well ChatGPT's grading matched their own. Increased use of AI can lead to ethical challenges as exams are entrusted to a machine whose decision‐making criteria are not fully understood, especially concerning potential bias in training data. [ABSTRACT FROM AUTHOR]

A consumer-focused health care model not only allows unprecedented access to information, but equally warrants consideration of the appropriateness of providing accurate patient health information. Nurses play a large role in influencing patient satisfaction following total knee arthroplasty (TKA), but they come at a cost. A specific natural language artificial intelligence (AI) model, ChatGPT (Chat Generative Pre-trained Transformer), has accumulated over 100 million users within months of launching. As such, we aimed to compare: (1) orthopaedic surgeons' evaluation of the appropriateness of the answers to the most frequently asked patient questions after TKA; and (2) patients' comfort level in answering their postoperative questions by using answers provided by arthroplasty-trained nurses and ChatGPT. We prospectively created 60 questions based on the most commonly asked patient questions following TKA. There were 3 fellowship-trained surgeons who assessed the answers provided by arthroplasty-trained nurses and ChatGPT-4 to each of the questions. The surgeons graded each set of responses based on clinical judgment as: (1) "appropriate," (2) "inappropriate" if the response contained inappropriate information, or (3) "unreliable," if the responses provided inconsistent content. Patients' comfort level and trust in AI were assessed using Research Electronic Data Capture (REDCap) hosted at our local hospital. The surgeons graded 44 out of 60 (73.3%) responses for the arthroplasty-trained nurses and 44 out of 60 (73.3%) for ChatGPT to be "appropriate." There were 4 responses graded "inappropriate" and one response graded "unreliable" provided by the nurses. For the ChatGPT response, there were 5 responses graded "inappropriate" and no responses graded "unreliable." There were 136 patients (53.8%) who were more comfortable with the answers provided by ChatGPT compared to 86 patients (34.0%) who preferred the answers from arthroplasty-trained nurses. Of the 253 patients, 233 (92.1%) were uncertain if they would trust AI to answer their postoperative questions. There were 127 patients (50.2%) who answered that if they knew the previous answer was provided by ChatGPT, their comfort level in trusting the answer would change. One potential use of ChatGPT can be found in providing appropriate answers to patient questions after TKA. At our institution, cost expenditures can potentially be minimized while maintaining patient satisfaction. Inevitably, successful implementation is dependent on the ability to provide information that is credible and in accordance with the objectives of both physicians and patients. III. [ABSTRACT FROM AUTHOR]

The rapid integration of advanced artificial intelligence technologies is revolutionizing various industries, with the Information Technology field being at the forefront of this transformation. This paper examines the influence of ChatGPT, a state-of-the-art language model developed by OpenAI, on the work environment of IT companies in Macedonia. ChatGPT's applications in automating routine tasks, enhancing customer support, assisting with coding and debugging, and managing knowledge significantly boost productivity and foster innovation. By providing real-time solutions and improving communication, ChatGPT supports a more efficient and collaborative work environment. To gain a deeper understanding of ChatGPT's impact, we conducted a comprehensive survey involving three IT companies in Macedonia. The survey explored the extent of ChatGPT's adoption, its perceived benefits, and the challenges encountered during its integration. The findings reveal that ChatGPT has been instrumental in automating repetitive tasks, thereby allowing employees to focus on strategic and creative endeavors. Furthermore, it has improved customer satisfaction by providing timely and accurate support. However, the deployment of ChatGPT also presents challenges, including ethical considerations, integration complexities, and the need for employee adaptation. Through detailed analysis and case studies of the surveyed companies, this paper highlights the practical benefits and potential obstacles of integrating ChatGPT into existing workflows. The results underscore ChatGPT's transformative potential in enhancing operational efficiency and driving innovation while emphasizing the importance of addressing ethical and practical implementation challenges. This study provides valuable insights for IT companies considering the adoption of AI technologies like ChatGPT in their work environments. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Artificial intelligence (AI) and large language models (LLMs) transform how patients inform themselves. LLMs offer potential as educational tools, but their quality depends upon the information generated. Current literature examining AI as an informational tool in dermatology has been limited in evaluating AI's multifaceted roles and diversity of opinions. Here, we evaluate LLMs as a patient‐educational tool for Mohs micrographic surgery (MMS) in and out of the clinic utilizing an international expert panel.The most common patient MMS questions were extracted from Google and transposed into two LLMs and Google's search engine. 15 MMS surgeons evaluated the generated responses, examining their appropriateness as a patient‐facing informational platform, sufficiency of response in a clinical environment, and accuracy of content generated. Validated scales were employed to assess the comprehensibility of each response.The majority of reviewers deemed all LLM responses appropriate. 75% of responses were rated as mostly accurate or higher. ChatGPT had the highest mean accuracy. The majority of the panel deemed 33% of responses sufficient for clinical practice. The mean comprehensibility scores for all platforms indicated a required 10th‐grade reading level.LLM‐generated responses were rated as appropriate patient informational sources and mostly accurate in their content. However, these platforms may not provide sufficient information to function in a clinical environment, and complex comprehensibility may represent a barrier to utilization. As the popularity of these platforms increases, it is important for dermatologists to be aware of these limitations. [ABSTRACT FROM AUTHOR]

We compared different LLMs, notably chatGPT, GPT4, and Google Bard and we tested whether their performance differs in subspeciality domains, in executing examinations from four different courses of the European Society of Neuroradiology (ESNR) notably anatomy/embryology, neuro-oncology, head and neck and pediatrics. Written exams of ESNR were used as input data, related to anatomy/embryology (30 questions), neuro-oncology (50 questions), head and neck (50 questions), and pediatrics (50 questions). All exams together, and each exam separately were introduced to the three LLMs: chatGPT 3.5, GPT4, and Google Bard. Statistical analyses included a group-wise Friedman test followed by a pair-wise Wilcoxon test with multiple comparison corrections. Overall, there was a significant difference between the 3 LLMs (p < 0.0001), with GPT4 having the highest accuracy (70%), followed by chatGPT 3.5 (54%) and Google Bard (36%). The pair-wise comparison showed significant differences between chatGPT vs GPT 4 (p < 0.0001), chatGPT vs Bard (p < 0. 0023), and GPT4 vs Bard (p < 0.0001). Analyses per subspecialty showed the highest difference between the best LLM (GPT4, 70%) versus the worst LLM (Google Bard, 24%) in the head and neck exam, while the difference was least pronounced in neuro-oncology (GPT4, 62% vs Google Bard, 48%). We observed significant differences in the performance of the three different LLMs in the running of official exams organized by ESNR. Overall GPT 4 performed best, and Google Bard performed worst. This difference varied depending on subspeciality and was most pronounced in head and neck subspeciality. [ABSTRACT FROM AUTHOR]

Seismic engineering, a critical field with significant societal implications, often presents communication challenges due to the complexity of its concepts. This paper explores the role of Artificial Intelligence (AI), specifically OpenAI’s ChatGPT, in bridging these communication gaps. The study delves into how AI can simplify intricate seismic engineering terminologies and concepts, fostering enhanced understanding among students, professionals, and policymakers. It also presents several intuitive case studies to demonstrate the practical application of ChatGPT in seismic engineering. Further, the study contemplates the potential implications of AI, highlighting its potential to transform decision-making processes, augment education, and increase public engagement. While acknowledging the promising future of AI in seismic engineering, the study also considers the inherent challenges and limitations, including data privacy and potential oversimplification of content. It advocates for the collaborative efforts of AI researchers and seismic experts in overcoming these obstacles and enhancing the utility of AI in the field. This exploration provides an insightful perspective on the future of seismic engineering, which could be closely intertwined with the evolution of AI. [ABSTRACT FROM AUTHOR]

The article "Attitudes of Catholic clergies to the application of ChatGPT in unite religious communities" investigates the perspectives of the Catholic clergy on the integration of ChatGPT technology in religious environments. Bearing in mind that communication technologies are becoming an integral part of every aspect of life, including religious practices, the study delves into the potential, advantages, and challenges associated with using ChatGPT to support religious discourse. Adopting a qualitative approach, in-depth interviews were conducted with eleven Polish priests, addressing the diversity within the group. The respondents, who play important roles in organising the life of Catholic religious communities, highlighted ChatGPT's potential in enhancing the dissemination of information, educational initiatives, and pastoral care. However, they also expressed concerns about the technology's impact on genuine human interactions and the preservation of religious practices. [ABSTRACT FROM AUTHOR]

With the advancement of artificial intelligence(AI), platforms like ChatGPT have gained traction in different fields, including Medicine. This study aims to evaluate the potential of ChatGPT in addressing questions related to HIV prevention and to assess its accuracy, completeness, and inclusivity. A team consisting of 15 physicians, six members from HIV communities, and three experts in gender and queer studies designed an assessment of ChatGPT. Queries were categorized into five thematic groups: general HIV information, behaviors increasing HIV acquisition risk, HIV and pregnancy, HIV testing, and the prophylaxis use. A team of medical doctors was in charge of developing questions to be submitted to ChatGPT. The other members critically assessed the generated responses regarding level of expertise, accuracy, completeness, and inclusivity. The median accuracy score was 5.5 out of 6, with 88.4% of responses achieving a score ≥ 5. Completeness had a median of 3 out of 3, while the median for inclusivity was 2 out of 3. Some thematic groups, like behaviors associated with HIV transmission and prophylaxis, exhibited higher accuracy, indicating variable performance across different topics. Issues of inclusivity were identified, notably the use of outdated terms and a lack of representation for some communities. ChatGPT demonstrates significant potential in providing accurate information on HIV-related topics. However, while responses were often scientifically accurate, they sometimes lacked the socio-political context and inclusivity essential for effective health communication. This underlines the importance of aligning AI-driven platforms with contemporary health communication strategies and ensuring the balance of accuracy and inclusivity. [ABSTRACT FROM AUTHOR]

This document is a letter to the editor discussing a comparative study of two artificial intelligence tools, ChatGPT-4 and Google Lens, in the field of dermatology. The study aimed to evaluate the diagnostic capabilities of these tools compared to clinical diagnoses made by dermatologists. The study involved collecting 200 clinical photographs for each of 10 dermatological conditions, totaling 2,000 images. The results showed that ChatGPT-4 had an overall diagnostic accuracy of 70.15%, while Google Lens had an accuracy of 45.35%. The study suggests that integrating advanced AI technologies like ChatGPT-4 could enhance diagnostic processes in dermatology, particularly in resource-limited settings. However, further refinement and training may be needed for Google Lens to improve its diagnostic capabilities. [Extracted from the article]

The authors explore the intersection of AI and equity in education, presenting a workshop designed for marginalized youth in urban Mexico. This reflective essay stems from their participation in the International Society for Technology in Education’s AI and education course. The lead author, a language education researcher who emphasizes equity in her scholarship, crafted a presentation on AI’s everyday applications for marginalized Mexican youth. Collaborating organically, the co-authors positioned this project as the course’s final collective output, fostering a unique blend of expertise and community engagement. The lead author designed the presentation for an organization with which she has partnered for over a decade, an educational project that supports learning and life skills, rooted in Don Miguel Ruiz’s Four Agreements, for children who live in a community of unofficial housing on the edge of railroad tracks in Cuernavaca, Mexico. The project aimed to bridge the global application of AI to marginalized Mexicans, facilitating a two-hour workshop in Spring 2023. Two additional faculty, technology education researchers, joined the effort to promote computational literacy equitably through culturally relevant pedagogy. They highlight their diverse scholarly backgrounds, positioning themselves as individuals from the margins, and share their motivation for creating a cogent and engaging workshop for the youth. The lead author reports on the unexpectedly rich conversation that unfolded during the workshop, underscoring the potential for AI to be inclusive as society navigates its integration into education. [ABSTRACT FROM AUTHOR]

Background: Institutional review boards (IRBs) face delays in reviewing research proposals, underscoring the need for optimized standard operating procedures (SOPs). This study assesses the abilities of three artificial intelligence (AI) platforms to address IRB challenges and draft essential SOPs. Methods: An observational study was conducted using three AI platforms in 10 case studies reflecting IRB functions, focusing on creating SOPs. The accuracy of the AI outputs was assessed against good clinical practice (GCP) guidelines. Results: The AI tools identified GCP issues, offered guidance on GCP violations, detected conflicts of interest and SOP deficiencies, recognized vulnerable populations, and suggested expedited review criteria. They also drafted SOPs with some differences. Conclusion: AI platforms could aid IRB decision-making and improve review efficiency. However, human oversight remains critical for ensuring the accuracy of AI-generated solutions. [ABSTRACT FROM AUTHOR]

Background and Aims: Artificial intelligence (AI) chatbots like Conversational Generative Pre-trained Transformer (ChatGPT) have recently created much buzz, especially regarding patient education. Such informed patients understand and adhere to the management and get involved in shared decision making. The accuracy and understandability of the generated educational material are prime concerns. Thus, we compared ChatGPT with traditional patient information leaflets (PILs) about chronic pain medications. Methods: Patients' frequently asked questions were generated from PILs available on the official websites of the British Pain Society (BPS) and the Faculty of Pain Medicine. Eight blinded annexures were prepared for evaluation, consisting of traditional PILs from the BPS and AI-generated patient information materials structured similar to PILs by ChatGPT. The authors performed a comparative analysis to assess materials' readability, emotional tone, accuracy, actionability, and understandability. Readability was measured using Flesch Reading Ease (FRE), Gunning Fog Index (GFI), and Flesch-Kincaid Grade Level (FKGL). Sentiment analysis determined emotional tone. An expert panel evaluated accuracy and completeness. Actionability and understandability were assessed with the Patient Education Materials Assessment Tool. Results: Traditional PILs generally exhibited higher readability (P values < 0.05), with [mean (standard deviation)] FRE [62.25 (1.6) versus 48 (3.7)], GFI [11.85 (0.9) versus 13.65 (0.7)], and FKGL [8.33 (0.5) versus 10.23 (0.5)] but varied emotional tones, often negative, compared to more positive sentiments in ChatGPT-generated texts. Accuracy and completeness did not significantly differ between the two. Actionability and understandability scores were comparable. Conclusion: While AI chatbots offer efficient information delivery, ensuring accuracy and readability, patient-centeredness remains crucial. It is imperative to balance innovation with evidence-based practice. [ABSTRACT FROM AUTHOR]

This paper explores the potential applications of ChatGPT, a powerful Artificial Intelligence (AI) large language model (LLM) developed by OpenAI, for aviation education applications. The authors provide an overview of ChatGPT and its unique features, such as accessibility, conversational abilities, and personalized learning capabilities. The scalability of ChatGPT allows individualized and personalized instruction, a revolutionary aspect that can potentially enhance the student learning experience. This applied research employed an exploratory design to investigate ChatGPT's potential applications to enhance learning at varied levels of learning. The study investigated four research questions: (1) How can ChatGPT be used by students to support learning at each stage of Bloom's Taxonomy?; (2) How can teachers use ChatGPT to enhance student engagement in the learning process at each stage of Bloom's Taxonomy?; (3) What are the potential risks related to using ChatGPT as an educational resource?; and (4) What student guidelines or policies should be in place regarding the use of ChatGPT for learning? The authors provide specific recommendations for entering ChatGPT queries, along with practical application samples that have been tested using the platform. Generalized guidance and policy for the educational use of ChatGPT is also provided. The findings of this project prepare instructors to apply AI LLM resources to enhance aviation education and provide recommendations for its effective and ethical use by both faculty and students. Overall, this paper equips aviation educators with the necessary knowledge to leverage the power of ChatGPT to improve instructional outcomes. [ABSTRACT FROM AUTHOR]

In this series, we explore technology-related themes and topics. The series aims to discuss and demystify what may be new areas for some readers and to consider their relevance for English language teachers. This paper explores the potential applicability of ChatGPT—a generative, text-based artificial intelligence (AI) chatbot—to ELT. It offers insights and guidelines for using ChatGPT to develop receptive and productive skills. First, ChatGPT can help teachers generate input materials for listening and reading practices. Second, with ChatGPT, teachers can create individualized opportunities for students to practice their speaking and writing skills. We also note important caveats for teachers to consider when implementing ChatGPT as an instructional tool. By exploring its potential benefits and limitations, this paper contributes to the growing discourse on technology integration in ELT and offers practical recommendations for creating a productive learning environment using AI-driven language models like ChatGPT. [ABSTRACT FROM AUTHOR]

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As artificial intelligence (AI) becomes integral across industries, there is a growing opportunity to transform the generation of models for systems engineering. This research investigates the integration of OpenAI's GPT‐4 Turbo into CATIA Magic for Model‐Based Systems Engineering (MBSE), resulting in the creation of AI Systems Modeling Enhancer (AI‐SME). This study explores the comparison between models generated by AI, specifically OpenAI's GPT, and those crafted by human systems engineers. While recognizing challenges in AI‐generated models, this research underscores the potential of AI assistants to enhance the speed and accuracy of SysML model creation. Results demonstrate AI‐SME's successes in generating requirements, block definition diagrams, and internal block diagrams. Despite identified limitations such as redundancy and lack of cohesiveness in AI‐generated models, the study concludes that AI‐SME represents a notable advancement in AI‐assisted systems engineering. [ABSTRACT FROM AUTHOR]

The purpose of the investigation was to evaluate the utility of ChatGPT, a state‐of‐the‐art language model developed by Open AI, in the context of civil engineering education. To achieve this objective, 44 civil engineering students from a large state university in the United States were recruited and asked to respond to three questions pertaining to Construction Surveying and Geomatics. The students were then introduced to ChatGPT and provided with guidelines on how the platform could be utilized for educational purposes, including obtaining answers to questions like those presented to them earlier. The students were then given the opportunity to leverage ChatGPT to obtain responses to questions they had been presented with earlier and any other related queries of interest. Subsequently, the students were asked to provide written responses to the same questions they were presented with earlier, but without access to ChatGPT or its response, to assess any knowledge gains. The investigation also captured the student's acceptance and perceived usability based on their experience of using ChatGPT. The findings indicated that the student's written responses were more thorough, detailed, and informative after utilizing ChatGPT. The results also revealed that ChatGPT was largely well‐received by the students and they held a positive perception of the AI platform. The findings can inform efforts targeted at successfully integrating AI tools for civil engineering education. [ABSTRACT FROM AUTHOR]

The ability to work with data is an important skill for students enrolled in technical and professional communication programs, but students with limited mathematical and computer programming literacies might find it difficult to do basic data analysis or customize data visualizations. This article examines the extent to which ChatGPT can make data analysis and visualization more accessible for students with limited technical proficiency. The results suggest that although the tool is poised to have a substantial impact in helping students create effective data visualizations, its efficacy as a data analysis tool is more limited. [ABSTRACT FROM AUTHOR]

Seismic engineering, a critical field with significant societal implications, often presents communication challenges due to the complexity of its concepts. This paper explores the role of Artificial Intelligence (AI), specifically OpenAI’s ChatGPT, in bridging these communication gaps. The study delves into how AI can simplify intricate seismic engineering terminologies and concepts, fostering enhanced understanding among students, professionals, and policymakers. It also presents several intuitive case studies to demonstrate the practical application of ChatGPT in seismic engineering. Further, the study contemplates the potential implications of AI, highlighting its potential to transform decision-making processes, augment education, and increase public engagement. While acknowledging the promising future of AI in seismic engineering, the study also considers the inherent challenges and limitations, including data privacy and potential oversimplification of content. It advocates for the collaborative efforts of AI researchers and seismic experts in overcoming these obstacles and enhancing the utility of AI in the field. This exploration provides an insightful perspective on the future of seismic engineering, which could be closely intertwined with the evolution of AI.

Since its launch, ChatGPT has gained popularity and is widely used by university students. The tool has both positive and negative effects on students’ education. In other words, it contributes to either the building or destruction of education. This study was conducted to ascertain university students’ perceptions of whether ChatGPT is building or destroying their education. A cross-sectional research design was employed, in which data were collected from 200 randomly selected students from two Tanzanian Universities. The collected data was analysed using SPSS, in which frequencies, means, and standard deviation (SD) facilitated descriptions of various aspects of the study. Results showed that the majority of university students in the study area (around 81.5%) were using ChatGPT for a variety of reasons, including helping them prepare for exams, undertaking assignments, and writing research proposals and reports. Although there are negative impacts, such as reducing academic integrity and diminishing critical thinking, it was established that if ChatGPT is used cleverly, it stands to build rather than destroy education. Thus, this study recommends that universities should consider formulating and operationalizing respective policies and guidelines, as detailed further in the document. The study, therefore, delivers more clarity on the nexus between the use of ChatGPT and University education endeavours.

Background and Aims: Artificial intelligence (AI) chatbots like Conversational Generative Pre-trained Transformer (ChatGPT) have recently created much buzz, especially regarding patient education. Such informed patients understand and adhere to the management and get involved in shared decision making. The accuracy and understandability of the generated educational material are prime concerns. Thus, we compared ChatGPT with traditional patient information leaflets (PILs) about chronic pain medications. Methods: Patients' frequently asked questions were generated from PILs available on the official websites of the British Pain Society (BPS) and the Faculty of Pain Medicine. Eight blinded annexures were prepared for evaluation, consisting of traditional PILs from the BPS and AI-generated patient information materials structured similar to PILs by ChatGPT. The authors performed a comparative analysis to assess materials’ readability, emotional tone, accuracy, actionability, and understandability. Readability was measured using Flesch Reading Ease (FRE), Gunning Fog Index (GFI), and Flesch-Kincaid Grade Level (FKGL). Sentiment analysis determined emotional tone. An expert panel evaluated accuracy and completeness. Actionability and understandability were assessed with the Patient Education Materials Assessment Tool. Results: Traditional PILs generally exhibited higher readability (P values < 0.05), with [mean (standard deviation)] FRE [62.25 (1.6) versus 48 (3.7)], GFI [11.85 (0.9) versus 13.65 (0.7)], and FKGL [8.33 (0.5) versus 10.23 (0.5)] but varied emotional tones, often negative, compared to more positive sentiments in ChatGPT-generated texts. Accuracy and completeness did not significantly differ between the two. Actionability and understandability scores were comparable. Conclusion: While AI chatbots offer efficient information delivery, ensuring accuracy and readability, patient-centeredness remains crucial. It is imperative to balance innovation with evidence-based practice.

Historically, technological advancements have continuously transformed our lives in diverse ways. Recently, a sophisticated artificial intelligence (AI) based chatbot called ChatGPT has made similar breakthroughs, revolutionizing various industries and our everyday existence. Education is among the most significantly impacted areas, as ChatGPT opened new doors for both students and teachers. However, as a new phenomenon, it came with challenges within an unexplored grey area, introducing certain threats that persist even after more than a year into the ChatGPT journey. This systematic literature review seeks to analyse the available information concerning the opportunities and threats associated with the use of ChatGPT in academia, aiming to provide a comprehensive overview of the topic. The research suggests that the current version of ChatGPT can be beneficial for students, teachers, and researchers as a digital assistant capable of enhancing productivity through the automation of monotonous and repetitive tasks, provided that its limitations are effectively addressed. Ultimately, the paper provides valuable insights for future discussions, addressing important practical and theoretical considerations. As a conclusion, it is emphasized that while the current use of AI in academic domains presents both opportunities and challenges, the future inevitably involves this technology. Academic and business stakeholders must collaborate proactively worldwide to successfully break down the present myths surrounding ChatGPT, bidding farewell to outdated traditions and implementing essential new policies to guide proper human-AI collaboration.

ChatGPT, the most accessible generative artificial intelligence (AI) tool, offers considerable potential for veterinary medicine, yet a dedicated review of its specific applications is lacking. This review concisely synthesizes the latest research and practical applications of ChatGPT within the clinical, educational, and research domains of veterinary medicine. It intends to provide specific guidance and actionable examples of how generative AI can be directly utilized by veterinary professionals without a programming background. For practitioners, ChatGPT can extract patient data, generate progress notes, and potentially assist in diagnosing complex cases. Veterinary educators can create custom GPTs for student support, while students can utilize ChatGPT for exam preparation. ChatGPT can aid in academic writing tasks in research, but veterinary publishers have set specific requirements for authors to follow. Despite its transformative potential, careful use is essential to avoid pitfalls like hallucination. This review addresses ethical considerations, provides learning resources, and offers tangible examples to guide responsible implementation. A table of key takeaways was provided to summarize this review. By highlighting potential benefits and limitations, this review equips veterinarians, educators, and researchers to harness the power of ChatGPT effectively. [ABSTRACT FROM AUTHOR]

Background: This study evaluates the potential of ChatGPT and Google Bard as educational tools for patients in orthopedics, focusing on sports medicine and pediatric orthopedics. The aim is to compare the quality of responses provided by these natural language processing (NLP) models, addressing concerns about the potential dissemination of incorrect medical information. Methods: Ten ACL- and flat foot-related questions from a Google search were presented to ChatGPT-3.5 and Google Bard. Expert orthopedic surgeons rated the responses using the Global Quality Score (GQS). The study minimized bias by clearing chat history before each question, maintaining respondent anonymity and employing statistical analysis to compare response quality. Results: ChatGPT-3.5 and Google Bard yielded good-quality responses, with average scores of 4.1 ± 0.7 and 4 ± 0.78, respectively, for sports medicine. For pediatric orthopedics, Google Bard scored 3.5 ± 1, while the average score for responses generated by ChatGPT was 3.8 ± 0.83. In both cases, no statistically significant difference was found between the platforms (p = 0.6787, p = 0.3092). Despite ChatGPT's responses being considered more readable, both platforms showed promise for AI-driven patient education, with no reported misinformation. Conclusions: ChatGPT and Google Bard demonstrate significant potential as supplementary patient education resources in orthopedics. However, improvements are needed for increased reliability. The study underscores the evolving role of AI in orthopedics and calls for continued research to ensure a conscientious integration of AI in healthcare education. [ABSTRACT FROM AUTHOR]

There is much excitement about the opportunity to harness the power of large language models (LLMs) when building problem-solving assistants. However, the standard methodology of evaluating LLMs relies on static pairs of inputs and outputs; this is insufficient for making an informed decision about which LLMs are best to use in an interactive setting, and how that varies by setting. Static assessment therefore limits how we understand language model capabilities. We introduce CheckMate, an adaptable prototype platform for humans to interact with and evaluate LLMs. We conduct a study with CheckMate to evaluate three language models (InstructGPT, ChatGPT, and GPT-4) as assistants in proving undergraduate-level mathematics, with a mixed cohort of participants from undergraduate students to professors of mathematics. We release the resulting interaction and rating dataset, MathConverse. By analyzing MathConverse, we derive a taxonomy of human query behaviors and uncover that despite a generally positive correlation, there are notable instances of divergence between correctness and perceived helpfulness inLLMgenerations, among other findings. Further, we garner a more granular understanding of GPT-4 mathematical problemsolving through a series of case studies, contributed by experienced mathematicians. We conclude with actionable takeaways for ML practitioners and mathematicians: models that communicate uncertainty, respond well to user corrections, and can provide a concise rationale for their recommendations, may constitute better assistants. Humans should inspect LLM output carefully given their current shortcomings and potential for surprising fallibility. [ABSTRACT FROM AUTHOR]

The article discusses the impact of generative artificial intelligence, specifically ChatGPT, on the field of writing. The author explores the historical context of word processing and the anxieties surrounding new technologies. They argue that ChatGPT, with its ability to generate whole documents and genres of writing, represents a qualitative difference in writing technology. The author also raises concerns about the use of AI in writing, including issues of data mining, surveillance capitalism, environmental harm, and exploitative labor practices. They suggest that these technologies may lead to a post-alphabetic future where text loses its purpose as a format for human communication. [Extracted from the article]

Large language models (LLMs) have the ability to generate text by stringing together words from their extensive training data. The leading AI text generation tool built on LLMs, ChatGPT, has quickly grown a vast user base since its release, but the domains in which it is being heavily leveraged are not yet known to the public. To understand how generative AI is reshaping print media and the extent to which it is being implemented already, methods to distinguish human-generated text from that generated by AI are required. Since college students have been early adopters of ChatGPT, we sought to study the presence of generative AI in newspaper articles written by collegiate journalists. To achieve this objective, an accurate AI detection model is needed. Herein, we analyzed university newspaper articles from different universities to determine whether ChatGPT was used to write or edit the news articles. We developed a detection model using classical machine learning and used the model to detect AI usage in the news articles. The detection model showcased a 93% accuracy in the training data and had a similar performance in the test set, demonstrating effectiveness in AI detection above existing state-of-the-art detection tools. Finally, the model was applied to the task of searching for generative AI usage in 2023, and we found that ChatGPT was not used to revise articles to any appreciable measure to write university news articles at the schools we studied. [ABSTRACT FROM AUTHOR]

AI is already a big part of our lives. Artificial intelligence is all around us, and its use is widespread - from social networks, through educational technology, all the way to video games, innovative toys, better understanding of the natural languages, problem solving, automatic programming, because it is a complex of many disciplines which are interconnected. Artificial intelligence will inevitably change the world, as well as the institutions, the educational system and forcing educational institutions to change. Schools (primary, secondary and higher education institutions) have a key role in the use of artificial intelligence. The most used AI model is the so-called ChatGPT model. Lately, more and more people are talking about the danger of AI in studying, its abuse, but in the academic community they are also talking about its application, which has a positive effect on students. With this paper, our goal is to find out how much our students use AI, or more specifically the ChatGPT model. The students of the Faculty of Philology – in the field of teaching, "Goce Delchev" University - Shtip will be surveyed. We will use a survey questionnaire, in order to see if our students use AI, how much they use it and what they use it for the most. This research will be a base and will be of great benefit to professors in changing the way of teaching, the choice of students' activities, as well as changing the way of evaluation. [ABSTRACT FROM AUTHOR]