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In the rapid evolving landscape of artificial intelligence (AI), scientific publishing is experiencing significant transformations. AI tools, while offering unparalleled efficiencies in paper drafting and peer review, also introduce notable ethical concerns. This study delineates AI's dual role in scientific publishing: as a co-creator in the writing and review of scientific papers and as an ethical challenge. We first explore the potential of AI as an enhancer of efficiency, efficacy, and quality in creating scientific papers. A critical assessment follows, evaluating the risks vs. rewards for researchers, especially those early in their careers, emphasizing the need to maintain a balance between AI's capabilities and fostering independent reasoning and creativity. Subsequently, we delve into the ethical dilemmas of AI's involvement, particularly concerning originality, plagiarism, and preserving the genuine essence of scientific discourse. The evolving dynamics further highlight an overlooked aspect: the inadequate recognition of human reviewers in the academic community. With the increasing volume of scientific literature, tangible metrics and incentives for reviewers are proposed as essential to ensure a balanced academic environment. AI's incorporation in scientific publishing is promising yet comes with significant ethical and operational challenges. The role of human reviewers is accentuated, ensuring authenticity in an AI-influenced environment. As the scientific community treads the path of AI integration, a balanced symbiosis between AI's efficiency and human discernment is pivotal. Emphasizing human expertise, while exploit artificial intelligence responsibly, will determine the trajectory of an ethically sound and efficient AI-augmented future in scientific publishing. [ABSTRACT FROM AUTHOR]

AbstractOpenAI’s ChatGPT is an advanced large language model AI that has caused both excitement and concern in academia. TurnItIn and similar software programs are widely used in higher education to detect potential plagiarism. However, the extent to which such software can identify papers produced by ChatGPT remains unclear. The current study partially addressed this question by submitting five versions of short essays about criminological topics generated from ChatGPT to the TurnItIn software. Overall, the results indicated that TurnItIn adequately detected that the essays were not original works (mean percent plagiarized score = 31%). The analyses further illustrated that ChatGPT wrote at an exceedingly high level (mean Flesch-Kincaid Grade Level = 15.1) atypical of essays in higher education. Consequently, it appears that detection of AI-generated writing may be easier than initially assumed although the technology is bound to improve. Accordingly, possible strategies for approaching AI in higher education are proposed. [ABSTRACT FROM AUTHOR]

Background and Aims: ChatGPT represents the most popular and widely used generative artificial intelligence (AI) model that received significant attention in healthcare research. The aim of the current study was to assess the future trajectory of the needed research in this domain based on the recommendations of the top influential published records. Materials and Methods: A systematic search was conducted on Scopus, Web of Science, and Google Scholar (27–30 November 2023) to identify the top ten ChatGPT-related published records in healthcare across the three databases. Classification of the records as “top” denoting high influence in the field was based on citation counts. Results: A total of 22 unique records from 17 different journals representing 14 different publishers were identified as the top ChatGPT-related publications in healthcare subject. Based on the identified records’ recommendations, the following themes appeared as important areas to consider in future ChatGPT research in healthcare: improving healthcare education, improved efficiency of clinical processes (e.g., documentation), addressing ethical concerns (e.g., patient privacy and consent), supporting research tasks (e.g., data analysis, manuscript preparation), mitigating ChatGPT output biases, improving patient education and engagement, and developing standardized assessment protocols for ChatGPT utility in healthcare. Conclusions: The current review highlighted key areas to be prioritized in assessment of ChatGPT utility in healthcare. Interdisciplinary collaborations and standardizing methodologies are needed to synthesize robust evidence in these studies. Based on these recommendations and the promising potential of ChatGPT on healthcare, JMJ launched a call for papers for a special issue entitled “Evaluating Generative AI-Based Models in Healthcare”. [ABSTRACT FROM AUTHOR]

ChatGPT could allow students to plagiarize the content of their coursework with little risk of detection. Little is known about undergraduate willingness to use AI tools. In this study, psychology undergraduates (N = 160) from the United Kingdom, indicated their willingness to use, and history of using, ChatGPT to write university assignments. Almost a third (32%) indicated that they would use such tools; 15% indicated that they had used them already. Neither personality (conscientiousness, agreeableness, Machiavellianism, narcissism), academic performance, nor study skills self-efficacy could predict future use of AI tools. A novel Degree Apathy Scale was the only significant predictor. Willingness to use AI tools was greater when the risk of getting caught was low, and punishment was light, particularly for those high in degree apathy. Findings suggest that degree apathy is a key risk factor in academic misconduct. Wider research and pedagogical applications of degree apathy are discussed. • Thirty-two percent of students surveyed reported that they would use ChatGPT on future academic assignments. • Future use of AI tools was significantly predicted by a new Degree Apathy Scale. • Big Five and Dark Triad scores were not significant predictors, nor was previous academic performance. • Likelihood of cheating using ChatGPT was reduced with increasing risk of detection or severity of punishment. [ABSTRACT FROM AUTHOR]

In the landscape of academic research and citation practices, the emergence of ChatGPT, an artificial intelligence language model developed by OpenAI, represents a transformative leap forward. This paper delves into the multifaceted role of ChatGPT in revolutionizing scholarly endeavors beyond mere plagiarism detection. We explore how ChatGPT facilitates research collaboration, streamlines literature reviews, and assists in proper citation practices. By harnessing ChatGPT's contextual understanding and vast knowledge repository, social work researchers can unlock new avenues of creativity and efficiency in knowledge acquisition and dissemination. Moreover, this paper discusses the ethical considerations surrounding the integration of AI in academia and underscores the need for guidelines and education to ensure responsible usage. Ultimately, ChatGPT stands at the forefront of a technological revolution, empowering social work researchers to push the boundaries of knowledge acquisition and dissemination in unprecedented ways. [ABSTRACT FROM AUTHOR]

This discussion article examines the potential integration of Generative Artificial Intelligence (Gen-AI), including advanced Large-Language Models like the popular platform ChatGPT into subject English education. Following the significant public and academic attention in response to these technologies through 2023, this paper considers the transformative potential and challenges posed by Gen-AI in educational settings. Central to the discussion is the exploration of how English teachers can leverage Gen-AI to enrich student learning beyond the obvious domain of writing skills. Instead, the article foregrounds the necessity for students' understanding of Gen-AI as an essential component of digital literacy. While acknowledging ethical concerns such as plagiarism, equity, and access, the paper presents an argument for the productive use of Gen-AI in the classroom to augment reading, viewing, and interpretation lessons. Avoiding an evangelical or dystopian view of AI, this discussion piece explores the time-critical and urgent issue of how, when, and why English can engage with the technology. [ABSTRACT FROM AUTHOR]

The modern language generation model ChatGPT, created by Open Artificial Intelligence (AI), is recognised for its capacity to comprehend context and produce pertinent content. This model is built on the transformer architecture, which enables it to process massive volumes of data and produce text that is both cohesive and illuminating. Service is a crucial component everywhere as it provides the basis for establishing client rapport and offering aid and support. In healthcare, the application of ChatGPT for patient service support has been one of the most significant advances in recent years. ChatGPT can help overcome language obstacles and improve patient satisfaction by facilitating communication with healthcare personnel and understanding of care. It can assist in enhancing the entire patient experience by offering personalised information and support to patients and making it more straightforward for them to communicate with healthcare professionals. Its goal can be to expedite and streamline service by promptly and accurately responding to customers. Businesses of all sizes increasingly use ChatGPT since it allows them to provide 24/7 customer support without requiring human contact. This paper briefly discusses ChatGPT and the need for better services. Various perspectives on improving customer and patient services through ChatGPT are discussed. The article also discussed the major key enablers of ChatGPT for refining customer and patient assistance. Further, the paper identifies and discusses the critical application areas of ChatGPT for customer and patient service. With its ability to handle several requests simultaneously, respond quickly and accurately to client questions, and gain knowledge from every interaction, ChatGPT is revolutionising customer and patient service. Its accessibility and compatibility with various communication channels make it a desirable solution for businesses looking to improve support. As technology advances, ChatGPT is positioned to become an essential tool for businesses wishing to provide speedy and customised service. Although ChatGPT may give convincing solutions, the chance of providing accurate and updated information poses a problem for its usage in service jobs that need accurate and up-to-date information. In future, various services will become better and more efficient due to ChatGPT and AI. [ABSTRACT FROM AUTHOR]

This systematic review, adhering to the PRISMA framework, investigated the utilisation of ChatGPT, a language model developed by OpenAI, throughout Kindergarten to 12th grade (K‐12) educational settings. The review synthesises findings from 13 selected papers, encompassing the strengths, weaknesses, opportunities, and threats (SWOT) analysis of ChatGPT's implementation in K‐12 education, implications for various stakeholders, and practical recommendations. It is highlighted that ChatGPT could empower educators through curriculum, lesson planning, materials generation, differentiation, and optimising student learning experience through personalised learning. However, concerns regarding academic integrity and output quality must be addressed. The paper provides pedagogical recommendations and ethical considerations to utilise ChatGPT better. It contributes to the ongoing discourse about AI, particularly ChatGPT's role in K‐12 education, further inspiring future research and educational practices and facilitating the effective integration of ChatGPT into K‐12 educational settings where collaboration arises as a key role, in particular under the approach of co‐design for learning. [ABSTRACT FROM AUTHOR]

The use of artificial intelligence (AI) tools to aid in summarizing information in medicine and research has recently garnered a huge amount of interest. While tools such as ChatGPT produce convincing and naturally sounding output, the answers are sometimes incorrect. Some of these drawbacks, it is hoped, can be avoided by using programmes trained for a more specific scope. In this study we compared the performance of a new AI tool (the-literature.com) to the latest version OpenAI's ChatGPT (GPT-4) in summarizing topics that the authors have significantly contributed to. The AI tools were asked to produce a literature review on 7 topics. These were selected based on the research topics that the authors were intimately familiar with and have contributed to through their own publications. The output produced by the AI tools were graded on a 1–5 Likert scale for accuracy, comprehensiveness, and relevance by two fellowship trained consultant radiologists. The-literature.com produced 3 excellent summaries, 3 very poor summaries not relevant to the prompt, and one summary, which was relevant but did not include all relevant papers. All of the summaries produced by GPT-4 were relevant, but fewer relevant papers were identified. The average Likert rating was for the-literature was 2.88 and 3.86 for GPT-4. There was good agreement between the ratings of both radiologists (ICC = 0.883). Summaries produced by AI in its current state require careful human validation. GPT-4 on average provides higher quality summaries. Neither tool can reliably identify all relevant publications. • Literature review is a crucial, but labour intensive, part of research. • Artificial intelligence tools have the potential to realise significant time savings. • AI driven tools can in certain cases produce impressive literature reviews. • However, current AI literature review tools are too unreliable for routine use. [ABSTRACT FROM AUTHOR]

In an age where technology is evolving at a sometimes incomprehensibly rapid pace, the liver community must adjust and learn to embrace breakthroughs with an open mind in order to benefit from potentially transformative influences on our science and practice. The Journal of Hepatology has responded to novel developments in artificial intelligence (AI) by recruiting experts in the field to serve on the Editorial Board. Publications introducing novel AI technology are no longer uncommon in our journal and are among the most highly debated and possibly practice-changing papers across a broad range of scientific disciplines, united by their focus on liver disease. As AI is rapidly evolving, this expert paper will focus on educating our readership on large language models and their possible impact on our research practice and clinical outlook, outlining both challenges and opportunities in the field. "To improve is to change; to be perfect is to change often." ― Winston S. Churchill [ABSTRACT FROM AUTHOR]

Creativity has long been viewed as the bastion of human expression. With the advent of generative artificial intelligence (AI), there is an emerging notion of artificial creativity that contests traditional perspectives of artistic exploration. This paper explores the complex dynamics of this evolution by examining how generative AI intertwines with and transforms the art world. It presents a comprehensive analysis of the challenges posed by generative AI in art, from questions of authenticity and intellectual property to ethical dilemmas and impacts on conventional art practices. Simultaneously, it investigates the revolutionary opportunities generative AI offers, including the democratization of art creation, the expansion of creative boundaries, and the development of new collaborative and economic models. The paper posits that the integration of generative AI in art is not just a technological advancement but a significant cultural shift, which necessitates a reevaluation of our understanding of art and the artist. It concludes with a forward-looking perspective, advocating for a collaborative approach to harness the potential of this technology in enriching human creativity and ensuring the vibrant evolution of the art world in the era of AI-driven generation. [ABSTRACT FROM AUTHOR]

With the introduction of ChatGPT, the public's perception of AI-generated content has begun to reshape. Artificial intelligence has significantly reduced the barrier to entry for non-professionals in creative endeavors, enhancing the efficiency of content creation. Recent advancements have seen significant improvements in the quality of symbolic music generation, which is enabled by the use of modern generative algorithms to extract patterns implicit in a piece of music based on rule constraints or a musical corpus. Nevertheless, existing literature reviews tend to present a conventional and conservative perspective on future development trajectories, with a notable absence of thorough benchmarking of generative models. This paper provides a survey and analysis of recent intelligent music generation techniques, outlining their respective characteristics and discussing existing methods for evaluation. Additionally, the paper compares the different characteristics of music generation techniques in the East and West as well as analysing the field's development prospects. [ABSTRACT FROM AUTHOR]

The use of artificial intelligence in academia is a hot topic in the education field. ChatGPT is an AI tool that offers a range of benefits, including increased student engagement, collaboration, and accessibility. However, is also raises concerns regarding academic honesty and plagiarism. This paper examines the opportunities and challenges of using ChatGPT in higher education, and discusses the potential risks and rewards of these tools. The paper also considers the difficulties of detecting and preventing academic dishonesty, and suggests strategies that universities can adopt to ensure ethical and responsible use of these tools. These strategies include developing policies and procedures, providing training and support, and using various methods to detect and prevent cheating. The paper concludes that while the use of AI in higher education presents both opportunities and challenges, universities can effectively address these concerns by taking a proactive and ethical approach to the use of these tools. [ABSTRACT FROM AUTHOR]

Generative Artificial Intelligence (AI), especially machine learning models that autonomously generate human-like content, has recently attracted significant attention in the education sector. This paper explores the potential of generative AI, including tools like ChatGPT, to shift from traditional outcome-oriented educational practices to a more balanced approach that values both the learning process and its outcomes. Traditionally, education has emphasized achieving predefined results, but the advent of generative AI tools, which enable students to easily produce tangible results, calls for a reevaluation of these practices. This shift suggests a need for a broader focus that encompasses the entire learning process leading to the final product, thereby promoting an educational practice that equally emphasizes both the journey and the destination of learning. Recognizing that the implementation of such practices, facilitated by generative AI, still requires exploration, this paper proposes a solution that integrates the experiential learning cycle and learning portfolio. This approach is designed to demonstrate the realization of process-outcome-balanced educational practices through the use of a pedagogical AI agent. [ABSTRACT FROM AUTHOR]

This paper examines the potential impact of AI-based language models on education, with a specific focus on the ChatGPT model developed by OpenAI. The study begins by providing an overview of the current state of AI in education, including the challenges and opportunities presented by these models. It then delves into an analysis of ChatGPT, including its capabilities, strengths and limitations. The paper also conducts a thorough analysis of potential implications and offers suggestions for assessment design to prevent students from utilising AI-based language models in educational environments. Finally, the paper concludes with a set of recommendations for assessment design, considering the specific characteristics of ChatGPT and the potential impact of AI-based language models on tourism education. [ABSTRACT FROM AUTHOR]

As artificial intelligence (AI) becomes increasingly integrated into our lives, the need for new norms is urgent. However, AI evolves at a much faster pace than the characteristic time of norm formation, posing an unprecedented challenge to our societies. This paper examines possible criticalities of the processes of norm formation surrounding AI. It focuses on how new norms can be established, rather than on what these norms should be. It distinguishes different scenarios based on the centralization or decentralization of the norm formation process, analysing the cases where new norms are shaped by formal authorities or informal institutions, or emerge spontaneously in a bottom-up fashion. On the latter point, the paper reports a conversation with ChatGPT in which the LLM discusses some of the emerging norms it has observed. Far from seeking exhaustiveness, this article aims to offer readers interpretive tools to frame society's response to the growing pervasiveness of AI. An outlook on how AI could influence the formation of future social norms emphasizes the importance for open societies to anchor their formal deliberation process in an open, inclusive and transparent public discourse. This article is part of the theme issue 'Social norm change: drivers and consequences'. [ABSTRACT FROM AUTHOR]

This review explores the transformative integration of artificial intelligence (AI) and healthcare through conversational AI leveraging Natural Language Processing (NLP). Focusing on Large Language Models (LLMs), this paper navigates through various sections, commencing with an overview of AI's significance in healthcare and the role of conversational AI. It delves into fundamental NLP techniques, emphasizing their facilitation of seamless healthcare conversations. Examining the evolution of LLMs within NLP frameworks, the paper discusses key models used in healthcare, exploring their advantages and implementation challenges. Practical applications in healthcare conversations, from patient-centric utilities like diagnosis and treatment suggestions to healthcare provider support systems, are detailed. Ethical and legal considerations, including patient privacy, ethical implications, and regulatory compliance, are addressed. The review concludes by spotlighting current challenges, envisaging future trends, and highlighting the transformative potential of LLMs and NLP in reshaping healthcare interactions. [ABSTRACT FROM AUTHOR]

This paper delves into the intricate relationship between Artificial Intelligence (AI) and the art ecosystem, emphasizing the need for a decolonizing approach in the face of AI's growing influence. It argues that the development of AI is not just a technological leap but also a significant cultural and societal moment, akin to the advent of moving images that Walter Benjamin famously analyzed. The paper examines how AI, particularly in its current oligarchical and corporate-driven form, perpetuates and magnifies the existing social inequalities, thereby necessitating a critical and radical rethinking of its role in society and the arts. At the heart of the discussion is the concept of AI as a broad term encompassing various forms of machine intelligence, from natural language processing to computer vision. The paper criticizes the dominant anthropocentric view of intelligence and creativity, proposing a more inclusive approach that considers the diverse forms of intelligence present in other species and potentially in AI itself. It underscores the role of AI in shaping the art ecosystem, not just in the creative process but also in gatekeeping and decision-making. The paper proposes a framework for decolonizing AI in the art ecosystem, focusing on four key tasks: recognizing access as a form of power, understanding and addressing biases inherent in AI, assessing the impact of AI on marginalized communities, and challenging dominant narratives and epistemologies to create space for alternative voices and perspectives. It emphasizes the need for artists and the art community to engage actively with AI, shaping its development towards more equitable and just outcomes. In conclusion, the paper calls for a radical reimagination of AI's role in society and the arts, advocating for a future where AI is not just about technological advancement but also about fostering a more inclusive, equitable, and creatively diverse world. It invites artists, thinkers, and innovators to join in this journey of reimagining and reshaping the future of AI and the art ecosystem. [ABSTRACT FROM AUTHOR]

In the era of generative AI and specifically large language models (LLMs), exemplified by ChatGPT, the intersection of artificial intelligence and human reasoning has become a focal point of global attention. Unlike conventional search engines, LLMs go beyond mere information retrieval, entering into the realm of discourse culture. Their outputs mimic well-considered, independent opinions or statements of facts, presenting a pretense of wisdom. This paper explores the potential transformative impact of LLMs on democratic societies. It delves into the concerns regarding the difficulty in distinguishing ChatGPT-generated texts from human output. The discussion emphasizes the essence of authorship, rooted in the unique human capacity for reason—a quality indispensable for democratic discourse and successful collaboration within free societies. Highlighting the potential threats to democracy, this paper presents three arguments: the Substitution argument, the Authenticity argument, and the Facts argument. These arguments highlight the potential risks that are associated with an overreliance on LLMs. The central thesis posits that widespread deployment of LLMs may adversely affect the fabric of a democracy if not comprehended and addressed proactively and properly. In proposing a solution, we advocate for an emphasis on education as a means to mitigate risks. We suggest cultivating thinking skills in children, fostering coherent thought formulation, and distinguishing between machine-generated output and genuine, i.e., human, reasoning. The focus should be on the responsible development and usage of LLMs, with the goal of augmenting human capacities in thinking, deliberating and decision-making rather than substituting them. [ABSTRACT FROM AUTHOR]

This paper aims to determine whether there is a case for promoting a new benchmark for forecasting practice via the innovative application of generative artificial intelligence (Gen-AI) for predicting the future. Today, forecasts can be generated via Gen-AI models without the need for an in-depth understanding of forecasting theory, practice, or coding. Therefore, using three datasets, we present a comparative analysis of forecasts from Gen-AI models against forecasts from seven univariate and automated models from the forecast package in R, covering both parametric and non-parametric forecasting techniques. In some cases, we find statistically significant evidence to conclude that forecasts from Gen-AI models can outperform forecasts from popular benchmarks like seasonal ARIMA, seasonal naïve, exponential smoothing, and Theta forecasts (to name a few). Our findings also indicate that the accuracy of forecasts from Gen-AI models can vary not only based on the underlying data structure but also on the quality of prompt engineering (thus highlighting the continued importance of forecasting education), with the forecast accuracy appearing to improve at longer horizons. Therefore, we find some evidence towards promoting forecasts from Gen-AI models as benchmarks in future forecasting practice. However, at present, users are cautioned against reliability issues and Gen-AI being a black box in some cases. [ABSTRACT FROM AUTHOR]

The field of dermatology is experiencing the rapid deployment of artificial intelligence (AI), from mobile applications (apps) for skin cancer detection to large language models like ChatGPT that can answer generalist or specialist questions about skin diagnoses. With these new applications, ethical concerns have emerged. In this scoping review, we aimed to identify the applications of AI to the field of dermatology and to understand their ethical implications. We used a multifaceted search approach, searching PubMed, MEDLINE, Cochrane Library and Google Scholar for primary literature, following the PRISMA Extension for Scoping Reviews guidance. Our advanced query included terms related to dermatology, AI and ethical considerations. Our search yielded 202 papers. After initial screening, 68 studies were included. Thirty-two were related to clinical image analysis and raised ethical concerns for misdiagnosis, data security, privacy violations and replacement of dermatologist jobs. Seventeen discussed limited skin of colour representation in datasets leading to potential misdiagnosis in the general population. Nine articles about teledermatology raised ethical concerns, including the exacerbation of health disparities, lack of standardized regulations, informed consent for AI use and privacy challenges. Seven addressed inaccuracies in the responses of large language models. Seven examined attitudes toward and trust in AI, with most patients requesting supplemental assessment by a physician to ensure reliability and accountability. Benefits of AI integration into clinical practice include increased patient access, improved clinical decision-making, efficiency and many others. However, safeguards must be put in place to ensure the ethical application of AI. [ABSTRACT FROM AUTHOR]

The custom GPT is the latest powerful feature added to ChatGPT. Non-programmers can create and share their own GPTs ("chat bots"), allowing Health Professions Educators to apply the capabilities of ChatGPT to create administrative assistants, online tutors, virtual patients, and more, to support their clinical and non-clinical teaching environments. To achieve this correctly, however, requires some skills, and this 12-Tips paper provides those: we explain how to construct data sources, build relevant GPTs, and apply some basic security. [ABSTRACT FROM AUTHOR]

The recent popularity of ChatGPT and artificial intelligence chatbots presents both challenges and opportunities for incorporating this modern technology in the classroom. This paper introduces an activity that uses ChatGPT to help students practice their role playing sales skills. The benefits of using this AI chatbot for role play training include allowing students to practice when it's convenient and have the ability to react to a chatbot taking on personas of different buyer types. Survey results demonstrate the effectiveness of this training method for both role play training and general familiarity with ChatGPT. [ABSTRACT FROM AUTHOR]

This paper examines the role of Generative AI (GenAI) and Large Language Models (LLMs) in penetration testing exploring the benefits, challenges, and risks associated with cyber security applications. Through the use of generative artificial intelligence, penetration testing becomes more creative, test environments are customised, and continuous learning and adaptation is achieved. We examined how GenAI (ChatGPT 3.5) helps penetration testers with options and suggestions during the five stages of penetration testing. The effectiveness of the GenAI tool was tested using a publicly available vulnerable machine from VulnHub. It was amazing how quickly they responded at each stage and provided better pentesting report. In this article, we discuss potential risks, unintended consequences, and uncontrolled AI development associated with pentesting. [ABSTRACT FROM AUTHOR]

Background: Introducing new technologies in education sparks debates, disrupting traditional practices, and requiring teacher adaptation. ChatGPT is an example. Research explores its benefits and concerns in education, with recommendations for classroom use. Nevertheless, limited evidence supports ChatGPT as a tool for supporting English as a Foreign Language (EFL) students' research competency. Moreover, while the literature primarily focuses on the perspectives of scholars and teachers, it is essential to incorporate students' viewpoints in order to maximize the potential of this technology. Objectives: The present study investigated EFL undergraduates' perceptions and practices of ChatGPT as a tool for promoting their research competency. Additionally, the study examined the potential influence of metacognitive awareness (MA) levels in this context. Methods: The study utilized a mixed‐method research design, collecting quantitative and qualitative data from 27 EFL undergraduates (12 with low MA and 15 with high MA) over one semester. Data sources included a self‐report questionnaire, self‐study log, and semi‐structured interviews. Results and conclusions: Quantitative analysis showed significant differences between low and high MA groups in their perceptions of ChatGPT (U = 37.500, Z = 2.570). Regression analysis revealed a positive correlation between MA scores and students' perceptions and practices of ChatGPT. Qualitative analysis revealed diverse perceptions and practices of ChatGPT between the high MA and low MA groups, showcasing behaviours ranging from replication to using ChatGPT as a thought‐stimulating and supportive tool, accessing supplementary information, and seeking guidance. Key factors for effective ChatGPT use included prompt formulation, systematic thinking, self‐regulation strategies, and trust in AI. Lay Description: What is currently known about this topic: Research competency and metacognitive awareness are important for EFL undergraduates.Technology has been explored for promoting research competency.ChatGPT is used as a learning tool in EFL instruction contexts. What does this paper add: It provides a deeper understanding of the practical application of AI tools like ChatGPT for developing research competency among EFL students.It enhances understanding of metacognition's role in successful learning in digital environments by exploring MA's impact on using ChatGPT for research purposes. Implications for practice/policy: Provide explicit instructions and guidelines for EFL students to effectively use ChatGPT for research competency, emphasizing clear prompt design and fostering responsible use through critical thinking and awareness of biases and limitations.Enhance EFL students' metacognitive awareness through scaffolding, explicit instruction, and activities.Implement assessments and monitoring mechanisms to track metacognitive development and guide instructional interventions.Offer professional development opportunities for EFL teachers to enhance their understanding and skills in integrating AI tools into research instruction and other EFL aspects. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is influencing different aspects of human life. An AI‐powered technology, which has been recently released, is ChatGPT. It is a cutting‐edge technology that influences second/foreign language (L2) education. Although there is increasing research on the benefits and misfits of this chatbot in different disciplines, L2 education lacks a thorough investigation. To fill this lacuna, this phenomenographic study examined the perceptions of research‐active English as a Foreign Language (EFL) teachers regarding the potentials and pitfalls of ChatGPT for L2 learning, teaching, assessment, and research. To this end, a semistructured interview was held with 30 Iranian EFL teachers with varying educational backgrounds and AI integration experiences. The results of content and thematic analysis indicated that ChatGPT is a double‐edged sword that can both benefit and hurt these areas of L2 education. The most notable potentials were augmenting learner autonomy, providing personalized learning, reducing teachers’ teaching workload, designing assessment rubrics, and summarizing lengthy papers and theses to save L2 researchers’ time and energy. Concerning pitfalls, it was reported that ChatGPT might kill creativity and academic integrity, encourage cheating in online exams, spread fake and misinformation into the world of research, and cherish high‐tech plagiarism. Some practical suggestions are made to empower L2 educators and researchers to survive in the world of AI. [ABSTRACT FROM AUTHOR]

In this paper, we employ the language ontologies framework to artificial intelligence (specifically, OpenAI's ChatGPT) to investigate the 'ethnographic encounter' between human and non-human language users. Our focus is on the exchange and interplay between human language users and non-human artificial language generators in the production of written text. We analyse how such programs transform our understanding of what language is or might be; their practices to create language are unfamiliar, and yet they make sense to human interlocutors. Drawing from, and building on, the language ontologies framework, we discuss the practices involved in such encounters and suggest the need for an updated 'toolkit' in our understanding of language to account for transhuman interactions. • Language is many things, depending on how it is practiced and performed. • Ontologies allow us to approach language(s)/languaging as an anthropologist approaches an 'ethnographic encounter'. • The interaction between humans and artificial intelligence (AI) is an ethnographic encounter used to explore transhuman language ontologies. • The ways in which AI generates language is responsive to human linguistic behaviour; however, the way AI creates language is unique. • Language patterns, or wordings , constitute a significant element of the languaging process for ChatGPT. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to examine the opportunities and challenges of using ChatGPT in higher education. Furthermore, it is also discuss the potential risks and plunders of these tools. Design/methodology/approach: The paper discuss the use of artificial intelligence (AI) in academia and explores the opportunities and challenges of using ChatGPT in higher education. It also highlights the difficulties of detecting and preventing academic dishonesty and suggests strategies that universities can adopt to ensure ethical and useful use of these tools. Findings: The paper concludes that while the use of AI tools, ChatGPT in higher education presents both opportunities and challenges. The universities can effectively address these concerns by taking a proactive and ethical approach to the use of these tools. This paper further suggests that universities should develop policies and procedures, provide training and support, to detect and prevent cheating intentions. Originality/value: The paper provides insights into the opportunities and challenges of using ChatGPT in higher education, as well as strategies for addressing concerns related to academic dishonesty. The paper further adds importance to the discussion on the ethical and responsible use of AI tools in higher education. [ABSTRACT FROM AUTHOR]

This paper explores the transformative potential of Large Language Models Artificial Intelligence (LLM AI) in educational contexts, particularly focusing on the innovative practice of prompt engineering. Prompt engineering, characterized by three essential components of content knowledge, critical thinking, and iterative design, emerges as a key mechanism to access the transformative capabilities of LLM AI in the learning process. This paper charts the evolving trajectory of LLM AI as a tool poised to reshape educational practices and assumptions. In particular, this paper breaks down the potential of prompt engineering practices to enhance learning by fostering personalized, engaging, and equitable educational experiences. The paper underscores how the natural language capabilities of LLM AI tools can help students and educators transition from passive recipients to active co-creators of their learning experiences. Critical thinking skills, particularly information literacy, media literacy, and digital citizenship, are identified as crucial for using LLM AI tools effectively and responsibly. Looking forward, the paper advocates for continued research to validate the benefits of prompt engineering practices across diverse learning contexts while simultaneously promoting potential defects, biases, and ethical concerns related to LLM AI use in education. It calls upon practitioners to explore and train educational stakeholders in best practices around prompt engineering for LLM AI, fostering progress towards a more engaging and equitable educational future. [ABSTRACT FROM AUTHOR]

In recent years, the fusion of Artificial Intelligence (AI) with traditional sectors has catalyzed a paradigm shift that extends beyond technological advancements and reaches into the core of human learning and development. One such domain undergoing significant transformation is mental health education. This short conceptual paper seeks to examine the intricate relationship between AI and education in the context of mental health studies, shedding light on the challenges, opportunities, and ethical considerations that arise as teaching evolves in the Age of AI. This paper is not intended to serve as THE definitive solution to inquiries regarding the integration of AI/ChatGPT in mental health education. Rather, its purpose is to provide AN approach to contemplating this matter and to initiate further discussions within mental health-related fields about the utilization of AI and ChatGPT in education, given the persistent prominence of AI. [ABSTRACT FROM AUTHOR]

Educational technology innovations leveraging large language models (LLMs) have shown the potential to automate the laborious process of generating and analysing textual content. While various innovations have been developed to automate a range of educational tasks (eg, question generation, feedback provision, and essay grading), there are concerns regarding the practicality and ethicality of these innovations. Such concerns may hinder future research and the adoption of LLMs‐based innovations in authentic educational contexts. To address this, we conducted a systematic scoping review of 118 peer‐reviewed papers published since 2017 to pinpoint the current state of research on using LLMs to automate and support educational tasks. The findings revealed 53 use cases for LLMs in automating education tasks, categorised into nine main categories: profiling/labelling, detection, grading, teaching support, prediction, knowledge representation, feedback, content generation, and recommendation. Additionally, we also identified several practical and ethical challenges, including low technological readiness, lack of replicability and transparency and insufficient privacy and beneficence considerations. The findings were summarised into three recommendations for future studies, including updating existing innovations with state‐of‐the‐art models (eg, GPT‐3/4), embracing the initiative of open‐sourcing models/systems, and adopting a human‐centred approach throughout the developmental process. As the intersection of AI and education is continuously evolving, the findings of this study can serve as an essential reference point for researchers, allowing them to leverage the strengths, learn from the limitations, and uncover potential research opportunities enabled by ChatGPT and other generative AI models. Practitioner notesWhat is currently known about this topic Generating and analysing text‐based content are time‐consuming and laborious tasks.Large language models are capable of efficiently analysing an unprecedented amount of textual content and completing complex natural language processing and generation tasks.Large language models have been increasingly used to develop educational technologies that aim to automate the generation and analysis of textual content, such as automated question generation and essay scoring.What this paper adds A comprehensive list of different educational tasks that could potentially benefit from LLMs‐based innovations through automation.A structured assessment of the practicality and ethicality of existing LLMs‐based innovations from seven important aspects using established frameworks.Three recommendations that could potentially support future studies to develop LLMs‐based innovations that are practical and ethical to implement in authentic educational contexts.Implications for practice and/or policy Updating existing innovations with state‐of‐the‐art models may further reduce the amount of manual effort required for adapting existing models to different educational tasks.The reporting standards of empirical research that aims to develop educational technologies using large language models need to be improved.Adopting a human‐centred approach throughout the developmental process could contribute to resolving the practical and ethical challenges of large language models in education. [ABSTRACT FROM AUTHOR]

Aim Methods Results Conclusions ChatGPT's role in medical writing is a topic of discussion. I experimented whether ChatGPT almost automatically generates Correspondence or Letter addressed to a “translated” article, and thereby wish to arouse discussion regarding ChatGPT use in medical writing.I input an English article of mine into ChatGPT, tasking it with generating an English Disagreement Letter (Letter 1). Next, I tasked ChatGPT with translating the manuscript addressed to from English‐French‐Spanish‐German. Then, I once again tasked ChatGPT with generating an English Disagreement Letter addressed to a German manuscript (triplicate translated manuscript) (Letter 2).Letters 1 and 2 are readable and reasonable, shooting the point that the author (myself) felt as the weakness of the article. Letters addressed to French (single translation) and to Spanish (double translation) and longer Letters (corresponding to Letters 1 and 2) are also readable, and thus stand.Solely based on this experiment, one may be able to write a letter even without understanding the meaning of the paper being addressed, let alone the language of the paper. Although this humble experiment does not conclude anything, I plea for a comprehensive discussion on the implications of these findings. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) is not a new technology, as many industries have been using it for years. Recently, it has become a more available asset to university students and faculty. Due to this interest, guidelines and practices are being established in universities and academic libraries on how best to use AI. This paper covers some of the challenges currently facing academia when it comes to AI and the various ways AI can benefit academic libraries in teaching, collection services, and aspects of accessibility. [ABSTRACT FROM AUTHOR]

This study aimed to comprehensively evaluate the current utilization and future potential of ChatGPT, an AI-based chat model, in the field of radiology. The primary focus is on its role in enhancing decision-making processes, optimizing workflow efficiency, and fostering interdisciplinary collaboration and teaching within healthcare. A systematic search was conducted in PubMed, EMBASE and Web of Science databases. Key aspects, such as its impact on complex decision-making, workflow enhancement and collaboration, were assessed. Limitations and challenges associated with ChatGPT implementation were also examined. Overall, six studies met the inclusion criteria and were included in our analysis. All studies were prospective in nature. A total of 551 chatGPT (version 3.0 to 4.0) assessment events were included in our analysis. Considering the generation of academic papers, ChatGPT was found to output data inaccuracies 80% of the time. When ChatGPT was asked questions regarding common interventional radiology procedures, it contained entirely incorrect information 45% of the time. ChatGPT was seen to better answer US board-style questions when lower order thinking was required (P = 0.002). Improvements were seen between chatGPT 3.5 and 4.0 in regard to imaging questions with accuracy rates of 61 versus 85%(P = 0.009). ChatGPT was observed to have an average translational ability score of 4.27/5 on the Likert scale regarding CT and MRI findings. ChatGPT demonstrates substantial potential to augment decision-making and optimizing workflow. While ChatGPT’s promise is evident, thorough evaluation and validation are imperative before widespread adoption in the field of radiology. [ABSTRACT FROM AUTHOR]

The introduction of ChatGPT 3.5 in November 2022 ignited a sensation in the academic community, leaving many astounded by its capabilities. This new release more closely emulates human responses than its predecessors. Among its remarkable capabilities, it can answer questions, catalog items in MARC21, recommend reading lists, and make suggestions on a wide array of topics. To assess ChatGPT’s efficacy in aiding library users, the authors of this paper conducted an experiment comparing ChatGPT’s performance with that of librarians in answering reference questions. Thirty questions were randomly selected from the transaction log of the reference inquiries between June 1, 2023 to July 31, 2023 at the Rider University Libraries. These queries constituted 34% of the total user questions during this two-month period. The authors compared the answers by ChatGPT and those by reference librarians for their accuracy, relevance, and friendliness. The findings indicate that reference librarians markedly outperformed their robotic counterpart. An evident issue arises from ChatGPT’s deficiency in understanding local policies and practices. This consequently hinders its ability to provide satisfactory answers in those areas. OpenAI posits that ChatGPT’s proficiency can be enhanced through targeted fine-tuning using locally specific information. At the moment, ChatGPT remains a great tool for librarians. [ABSTRACT FROM AUTHOR]

Purpose: The usage of Chatbots as a kind of Artificial Intelligence in medicine is getting to increase in recent years. UpToDate® is another well-known search tool established on evidence-based knowledge and is used daily by doctors worldwide. In this study, we aimed to investigate the usefulness and reliability of ChatGPT compared to UpToDate in Otorhinolaryngology and Head and Neck Surgery (ORL–HNS). Materials and methods: ChatGPT-3.5 and UpToDate were interrogated for the management of 25 common clinical case scenarios (13 males/12 females) recruited from literature considering the daily observation at the Department of Otorhinolaryngology of Ege University Faculty of Medicine. Scientific references for the management were requested for each clinical case. The accuracy of the references in the ChatGPT answers was assessed on a 0–2 scale and the usefulness of the ChatGPT and UpToDate answers was assessed with 1–3 scores by reviewers. UpToDate and ChatGPT 3.5 responses were compared. Results: ChatGPT did not give references in some questions in contrast to UpToDate. Information on the ChatGPT was limited to 2021. UpToDate supported the paper with subheadings, tables, figures, and algorithms. The mean accuracy score of references in ChatGPT answers was 0.25–weak/unrelated. The median (Q1–Q3) was 1.00 (1.25–2.00) for ChatGPT and 2.63 (2.75–3.00) for UpToDate, the difference was statistically significant (p < 0.001). UpToDate was observed more useful and reliable than ChatGPT. Conclusions: ChatGPT has the potential to support the physicians to find out the information but our results suggest that ChatGPT needs to be improved to increase the usefulness and reliability of medical evidence-based knowledge. [ABSTRACT FROM AUTHOR]

Introduction: Chatbot generative pre-trained transformer (ChatGPT) is a new artificial intelligence-powered language model of chatbot able to help otolaryngologists in practice and research. We investigated the accuracy of ChatGPT-3.5 and -4 in the referencing of manuscripts published in otolaryngology. Methods: ChatGPT-3.5 and ChatGPT-4 were interrogated for providing references of the top-30 most cited papers in otolaryngology in the past 40 years including clinical guidelines and key studies that changed the practice. The responses were regenerated three times to assess the accuracy and stability of ChatGPT. ChatGPT-3.5 and ChatGPT-4 were compared for accuracy of reference and potential mistakes. Results: The accuracy of ChatGPT-3.5 and ChatGPT-4.0 ranged from 47% to 60%, and 73% to 87%, respectively (p < 0.005). ChatGPT-3.5 provided 19 inaccurate references and invented 2 references throughout the regenerated questions. ChatGPT-4.0 provided 13 inaccurate references, while it proposed only one invented reference. The stability of responses throughout regenerated answers was mild (k = 0.238) and moderate (k = 0.408) for ChatGPT-3.5 and 4.0, respectively. Conclusions: ChatGPT-4.0 reported higher accuracy than the free-access version (3.5). False references were detected in both 3.5 and 4.0 versions. Practitioners need to be careful regarding the use of ChatGPT in the reach of some key reference when writing a report. [ABSTRACT FROM AUTHOR]

Background: The increasing prevalence of Artificial Intelligence (AI) language models, exemplified by ChatGPT, has sparked inquiries into their influence on creative writing skills in educational contexts. This study aims to quantitatively investigate whether ChatGPT's use negatively affects university students' creative writing abilities, focusing on originality, content presentation, accuracy, and elaboration in essays. The research adopts an experimental approach to shed light on this concern. Objective: This study aims to quantitatively investigate whether the utilization of ChatGPT, an AI chatbot, adversely affects specific dimensions of creative writing skills among university students, with an emphasis on originality, content presentation, accuracy, and elaboration. Method: The experimental study involves 600 students from 10 universities, divided into a control and an experimental group (EGp). The EGp incorporates ChatGPT in their creative writing process as an intervention. The study evaluates originality, content presentation, accuracy, and elaboration, utilizing the Wilcoxon Signed‐Rank Test for analysis. Results and Conclusion: The findings reveal a detrimental association between ChatGPT use and university students' creative writing abilities. Analysing both machine‐based and human‐based assessments substantiates earlier qualitative observations regarding ChatGPT's adverse impact on creative writing. This study highlights the necessity of approaching AI integration, particularly in creative writing disciplines, with caution. While AI tools have merits, their integration should be thoughtful, considering the potential drawbacks. These insights inform future research and educational practices, guiding the effective incorporation of AI while nurturing students' writing skills. Lay Description: What is already known about this topic: ChatGPT poses an ethical dilemma regarding its use in the field of academiaQualitative claims and opinions have been raised in prior studies regarding its use in the creative writing processPrior studies have both supported and opposed its use but with very limited quantitative approaches while most of the opinions remain qualitativeSome prior studies opine in support of ChatGPT's ability as an authorSeveral factors measuring creativity has been identified by previous studies but a constructive approach in the light of advanced Artificial Intelligence (AI) based chatbots like ChatGPT is missing in such literature What this paper adds: An experimental approach to provide a valid quantitative proof of the qualitative claims over ChatGPT's detrimental effect towards creativity in writing, which was absent in prior studiesA multifactor‐based formula to measure creativity in a quantitative formA quantitative view of the factors that are affected in either a positive way or a negative way in a user by ChatGPT, providing a holistic picture to determine its extent of useA statistical and theoretical understanding over an unexplored topic like creative writing in the light of ChatGPTA quantitative proof why ChatGPT should not be considered as an author Implications for practice and/or policy: Educators may implement changes in assigning tasks to students compared to their earlier practices, based on the identified factors that are being affected negatively, to ensure ChatGPT does not hinder a student's creativity at a greater extentThe extent of using ChatGPT should be limited to self‐learning as positive effect was experienced through the experimentPolicymakers may use the findings of the study to impose strict policies in academia for ensuring academic integrity (Example: must use of plagiarism detecting software for checking scripts, assigning tasks to students which require more analytical abilities, providing tasks which are not properly readable by LLM's like ChatGPT such as image‐based questions, case studies etc.) [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has emerged as one of the central topics of 2023 with extensive media coverage of the most relevant technologies and issues associated with this subject. In a highly competitive digital media landscape, search engine optimization (SEO) has become cybermedia’s primary strategy to increase visibility and attract more readers. The objective of this paper is to analyze the visibility of content published by the media relating to artificial intelligence, focusing on a selection of related keywords. The research also aims to investigate how this visibility has impacted both the technologies themselves and the analyzed media outlets. A total of 69 media outlets from 12 European Union countries, the United States, and the United Kingdom were examined. The results reveal a pronounced dominance of U.S. media, closely followed by Spanish media. There is an uneven distribution of media outlets across most of the countries analyzed, with two or three most of the of visibility. The search queries that contribute the most visibility to the analyzed media align with an informational intent, are of the long-tail type, and are associated with OpenAI technologies, particularly ChatGPT. Moreover, these queries are primarily found in news sections dedicated to science and technology. The findings underscore both the increasing interest in the subject and the effective SEO practices of certain media outlets. [ABSTRACT FROM AUTHOR]

Background: This paper investigates initial exuberance and emotions surrounding ChatGPT's first three months of launch (1 December 2022–1 March 2023). The impetus for studying active discussions surrounding its implications, fears, and opinions is motivated by its nascent popularity and potential to disrupt existing professions; compounded by its significance as a crucial inflexion point in history. Capturing the public zeitgeist on new innovations—much like the advent of the printing press, radio, newspapers, or the internet—provides a retrospective overview of public sentiments, common themes, and issues. Objectives: Since launch, few big data studies delved into initial public discourse surrounding the chatbot. This report firstly identifies highest-engagement issues and themes that generated the most interaction; secondly, identifies the highest-engaged keywords on both sides of the sentiment valence scale (positive and negative) associated with ChatGPT. Methods: We interrogate a large twitter corpus (n = 4,251,662) of all publicly available English-language tweets containing the ChatGPT keyword. Our first research aim utilizes a prominent peaks model (upper-quartile significance threshold of prominence>20,000). Our second research aim utilized sentiment analysis to identify, week-on-week, highest-frequency negative, and positive keywords and emojis. Results: Six prominent peaks were identified with the following themes: 'hype and hesitance', 'utility and misuse in professional and academic settings', 'demographic bias', 'philosophical thought experiments on morality' and 'artificial intelligence as a mirror of human knowledge'. Of high-frequency valence, negativity included credibility concerns, implicit bias, environmental ethics, employment rights of data annotators and programmers, the ethicality of neural network datasets. Positivity included excitement over application, especially in coding, as a creative tool, education, and personal productivity. Conclusions: Overall, sentiments and themes were double-edged, expressing excitement over this powerful new tool and wariness toward its potential for misuse. [ABSTRACT FROM AUTHOR]

OBJECTIVE: We, therefore, aim to conduct a systematic review to assess the academic potential of ChatGPT-3.5, along with its strengths and limitations when giving medical exams. METHOD: Following PRISMA guidelines, a systemic search of the literature was performed using electronic databases PUBMED/MEDLINE, Google Scholar, and Cochrane. Articles from their inception till April 4, 2023, were queried. A formal narrative analysis was conducted by systematically arranging similarities and differences between individual findings together. RESULTS: After rigorous screening, 12 articles underwent this review. All the selected papers assessed the academic performance of ChatGPT-3.5. One study compared the performance of ChatGPT-3.5 with the performance of ChatGPT-4 when giving a medical exam. Overall, ChatGPT performed well in 4 tests, averaged in 4 tests, and performed badly in 4 tests. ChatGPT's performance was directly proportional to the level of the questions' difficulty but was unremarkable on whether the questions were binary, descriptive, or MCQ-based. ChatGPT's explanation, reasoning, memory, and accuracy were remarkably good, whereas it failed to understand image-based questions, and lacked insight and critical thinking. CONCLUSION: ChatGPT-3.5 performed satisfactorily in the exams it took as an examinee. However, there is a need for future related studies to fully explore the potential of ChatGPT in medical education. [ABSTRACT FROM AUTHOR]

Key digested message This article examines the expansive growth of ChatGPT and the implications for large-scale test design. The authors contend that the impressive test simulation results observed by Chat-GPT undergird ongoing construct validity concerns with student testing. In order to address these challenges, a set of strategies is proposed that emphasises authentic assessment, the importance of human elements in traditional paper-and-pencil questions, and the controversial issue of the stakes ascribed to test results. Collectively, these approaches are meant to help test developers more carefully consider existing limitations within traditional standardised and large-scale assessment programs. Ultimately, test design reforms that enhance validity are increasingly needed to address the challenges posed by AI applications. [ABSTRACT FROM AUTHOR]

Concerns about runaway artificial intelligence (AI) – including large language models (LLMs) like ChatGPT – are at the forefront of contemporary political, social, and scientific discourse. This commentary provides a first look at ChatGPT's capabilities and limitations in supporting geographic research, critical thinking, learning, and curriculum development. We assessed ChatGPT's geographic knowledge, synthesising abilities, and potential for extrapolation. ChatGPT was employed for writing assistance, research evaluation, curriculum material creation, and content generation. Despite achieving scores of 47% to 55% on an actual exam paper, ChatGPT exhibited shortcomings including the generation of false references. Ethical concerns regarding academic misconduct, model bias, robustness, and toxic output were also identified. We assert that AI and LLMs like ChatGPT have transformative potential in Geography education and knowledge production but demand critical usage. Accordingly, we urge geographers to enhance AI literacy to enable responsible and effective use of these assistive technologies in our academic practice. This commentary provides a first look at ChatGPT's capabilities and limitations in supporting geographic research, critical thinking, learning, and curriculum development. We assessed ChatGPT's geographic knowledge, synthesising abilities, and potential for extrapolation as well as its use as a supportive technology for writing assistance, research evaluation, curriculum material creation, and content generation. We close by urging geographers to enhance AI literacy to enable responsible and effective use of these assistive technologies in our academic practice. [ABSTRACT FROM AUTHOR]

ChatGPT, an artificial intelligence large language model, took the world by storm in November 2022. Its launch was met with excitement, and it garnered over 1 million users within the first five days of its release, surpassing social media giants like Facebook, Instagram, Twitter and even the top search engine, Google. Having been trained on volumes of data, ChatGPT has displayed the ability to produce human-like responses to questions. Concerns have been raised among members of the academic and research community regarding the ethical usage of ChatGPT and language models in education and academic/scientific research. This paper examines the development and rise of ChatGPT and similar AI tools, their pros and cons, their impact on academic research and possible intellectual property conflicts. It concludes that ChatGPT and language models are here to stay and makes recommendations for its ethical usage to prevent and detect plagiarism and protect intellectual property rights. [ABSTRACT FROM AUTHOR]

Our paper compares the correctness, efficiency, and maintainability of human-generated and AI-generated program code. For that, we analyzed the computational resources of AI- and human-generated program code using metrics such as time and space complexity as well as runtime and memory usage. Additionally, we evaluated the maintainability using metrics such as lines of code, cyclomatic complexity, Halstead complexity and maintainability index. For our experiments, we had generative AIs produce program code in Java, Python, and C++ that solves problems defined on the competition coding website leetcode.com. We selected six LeetCode problems of varying difficulty, resulting in 18 program codes generated by each generative AI. GitHub Copilot, powered by Codex (GPT-3.0), performed best, solving 9 of the 18 problems (50.0%), whereas CodeWhisperer did not solve a single problem. BingAI Chat (GPT-4.0) generated correct program code for seven problems (38.9%), ChatGPT (GPT-3.5) and Code Llama (Llama 2) for four problems (22.2%) and StarCoder and InstructCodeT5+ for only one problem (5.6%). Surprisingly, although ChatGPT generated only four correct program codes, it was the only generative AI capable of providing a correct solution to a coding problem of difficulty level hard. In summary, 26 AI-generated codes (20.6%) solve the respective problem. For 11 AI-generated incorrect codes (8.7%), only minimal modifications to the program code are necessary to solve the problem, which results in time savings between 8.9% and even 71.3% in comparison to programming the program code from scratch. [ABSTRACT FROM AUTHOR]

The rapid advancement of artificial intelligence (AI) has given rise to sophisticated language models that excel in understanding and generating human-like text. With the capacity to process vast amounts of information, these models effectively tackle problems across diverse domains. In this paper, we present a comparative analysis of prominent AI language models—ChatGPT and Google Bard—focusing on their ability to solve undergraduate finance problems. We find that GPT-4 significantly outperforms Bard-1.0, excelling in easy problems but struggling with complex ones. The results suggest that it is crucial to handle AI with care in order to uphold academic integrity. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has emerged as a transformative force in various sectors, including medicine and healthcare. Large language models like ChatGPT showcase AI's potential by generating human-like text through prompts. ChatGPT's adaptability holds promise for reshaping medical practices, improving patient care, and enhancing interactions among healthcare professionals, patients, and data. In pandemic management, ChatGPT rapidly disseminates vital information. It serves as a virtual assistant in surgical consultations, aids dental practices, simplifies medical education, and aids in disease diagnosis. A total of 82 papers were categorised into eight major areas, which are G1: treatment and medicine, G2: buildings and equipment, G3: parts of the human body and areas of the disease, G4: patients, G5: citizens, G6: cellular imaging, radiology, pulse and medical images, G7: doctors and nurses, and G8: tools, devices and administration. Balancing AI's role with human judgment remains a challenge. A systematic literature review using the PRISMA approach explored AI's transformative potential in healthcare, highlighting ChatGPT's versatile applications, limitations, motivation, and challenges. In conclusion, ChatGPT's diverse medical applications demonstrate its potential for innovation, serving as a valuable resource for students, academics, and researchers in healthcare. Additionally, this study serves as a guide, assisting students, academics, and researchers in the field of medicine and healthcare alike. [ABSTRACT FROM AUTHOR]

The role of libraries in preparing students to thrive during their studies and innovate after university is growing in importance. Information is more easily accessible through digital channels and is increasingly abundant. Generative Artificial intelligence (AI) adds to this reality and increases the need for digitally driven information literacy skills. This paper aims to guide librarians by discussing the digitalization of information creation, retrieval, and use. It recommends the training of both digital and information literacy for students. Librarians are called upon to provide clear guidelines to their universities to steer the use of generative AI. The implications of digital information sources and generative AI are discussed with the role of librarians in context. Information literacy and digital literacy are related. Academic libraries should include digital topics in information literacy training. Information literacy should be trained at the start of university education and before students begin dissertation writing. University libraries should propose guidelines for the use of generative artificial intelligence tools by students. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) is the newest technological hype. Although it involves a great diversity of technologies, the disseminated image of AI has been a generic, super-powerful, extremely negative one, at the edge of dystopian, especially in works of science fiction. Recently, following the launch of ChatGPT, one finds an explosion of journalistic and academic publications, some of which reinforce this public imagination. In academia, AI’s risks remain highlighted and even apocalyptic scenarios related to it are taken into consideration. Ethical concerns, then, take on eminently negative connotations, and the much more realistic possible benefits of AIs are under-focused. We highlight in this paper the importance of going beyond the hype and developing multi/interdisciplinary, delimited, realistic, and thoughtful approaches. Employing the collective intelligence embodied in the interaction between researchers from three fields —Computer Science, Linguistics, and Philosophy— we approach a free machine translation tool: Google Translate. Our goal is to show that well-defined, multidisciplinary, technically supported approaches that do not adhere to sensationalist discourse lead us to more epistemically consistent and more thoughtful critical-normative reflections, which would be crucial for advancing the debate on AI. [ABSTRACT FROM AUTHOR]