ChatGPT Isn't Magic

How Can <i>IJDS</i> Authors, Reviewers, and Editors Use (and Misuse) Generative AI?

Purpose: This analysis aims to propose guidelines for artificial intelligence (AI) research ethics in scientific publications, intending to inform publishers and academic institutional policies in order to guide them toward a coherent and consistent approach to AI research ethics.Methods: A literature-based thematic analysis was conducted. The study reviewed the publication policies of the top 10 journal publishers addressing the use of AI in scholarly publications as of October 2024. Thematic analysis using Atlas.ti identified themes and subthemes across the documents, which were consolidated into proposed research ethics guidelines for using generative AI and AI-assisted tools in scholarly publications.Results: The analysis revealed inconsistencies among publishers’ policies on AI use in research and publications. AI-assisted tools for grammar and formatting are generally accepted, but positions vary regarding generative AI tools used in pre-writing and research methods. Key themes identified include author accountability, human oversight, recognized and unrecognized uses of AI tools, and the necessity for transparency in disclosing AI usage. All publishers agree that AI tools cannot be listed as authors. Concerns involve biases, quality and reliability issues, compliance with intellectual property rights, and limitations of AI detection tools.Conclusion: The article highlights the significant knowledge gap and inconsistencies in guidelines for AI use in scientific research. There is an urgent need for unified ethical standards, and guidelines are proposed for distinguishing between the accepted use of AI-assisted tools and the cautious use of generative AI tools.

Response to M. Trengove & coll regarding "Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine".

The Value of Artificial Intelligence for Healthcare Decision Making—Lessons Learned

Background ChatGPT is a large language model that uses deep learning techniques to generate human-like texts. ChatGPT has the potential to revolutionize medical education as it acts as an interactive virtual tutor and personalized learning assistant. We assessed the use of ChatGPT and other Artificial Intelligence (AI) tools among medical faculty in Uganda. Methods We conducted a descriptive cross-sectional study among medical faculty at four public universities in Uganda from November to December 2023. Participants were recruited consecutively. We used a semi-structured questionnaire to collect data on participants’ socio-demographics and the use of AI tools such as ChatGPT. Our outcome variable was the use of ChatGPT and other AI tools. Data were analyzed in Stata version 17.0. Results We recruited 224 medical faculty, majority [75% (167/224)] were male. The median age (interquartile range) was 41 years (34–50). Almost all medical faculty [90% (202/224)] had ever heard of AI tools such as ChatGPT. Over 63% (120/224) of faculty had ever used AI tools. The most commonly used AI tools were ChatGPT (56.3%) and Quill Bot (7.1%). Fifty-six faculty use AI tools for research writing, 37 for summarizing information, 28 for proofreading work, and 28 for setting exams or assignments. Forty faculty use AI tools for non-academic purposes like recreation and learning new skills. Faculty older than 50 years were 40% less likely to use AI tools compared to those aged 24 to 35 years (Adjusted Prevalence Ratio (aPR):0.60; 95% Confidence Interval (CI): [0.45, 0.80]). Conclusion The use of ChatGPT and other AI tools was high among medical faculty in Uganda. Older faculty (&gt;50 years) were less likely to use AI tools compared to younger faculty. Training on AI use in education, formal policies, and guidelines are needed to adequately prepare medical faculty for the integration of AI in medical education.

ChatGPT is a large language model that uses deep learning techniques to generate human-like texts. ChatGPT has the potential to revolutionize medical education as it acts as an interactive virtual tutor and personalized learning assistant. We assessed the use of ChatGPT and other Artificial Intelligence (AI) tools among medical faculty in Uganda. We conducted a descriptive cross-sectional study among medical faculty at four public universities in Uganda from November to December 2023. Participants were recruited consecutively. We used a semi-structured questionnaire to collect data on participants' socio-demographics and the use of AI tools such as ChatGPT. Our outcome variable was the use of ChatGPT and other AI tools. Data were analyzed in Stata version 17.0. We recruited 224 medical faculty, majority [75% (167/224)] were male. The median age (interquartile range) was 41 years (34-50). Almost all medical faculty [90% (202/224)] had ever heard of AI tools such as ChatGPT. Over 63% (120/224) of faculty had ever used AI tools. The most commonly used AI tools were ChatGPT (56.3%) and Quill Bot (7.1%). Fifty-six faculty use AI tools for research writing, 37 for summarizing information, 28 for proofreading work, and 28 for setting exams or assignments. Forty faculty use AI tools for non-academic purposes like recreation and learning new skills. Faculty older than 50 years were 40% less likely to use AI tools compared to those aged 24 to 35 years (Adjusted Prevalence Ratio (aPR):0.60; 95% Confidence Interval (CI): [0.45, 0.80]). The use of ChatGPT and other AI tools was high among medical faculty in Uganda. Older faculty (>50 years) were less likely to use AI tools compared to younger faculty. Training on AI use in education, formal policies, and guidelines are needed to adequately prepare medical faculty for the integration of AI in medical education.

Holding artificial intelligence to account

Artificial intelligence is defined as the totality of systems and programs that imitate human intelligence and can eventually surpass this intelligence over time. The rapid development of these technologies has raised various ethical debates such as moral responsibility, privacy, bias, respect for human rights, and social impacts. This study examines the technical infrastructure of artificial intelligence, the differences between weak and strong artificial intelligence, ethical issues, and theological dimensions in detail, providing a comprehensive perspective on the role of artificial intelligence in human life and the problems it brings. The historical development of artificial intelligence has been shaped by the contributions of various disciplines such as mathematical logic, cognitive science, philosophy, and engineering. From the ancient Greek philosophers to the present day, thoughts on artificial intelligence have raised deep philosophical questions such as human nature, consciousness, and responsibility. The algorithms developed by Alan Turing have contributed to the modern shaping of artificial intelligence and have put forward the first models to assess whether machines have human-like intelligence, such as the “Turing Test”. The study first analyzes the technical infrastructure of artificial intelligence in detail and discusses the current limits and potential of the technology through the distinction between weak and strong artificial intelligence. Weak artificial intelligence includes systems designed to perform specific tasks and do not exhibit general intelligence outside of those tasks, while strong artificial intelligence refers to systems with human-like general intelligence and flexible thinking capacity. Most of the widely used artificial intelligence applications today fall into the category of weak artificial intelligence. However, the development of strong artificial intelligence brings various ethical and theological consequences for humanity. The ethical issues of artificial intelligence include fundamental topics such as autonomy, responsibility, transparency, fairness, and privacy. The decision-making processes of autonomous systems raise serious ethical questions at the societal level. Especially autonomous weapons and artificial intelligence-managed justice systems raise concerns in terms of human rights and individual freedoms. In this context, the ethical framework of artificial intelligence has deep impacts on the future of humanity and human-machine interaction, not just limited to technological boundaries. From a theological perspective, the ability of artificial intelligence to imitate the human mind and creative processes raises deep theological issues such as the creativity of God, the place of human beings in the universe, and consciousness. The questions of whether artificial intelligence systems can gain consciousness and whether these conscious systems can have a spiritual status have led to new debates in theology and philosophy. The ethical principles of artificial intelligence are shaped around principles such as transparency, accountability, autonomy, human control, and data management. In conclusion, determining the ethical and theological principles that need to be considered in the development and application of artificial intelligence is critical for the future of humanity. A comprehensive examination of the ethical and theological dimensions of artificial intelligence technologies is necessary to understand and manage the social impacts of this technology. This study emphasizes the necessity of an interdisciplinary approach for the development of artificial intelligence in harmony with social values and for the benefit of humanity. The study provides an important theoretical framework for future research by shedding light on the complex ethical and theological issues arising from the development and widespread use of artificial intelligence.

Background ChatGPT is an open-source large language model that uses deep learning techniques to generate human-like texts. ChatGPT has the potential to revolutionize medical education as it acts as an interactive virtual tutor and personalized learning assistant. We assessed the use of ChatGPT and other Artificial Intelligence (AI) tools among medical faculty in Uganda. Methods We conducted a descriptive cross-sectional study among medical faculty at four public universities in Uganda from November to December 2023. Participants were recruited consecutively. We used a semi-structured questionnaire to collect data on participants’ socio-demographics and the use of AI tools such as ChatGPT. Our outcome variable was the use of ChatGPT and other AI tools. Data were analyzed in Stata version 17.0. Results We recruited 224 medical faculty, majority [75% (167/224)] were male. The median age (interquartile range) was 41 years (34–50). Almost all medical faculty [90% (202/224)] had ever heard of AI tools such as ChatGPT. Over 63% (120/224) of faculty had ever used AI tools. The most commonly used AI tools were ChatGPT (56.3%) and Quill Bot (7.1%). Fifty-six faculty use AI tools for research writing, 37 for summarizing information, 28 for proofreading work, and 28 for setting exams or assignments. Forty faculty use AI tools for non-academic purposes like recreation and learning new skills. Faculty older than 50 years were 40% less likely to use AI tools compared to those aged 24 to 35 years (Adjusted Prevalence Ratio (aPR):0.60; 95% Confidence Interval (CI): [0.45, 0.80]). Conclusion The use of ChatGPT and other AI tools was high among medical faculty in Uganda. Older faculty (&gt;50 years) were less likely to use AI tools compared to younger faculty. Training on AI use in education, formal policies, and guidelines are needed to adequately prepare medical faculty for the integration of AI in medical education.

As generative artificial intelligence (AI) tools and large language models (LLMs)-powered applications develop rapidly in the era of algorithms, it should be integrated thoughtfully to enhance English as a Foreign Language (EFL) teaching and learning without replacing learners’ critical thinking (CT). This study systematically analyzes the impact of generative AI tools and LLMs on language learners’ CT in EFL education using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework to identify, evaluate, and synthesize relevant studies from 2022 to 2025. A thorough review of 15 selected studies focuses on generative AI tools and LLMs’ dual nature, research methods, main focuses, theory and models, limitations and challenges, and future directions in the field based on Web of Science (WoS), SCOPUS, ERIC, ProQuest, and Google Scholar. The findings identified generative AI tools and LLMs possessed both the potential to nurture and the risk of hindering CT in EFL education. 66.67% of studies reported generative AI tools and LLMs’ positive role in CT, while 33.33% of studies reported its negative role in CT. Furthermore, 3 types of research methods, 3 key themes of research focus, and 4 groups of theoretical perspectives were examined. However, 4 kinds of limitations in this field remain, including research scope, user dependency, generative AI reliability, and pedagogical integration. Future research can focus on assessing long-term effects, broadening research scope, promoting responsible AI use, and refining pedagogical strategies. Finally, Limitations, implications and future direction of this study were discussed.

Over the past three decades, the evolution of technology has dramatically reshaped the information landscape, making it easier to access and simultaneously easier to distort. The advent of artificial intelligence (AI), particularly generative tools like ChatGPT and CoPilot, has further complicated the pursuit of information literacy, posing significant challenges for educators, librarians and students alike. This paper explores the implications of integrating generative AI (GenAI) tools into educational and professional settings, emphasising the necessity of critical thinking and the development of robust information literacy skills to discern the credibility and authority of AI-generated content. By examining the Association of College and Research Libraries’ (ACRL) ‘Framework for Information Literacy for Higher Education’, this paper provides strategies to identify risk areas related to AI integration as well as produce use cases for large language model (LLM) GenAI tools, including a flowchart for determining when to make use of GenAI, a toolkit for positive/effective use cases, and a rubric for assessing information literacy and critical thinking. While AI tools can offer valuable educational opportunities, their propensity to generate misleading or inaccurate information necessitates a careful and informed approach to their use. This paper concludes with a call for ongoing vigilance in maintaining academic integrity and underscores the importance of continuously questioning the reliability of AI outputs in educational contexts.

The integration of generative artificial intelligence (AI) tools is a paradigm shift in enhanced learning methodologies and assessment techniques. This study explores the adoption of generative AI tools in higher education assessments by examining the perceptions of 353 students through a survey and 17 in-depth interviews. Anchored in the Unified Theory of Acceptance and Use of Technology (UTAUT), this study investigates the roles of perceived risk and tech-savviness in the use of AI tools. Perceived risk emerged as a significant deterrent, while trust and tech-savviness were pivotal in shaping student engagement with AI. Tech-savviness not only influenced adoption but also moderated the effect of performance expectancy on AI use. These insights extend UTAUT’s application, highlighting the importance of considering perceived risks and individual proficiency with technology. The findings suggest educators and policymakers need to tailor AI integration strategies to accommodate students’ personal characteristics and diverse needs, harnessing generative AI’s opportunities and mitigating its challenges.

In contemporary society, Artificial Intelligence (AI) pervades numerous facets of our lives and is likely to impact many sectors and professions, including education. Tertiary-level students in particular face challenges regarding the use of AI for studies and assessment, including limited understanding of AI tools, as well as a lack of deep critical engagement with AI for learning (Shibani et al., 2024). To respond to emerging developments in generative AI, the recent Australian Tertiary Education Quality and Standards Agency (TEQSA) report suggests tertiary-level learning and assessments be designed to foster responsible and ethical use of AI (Lodge et al., 2023). This involves the development of AI literacy among students to engage with AI in critical, ethical ways that aid their learning and not hinder it. Our project aims to narrow the AI literacy gap among students from diverse study backgrounds by providing foundational knowledge and developing critical skills for practical use of AI tools for learning and professional practice, in collaboration with students and academics as part of a Students as Partners (SAP) initiative. Staff bring expertise in AI critical engagement and students bring practical, first-hand experiences of learning in this collaboration, supported by the university’s SAP program. Building on the current UNESCO recommendations for the use of generative AI in education (UNESCO, 2023) and prior theoretical frameworks on AI literacy (Chiu et al., 2024; Ng, et al., 2021; Southworth et al., 2023) we target key skills that higher education students should develop to meaningfully engage with AI. By creating accessible and engaging resources, such as instructional videos and comprehensive guides on generative AI applications like ChatGPT and ways to prompt for enhancing learning, we introduce existing AI tools and teach students to use them effectively, promoting a hands-on learning environment. Using learning design principles, the developed curriculum will be presented in an AI Literacy module on a Canvas site, with supporting instruction workshopped with student participants for evaluation. Student cohorts recruited from diverse disciplines will pilot and assess the effectiveness of the program, and qualitative methods such as focus groups and interviews will be used for evaluation of our intervention and continuous improvements. Findings will inform tertiary students’ current level of AI literacy and the effectiveness of interventions to improve key skills beyond their disciplinary knowledge, better preparing them for life beyond university. Indeed, the implementation of similar AI literacy courses has demonstrated statistically significant improvements in AI literacy and understanding of AI concepts amongst university students (Kong, Cheung, &amp; Zhang, 2021). Our approach underscores the importance of relational engagement in higher education with students as partners (Matthews, 2018) and participatory design with students in a topic that is significant in the current age of AI (Laupichler et al., 2022). The course's flexibility to be accessed directly or embedded into other curricula ensures scalability and broader impact, solidifying the validity of our multifaceted approach. Through utilising relevant research methodologies and learning design principles, we endeavour to create an AI literacy course that is robust, accessible, educational, and engaging to use by tertiary-level students from diverse study backgrounds.

Students’ use of Artificial Intelligence tools to complete assignments spawns issues in academic integrity. The purpose of this study was to explore students’ and faculty’s perspectives on the benefits and challenges of using ChatGPT and assistive Artificial intelligence (AI) tools to complete assignments. This descriptive phenomenological qualitative methodology study encompassed interviews with eight students who used Large Language Models (LLMs) AI tools to complete their assignments and nine students who did not. It also contains interviews with six Faculty and their perspectives on students’ use of Large Language Models (LLMs) AI tools to complete their assignments and their thoughts on the benefits and challenges. The participants were purposively selected. The data were coded based on Braun and Clarke’s (2013) six steps in thematic analysis. Descriptive, in vivo, and evaluative coding were used. Additionally, data were examined semantically and latently using reductionist analysis to determine the final themes. Five components of the Unified Theory of Acceptance and Use of Technology (UTTAUT) were applied to the data collected and provided the framework for the study. Behavioural intention served as the foundation. Effort and Performance Expectancies, and facilitating conditions were exemplified in participants’ responses about the use of ChatGPT, Grammarly, and other AI assistive tools, plagiarism/academic integrity, and social influence were indicated when participants (both Students and Faculty) suggested the need for the development of policies and procedures toward the appropriate use of AI tools. Effort and performance expectancies and habits were found in the data collected in the form of consideration of the pros of using AI tools such as ChatGPT and assistive tools. These include the time saved by generating information, examples for both students and Faculty, and help in the teaching/learning process, and one participant found that it motivated her. The cons cited were students’ lack of creativity and the inability to think critically, the cost of the AI assistive tools (related to the component Price), the bandwidth needed to use them, the digital divide, and the false information generated. This study has significance for the use of ChatGPT and assistive AI tools in education and the ethical implications. It is recommended that specific policies be established and enacted to ensure the appropriate use of assistive and Artificial Intelligence (LLMs) tools.

Should We Wait for Major Frauds to Unveil to Plan an AI Use License?