ChatGPT on campus: how top U.S. universities govern generative AI across higher education

Introduction Author Arthur C. Clarke famously argued that in science fiction literature “any sufficiently advanced technology is indistinguishable from magic” (Clarke). On 30 November 2022, technology company OpenAI publicly released their Large Language Model (LLM)-based chatbot ChatGPT (Chat Generative Pre-Trained Transformer), and instantly it was hailed as world-changing. Initial media stories about ChatGPT highlighted the speed with which it generated new material as evidence that this tool might be both genuinely creative and actually intelligent, in both exciting and disturbing ways. Indeed, ChatGPT is part of a larger pool of Generative Artificial Intelligence (AI) tools that can very quickly generate seemingly novel outputs in a variety of media formats based on text prompts written by users. Yet, claims that AI has become sentient, or has even reached a recognisable level of general intelligence, remain in the realm of science fiction, for now at least (Leaver). That has not stopped technology companies, scientists, and others from suggesting that super-smart AI is just around the corner. Exemplifying this, the same people creating generative AI are also vocal signatories of public letters that ostensibly call for a temporary halt in AI development, but these letters are simultaneously feeding the myth that these tools are so powerful that they are the early form of imminent super-intelligent machines. For many people, the combination of AI technologies and media hype means generative AIs are basically magical insomuch as their workings seem impenetrable, and their existence could ostensibly change the world. This article explores how the hype around ChatGPT and generative AI was deployed across the first six months of 2023, and how these technologies were positioned as either utopian or dystopian, always seemingly magical, but never banal. We look at some initial responses to generative AI, ranging from schools in Australia to picket lines in Hollywood. We offer a critique of the utopian/dystopian binary positioning of generative AI, aligning with critics who rightly argue that focussing on these extremes displaces the more grounded and immediate challenges generative AI bring that need urgent answers. Finally, we loop back to the role of schools and educators in repositioning generative AI as something to be tested, examined, scrutinised, and played with both to ground understandings of generative AI, while also preparing today’s students for a future where these tools will be part of their work and cultural landscapes. Hype, Schools, and Hollywood In December 2022, one month after OpenAI launched ChatGPT, Elon Musk tweeted: “ChatGPT is scary good. We are not far from dangerously strong AI”. Musk’s post was retweeted 9400 times, liked 73 thousand times, and presumably seen by most of his 150 million Twitter followers. This type of engagement typified the early hype and language that surrounded the launch of ChatGPT, with reports that “crypto” had been replaced by generative AI as the “hot tech topic” and hopes that it would be “‘transformative’ for business” (Browne). By March 2023, global economic analysts at Goldman Sachs had released a report on the potentially transformative effects of generative AI, saying that it marked the “brink of a rapid acceleration in task automation that will drive labor cost savings and raise productivity” (Hatzius et al.). Further, they concluded that “its ability to generate content that is indistinguishable from human-created output and to break down communication barriers between humans and machines reflects a major advancement with potentially large macroeconomic effects” (Hatzius et al.). Speculation about the potentially transformative power and reach of generative AI technology was reinforced by warnings that it could also lead to “significant disruption” of the labour market, and the potential automation of up to 300 million jobs, with associated job losses for humans (Hatzius et al.). In addition, there was widespread buzz that ChatGPT’s “rationalization process may evidence human-like cognition” (Browne), claims that were supported by the emergent language of ChatGPT. The technology was explained as being “trained” on a “corpus” of datasets, using a “neural network” capable of producing “natural language“” (Dsouza), positioning the technology as human-like, and more than ‘artificial’ intelligence. Incorrect responses or errors produced by the tech were termed “hallucinations”, akin to magical thinking, which OpenAI founder Sam Altman insisted wasn’t a word that he associated with sentience (Intelligencer staff). Indeed, Altman asserts that he rejects moves to “anthropomorphize” (Intelligencer staff) the technology; however, arguably the language, hype, and Altman’s well-publicised misgivings about ChatGPT have had the combined effect of shaping our understanding of this generative AI as alive, vast, fast-moving, and potentially lethal to humanity. Unsurprisingly, the hype around the transformative effects of ChatGPT and its ability to generate ‘human-like’ answers and sophisticated essay-style responses was matched by a concomitant panic throughout educational institutions. The beginning of the 2023 Australian school year was marked by schools and state education ministers meeting to discuss the emerging problem of ChatGPT in the education system (Hiatt). Every state in Australia, bar South Australia, banned the use of the technology in public schools, with a “national expert task force” formed to “guide” schools on how to navigate ChatGPT in the classroom (Hiatt). Globally, schools banned the technology amid fears that students could use it to generate convincing essay responses whose plagiarism would be undetectable with current software (Clarence-Smith). Some schools banned the technology citing concerns that it would have a “negative impact on student learning”, while others cited its “lack of reliable safeguards preventing these tools exposing students to potentially explicit and harmful content” (Cassidy). ChatGPT investor Musk famously tweeted, “It’s a new world. Goodbye homework!”, further fuelling the growing alarm about the freely available technology that could “churn out convincing essays which can't be detected by their existing anti-plagiarism software” (Clarence-Smith). Universities were reported to be moving towards more “in-person supervision and increased paper assessments” (SBS), rather than essay-style assessments, in a bid to out-manoeuvre ChatGPT’s plagiarism potential. Seven months on, concerns about the technology seem to have been dialled back, with educators more curious about the ways the technology can be integrated into the classroom to good effect (Liu et al.); however, the full implications and impacts of the generative AI are still emerging. In May 2023, the Writer’s Guild of America (WGA), the union representing screenwriters across the US creative industries, went on strike, and one of their core issues were “regulations on the use of artificial intelligence in writing” (Porter). Early in the negotiations, Chris Keyser, co-chair of the WGA’s negotiating committee, lamented that “no one knows exactly what AI’s going to be, but the fact that the companies won’t talk about it is the best indication we’ve had that we have a reason to fear it” (Grobar). At the same time, the Screen Actors’ Guild (SAG) warned that members were being asked to agree to contracts that stipulated that an actor’s voice could be re-used in future scenarios without that actor’s additional consent, potentially reducing actors to a dataset to be animated by generative AI technologies (Scheiber and Koblin). In a statement issued by SAG, they made their position clear that the creation or (re)animation of any digital likeness of any part of an actor must be recognised as labour and properly paid, also warning that any attempt to legislate around these rights should be strongly resisted (Screen Actors Guild). Unlike the more sensationalised hype, the WGA and SAG responses to generative AI are grounded in labour relations. These unions quite rightly fear the immediate future where human labour could be augmented, reclassified, and exploited by, and in the name of, algorithmic systems. Screenwriters, for example, might be hired at much lower pay rates to edit scripts first generated by ChatGPT, even if those editors would really be doing most of the creative work to turn something clichéd and predictable into something more appealing. Rather than a dystopian world where machines do all the work, the WGA and SAG protests railed against a world where workers would be paid less because executives could pretend generative AI was doing most of the work (Bender). The Open Letter and Promotion of AI Panic In an open letter that received enormous press and media uptake, many of the leading figures in AI called for a pause in AI development since “advanced AI could represent a profound change in the history of life on Earth”; they warned early 2023 had already seen “an out-of-control race to develop and deploy ever more powerful digital minds that no one – not even their creators – can understand, predict, or reliably control” (Future of Life Institute). Further, the open letter signatories called on “all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4”, arguing that “labs and independent experts should use this pause to jointly develop and implement a set of shared safety protocols for advanced AI design and development that are rigorously audited and overseen by independent outside experts” (Future of Life Institute). Notably, many of the signatories work for the very companies involved in the “out-of-control race”. Indeed, while this letter could be read as a moment of ethical clarity for the AI industry, a more cynical reading might just be that in warning that their AIs could effectively destroy the w

With the increasing use of Generative Artificial Intelligence (AI) tools like ChatGPT and Bard, universities face challenges in maintaining academic integrity. This research investigates the impact of these tools on learning outcomes (factual knowledge, comprehension, critical thinking) in selected universities of Ghana's Upper East Region during the 2023-2024 academic year. The study specifically analyzes changes in student comprehension and academic integrity concerns when using Generative AI for content generation, research assistance, and summarizing complex topics. A mixed-methods approach was employed, combining qualitative data from interviews and open-ended questions with quantitative analysis of survey data and academic records. The research focuses on three institutions: C. K. Tedam University of Technology and Applied Sciences, Bolgatanga Technical University, and Regentropfen University College. A purposive sampling technique recruited 150 participants (50 from each university) who had used Generative AI tools. Key findings show that 72% of students reported improved understanding of course material through Generative AI use, yet 75% cited academic integrity as a primary concern. Quantitative analysis revealed a weak to moderate positive correlation (r = 0.45) between AI tool usage and improved grades, with variations depending on the specific AI tasks performed. Qualitative data highlighted concerns about overreliance on AI and its impact on critical thinking skills. This research contributes to the ongoing debate on AI's role in education by providing valuable insights for educators and policymakers worldwide. The findings suggest that while AI tools can enhance comprehension, ethical considerations and potential drawbacks related to critical thinking require careful attention. The study concludes with recommendations for integrating AI literacy programs, developing ethical guidelines, and implementing advanced plagiarism detection systems to harness the benefits of Generative AI while mitigating risks to academic integrity. Although specific to the Upper East Region of Ghana, these insights may be applicable to other educational systems with similar characteristics.

Marketing scientists as well as practitioners believe that artificial intelligence (AI) holds the promise of productivity gains for organizations. However, there has been little scientific research into these theories. This study investigates the role of AI in enhancing marketing productivity, deriving insights from a case study conducted with the marketing team of an industrial software start-up. Drawing upon Case Study Analysis by Yin (2018) and Participatory Action Research by Kemmis and McTaggart (2007), the study employs a combination of survey interviews, AI tool research and AI tool testings. Key findings indicate that productivity gains are more likely than productivity impairments with the use of marketing AI tools. This effect is even stronger when knowledge workers possess high levels of AI skills and utilize AI tools with suitable capabilities. Having closely analyzed six marketing disciplines, particularly SEO / content and design demonstrated significant productivity gains including generative AI (GAI) tools the team already subscribed to like ChatGPT 4 and Canva, but also new AI solutions. While an AI tool’s level of integration only showed a weak positive productivity impact, future studies are suggested to further investigate this variable by comparing the effects of less advanced but more accessible tools like generative AI versus highly advanced, but less accessible business AI. Having navigated the vast and dynamic landscape of AI tools, insights further emphasize the importance of AI experience sharing and informed decision-making, implying knowledge of own user rights and always staying updated on AI advancements. Zooming out from process level, the work's literature review further highlights the role of environmental and organizational AI enablers, like budget allocation, fostering AI trust and mindset, but also implementing AI routines and responsibilities. Overall, this research underscores the imperative for companies, especially startups and SMEs, to explore AI technology as a means to enhance productivity and gain a competitive edge.

The article analyzes international and national experiences in the use of artificial intelligence (AI) tools in education and outlines the legal and regulatory framework for their implementation. The need for developing clear rules and recommendations on the ethical applying of generative AI in academia is emphasized. Current approaches to integrating AI technologies into the educational process of design specialties are examined. The research explores contemporary trends in the application of artificial intelligence technologies in education, particularly within the Design field. The purpose of the study is to analyze the potential of artificial intelligence (AI), especially generative models, in developing a product design concept using the Method of Focal Objects (MFO). Methodology. The study employs a comprehensive approach that combines theoretical analysis of recent scientific publications, a comparative method, and experimental modeling of the ideation process using generative AI tools. The Method of Focal Objects is considered as an algorithmic basis for creating new visual and functional solutions, while AI functions as an analytical assistant in selecting, combining, and visualizing creative ideas. Results. The study revealed that the rapid development and dissemination of AI technologies, particularly generative models, significantly affect the structure, content, and methodology of the educational process. The key stages of integrating AI into the process of developing a design concept are identified: defining characteristics/ properties of auxiliary objects, selecting associative series, generating creative combinations, analyzing results, and constructing a design model. It is demonstrated that the use of AI reduces the time required for idea generation, expands the designer’s associative field, and enables the emergence of unexpected yet potentially functional solutions. A practical scheme of interaction between MFO and AI is proposed. It is concluded that the higher education system have to adapt its approaches to learning, teaching, and assessment, taking into account technological innovations and the principles of academic integrity. Scientific novelty. For the first time, the methodological interaction between the Method of Focal Objects and generative AI in product design has been substantiated. A model of the creative process is proposed, in which AI algorithms act as a catalyst for creative thinking rather than a substitute for the designer. An analogy between the cognitive principles of the Method of Focal Objects and the architecture of generative models has been identified. Practical relevance. The findings can be applied in the professional training of designers to develop creative thinking skills and effective collaboration with AI tools. The proposed approach contributes to optimizing the conceptual design process, fostering an individual creative style, and enhancing the competitiveness of design solutions in the digital era. The results can also be used to develop methodological recommendations for integrating AI tools into higher education curricula. The conclusions of the study support the improvement of teacher training for working with generative technologies and the development of educational programs aimed at fostering ethical, digital, and civic competencies among students.

The study titled, “A Study on Evaluating the Impact of AI Tools on the Critical Thinking Ability of Students in Jerusalem College of Engineering,” examines how the use of Artificial Intelligence tools influences student’s academic learning and critical thinking ability. Using a descriptive research design, data were collected from 155 respondents through structured questionnaires and analyzed using percentage analysis, correlation analysis, ANOVA and chi-square tests. The study mainly focuses on how students use AI tools for academic tasks such as understanding concepts, completing assignments, preparing for exams and verifying information. The findings show that most students actively use AI tools for learning support, especially for understanding difficult concepts and completing academic tasks faster. While AI tools improve productivity and make learning easier, the study also indicates that excessive dependence on AI may affect student’s independent thinking ability. Many students still believe that AI tools should be used as a support tool rather than replacing traditional learning methods. Overall, the study highlights the importance of balancing AI usage with critical thinking to ensure effective learning and academic development. Keywords: Artificial Intelligence (AI) Tools, Critical Thinking, Student Learning Behavior, Academic Performance, Technology in Education, AI in Higher Education.

Purpose As generative artificial intelligence (AI) technologies continue to advance and become more prevalent in higher education, addressing the ethical concerns associated with their use is essential. This study emphasizes the need for robust AI governance as more young consumers increasingly use generative AI for various applications. This paper aims to examine the ethical challenges posed by generative AI and review the AI policies in higher education to regulate young consumers use of generative AI, focusing on the ethical use of AI from foundational principles to sustainable governance. Design/methodology/approach Through a content analysis of literature on generative AI policies in higher education published between 2020 and 2024, this research aims to explore a more holistic approach to integrating generative AI into the educational process. The analysis examines academic policies and governance framework from 28 journal papers regarding generative AI tools in higher education. Data were collected from publicly accessible sources, such as Scopus, Emerald Insights, ProQuest, Web of Science and ScienceDirect. Findings This study analyses ten elements of the governance framework to identify potential AI governance and policy setting, benefiting stakeholders aiming at enhancing the regulatory framework of generative AI use in higher education. The discussions indicate a generally balanced yet cautious approach to integrating generative AI technology, especially considering ethical issues, inherent limitations and data privacy concerns. Originality/value The findings contribute to ongoing discussions to strengthen universities’ responses to new academic challenges posed by the use of generative AI and promote high AI ethical standards across educational sectors.

The expansion of artificial intelligence (AI) tools has brought about new opportunities and challenges for teachers and students. These tools have the potential to reshape teaching and stimulate both students’ and teachers’ creativity. In 21st-century education, creativity emerges as a key skill that encompasses problem-solving, innovation, adaptability, critical thinking, and cognitive development. AI tools also provide personalized assistance and feedback as well as customized study materials. Moreover, they have proven beneficial in cultivating critical thinking and enhancing students’ research skills. Instead of questioning teachers’ preparedness for AI technologies, the focus should be on discovering ways to effectively and creatively integrate these tools into the classroom. This paper explores the possibilities of implementing generative AI tools to promote students’ creativity, thus enhancing the overall quality of teaching. In the Croatian educational system, similarly to Poland, school pedagogues should encourage positive changes within the school culture. Therefore, this paper also underscores the role of school pedagogues in bridging the gap between teachers and AI tools as an educational innovation. School pedagogues should be instrumental in supporting teachers during the integration of AI tools into their teaching by showcasing practical applications and emphasizing potential benefits for student engagement and learning outcomes. In this capacity, school pedagogues bear the responsibility of fostering a reflective and critical approach towards AI tools, advocating creative yet responsible use of technology in the classroom.

Generative artificial intelligence (AI) tools like ChatGPT hold the capacity to tremendously impact patterns of information seeking behavior in higher education, as students rely on AI tools for a variety of tasks in their daily life. This study examines the current state of how U.S. university students perceive and use AI chatbots versus traditional online search engines and academic library resources for academic information seeking and retrieval tasks. Based on an understanding of information seeking concepts drawn from existing information behavior research and theory, an electronic survey was distributed to 236 students from diverse demographic backgrounds, measuring information source use, preference, perceived relevance, and satisfaction across AI tools, search engines, and library databases. The results of the survey suggest that, while search engines like Google remain dominant for information retrieval in higher education, generative AI tools are an increasingly significant component of students’ information worlds. Younger students and international students are especially likely to use AI for academic tasks. Students who are frequent AI users also report higher satisfaction in the information supplied by AI models. These findings are indicative of a shifting ecology of information behavior where artificial intelligence serves both as a complement and a competitor to traditional information sources like search engines and university libraries, presenting important implications for information literacy instruction, academic library services, and educators navigating AI integration in higher education.

In the dynamic field of programming education, integrating artificial intelligence (AI) tools has started to play a significant role in enhancing learning experiences. This paper presents a case study conducted during a foundational programming course for first-year students in higher education, where students were encouraged to utilize generative artificial intelligence programming copilot extensions in their programming IDE and browser-based generative AI tools as supportive AI tools. The primary objective was to observe the impact of AI on the learning curve and the overall educational experience.Key findings suggest that the introduction of AI tools significantly altered the learning experience for students. Many who initially struggled with grasping elementary programming concepts found that AI support made understanding basic programming concepts much easier, enhancing their confidence and skills. This was particularly evident in the reduced levels of anxiety typically associated with early programming learning, as the AI copilot provided a non-judgmental, always-available source for clarifying doubts, including queries that students might hesitate to ask in a traditional classroom setting.Notably, some students leveraged the AI to generate similar exercise problems, reinforcing their understanding and skills. The AI's capability to address basic queries also freed up the instructor's time, allowing for more personalized student guidance in more advanced problems. This shift in the instructional dynamic further contributed to a learning environment where students felt more comfortable engaging with complex topics, thereby reducing the psychological barriers often linked with early-stage programming education.The course's structure, enriched by AI, enabled students to delve into more complex programming constructs earlier than traditional curricula would allow. For instance, students were tasked with simulating basic e-commerce operations, such as user registration, product browsing, and cart functionalities. These practical challenges naturally introduced advanced concepts like external data storage, unit testing, and user interface design, which are typically reserved for more advanced courses. With the help of generative AI programming copilot tools, students at any programming skill level were able to develop nearly functional complex structures. Interestingly, even when their projects were not fully functional, students remained motivated. Instead of feeling discouraged by these imperfect outcomes, they showed resilience and a keen interest in understanding and improving their code. This reaction is a significant shift from traditional learning settings, where unfinished or flawed projects often lead to increased anxiety or a drop in motivation.Furthermore, the AI's proactive suggestions inspired students to explore beyond the curriculum. Advanced learners delved into databases, cryptography libraries in Python, and even more advanced user interface design, ensuring that they remained engaged and challenged. This elementary course, enhanced by generative AI tools, also inspired students to learn other programming languages since they now learned that individual learning is more available with the aid of generative AI.In conclusion, the integration of AI in programming education offers a promising avenue for enhancing both the learning experience and outcomes. This case study underscores the potential of AI to revolutionize traditional teaching methodologies, fostering a more dynamic, responsive, and inclusive learning environment.This paper handles the results, possibilities and challenges of AI empowered education in programming. It also gives practical examples as well as future research perspectives.

This research explores postgraduate students' attitudes and use of Artificial Intelligence (AI) tools in academic writing, using the Theory of Planned Behavior (TPB). Guided by the mixed method approach, quantitative and qualitative measures like questionnaires and interviews were adopted to gather data from postgraduate students. Descriptive statistical tools like frequencies, means and SD were used to analyze responses from 339 postgraduate students, focusing on the perceived usefulness and actual usage of AI tools in their writing endeavors. The findings, presented through means and standard deviations, indicate an overall positive attitude towards AI tools. The students perceive AI as beneficial for improving grammar, preventing plagiarism, generating ideas, and enhancing overall writing proficiency. However, a lack of consensus is evident, with varied responses and inflated standard deviations suggesting differing opinions among respondents. Subjective norms play a crucial role in influencing students' decisions to use AI tools. Friends, colleagues, and lecturers significantly influence their perception and adoption of AI tools in academic writing. Although cautioned about excessive reliance, the influence of positive testimonials contributes to the widespread adoption of AI tools among postgraduate students. In terms of actual usage, the study reveals that postgraduate students frequently employ AI tools, primarily for idea development, spelling checks, paraphrasing, coherence, and searching for relevant literature. While some students appreciate the convenience and time-saving aspects of AI, others express concerns about potential detrimental effects on critical thinking and creativity. In conclusion, the research underscores the varied attitudes and usage patterns of postgraduate students regarding AI tools in academic writing. While many acknowledge the benefits, caution is advised to prevent overdependence and preserve critical thinking skills. The findings contribute valuable insights for educators and institutions seeking to integrate AI tools effectively into postgraduate education.

Higher education institutions throughout the world are challenged by the influx of Artificial Intelligence (AI) tools into education. Hence, the awareness and use of AI tools in education among the educators and students in higher education and their perspectives about AI are crucial and essential. This chapter comprised of a study exploring the awareness, use and perspectives on AI among educators and students in some government and private sectors of higher education. An average number of educators and a vast number of students are aware and use emerging AI tools like ChatGPT or a similar application. Educators are divided on the views that AI tools are well known in the University. Students consider that AI tools are an essential tool for undergraduate students' success. Professional discussion on AI tools in education are suggested for educators in higher education and students' insights are important in planning teaching and learning activities

Generative artificial intelligence (AI) tools have sparked debates in the education sector prompting researchers to explore their desirability and potential in education. This paper acknowledges generative AI’s potential to support the delivery of teaching, learning and research in the higher education emphasising its ability to improve student writing quality as well as academic productivity, success rate, and independence. However, responsible use of these AI tools to support research is also crucial. Furthermore, the challenges associate with AI tool use, especially accessibility and usage in the African context, are recognised. For instance, ethical challenges relating to (mis)use of AI because no or inadequate policy regulations have been implemented. In addition, there are technical and structural challenges relating to connectivity, power outages, device access and technical know-how. Therefore, this paper aims to identify the opportunities and challenges associated with using AI tools to support research in African Higher Education classrooms. For the study, a qualitative systematic literature review was applied to two articles using thematic analysis from a final selection of 29 articles. Findings indicated that generative AI tools could enhance student writing skills and increase productivity. Additionally, they could lead to research autonomy, improved writing proficiency, quality, and academic throughput. Shortcomings included AI misuse, knowledge deficiencies, and infrastructural challenges preventing AI access. Additionally, inadequate regulations relating to using generative AI tools for learning and teaching were a further challenge. It is essential to address the ethical concerns, invest in skills development and promote equitable digital access, especially in Africa, where this is limited. In addition, the capability approach revealed how the digital divide limited the adoption of generative AI tools in Africa.

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.

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.

Artificial Intelligence (AI) tools can potentially revolutionize classroom practices. English as a Foreign Language or Second Language (EFL/ESL) classrooms in higher education (HE) are also privy to the transformative features of AI. However, there is limited research on Bangladeshi HE teachers’ AI usage in teaching. This study, recognizing this gap, investigates Bangladeshi English teachers’ experiences and perceptions of using AI tools at the tertiary-level English classes. Data were collected employing an open-ended qualitative survey distributed among 17 English teachers from various public and private universities in Bangladesh. A thematic analysis suggests that most participants regularly use Turnitin, ChatGPT, and Grammarly among other AI tools. While some teachers did not routinely integrate AI tools into classroom activities, most considered them an efficient auxiliary tool for improving writing, vocabulary, grammar, designing materials, and detecting plagiarism. The results also revealed teachers' concerns about their lack of AI readiness and students’ malpractices using AI such as cheating and disinclination towards critical thinking. Based on the findings, the researchers discovered that effective integration of AI tools in learning can occur through a balance of human-led and AI-led instructions. The study recommended the need for teachers’ capacity building and skills training as mediators for contextually relevant AI usage, predominantly in writing. Spectrum, Volume 18, June 2023: 89-100