Contracting for Artificial Intelligence

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.

Objective: To explore the perception of university students on the use of Artificial Intelligence (AI) tools for the development of autonomous learning. Theoretical Framework: The research is based on Technological Acceptance Theory and Constructivism, focusing on the perception of AI in autonomous learning of university students. Method: Quantitative approach with a descriptive scope, the sample consisted of 665 students enrolled in the Faculty of Education Sciences and Languages (FCEI) of the Peninsula de Santa Elena State University (UPSE)-Ecuador; in the collection of information, the Questionnaire of Perception on the Use of Artificial Intelligence for Autonomous Learning was designed based on 4 dimensions of both variables, and the statistical program SPSS version 29 was used for data processing. Results and Discussion: The results indicate that students show a favorable perception towards the use of AI tools for the autonomous learning process, however, although AI is recognized as a potential tool in university environments, there are still challenges to be overcome. Research Implications: The study has practical implications for strengthening in students the digital competencies needed to effectively use AI tools in their autonomous learning. Originality/Value: The research provides data on the perception of AI tools among university students, offering a starting point for future technology integration strategies in universities.

Technical English (TE) proficiency is crucial for the future careers of polytechnic students. While Artificial Intelligence (AI) tools offer significant potential to enhance language learning, their effectiveness relies on student acceptance and use. There is limited understanding of what drives polytechnic students to adopt these tools specifically for TE. This study aims to identify the key factors influencing polytechnic students' acceptance and use of AI tools in this context and employ a quantitative approach based on the Technology Acceptance Model (TAM) and Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze survey data collected from 100 Polytechnic Kota Bharu (PKB) students enrolled in TE courses. The research investigates core antecedents, primarily perceived usefulness (PU) and perceived ease of use (PEOU), and their impact on students' behavioral intention (BI) to use AI tools. The potential influence of external factors such as social influence and lecturer support are examined. The study found PEOU was identified as a critical antecedent, which significantly positively affected PU and BI. The study reaffirmed the significant predictive power of BI on AU, indicating that students' stated intentions reliably translate into their subsequent usage behaviour. This research will offer practical recommendations for educators seeking to integrate AI tools effectively into TE instruction. Theoretically, this study contributes to understanding technology adoption within the specific domain of technical and vocational language education, providing valuable insights for leveraging AI to improve essential communication skills for aspiring technical professionals.

Introduction: The availability and use of artificial intelligence (AI) tools is accelerating significantly. As these technologies proliferate, many post-secondary institutions have responded by banning students from using AI tools such as ChatGPT and framing the conversation as breaches of academic integrity. Background: Despite these institutional responses, many students adopt these tools as part of their learning journey. In health care settings, the adoption of such tools in the context of patient care provision is a reality. Consequently, there is a relevant pedagogical opportunity to examine how such tools inform the experiential learning of nursing students and their future practice. Methods: To address the dearth of information regarding nursing students’ perceptions of using AI tools, a Canadian university teaching team incorporated ChatGPT into an undergraduate nursing course assignment. A pilot quasi-experimental pre-post-test survey design was employed to examine student perceptions of using ChatGPT. After obtaining institutional ethics approval, a neutral third party collected the anonymous data. Findings: Pilot study results highlighted significant student concerns regarding the ethics of using AI tools. Additionally, students described such tools as meaningful avenues to support learning access and equity. Finally, students identified a high probability of use of AI tools in their future practice, suggesting that exposure and support during learning can positively influence responses to these tools in practice settings. Conclusion: The students surveyed are now practising nurses; thus, findings may provide insight into perceptions of new nurses regarding the integration of AI to support competencies required by the nurses of tomorrow.

This study empirically investigates the use of artificial intelligence (AI) tools within Hungarian religious communities, with a focus on Catholic respondents, to assess their awareness, application, and acceptance of AI in religious contexts. By religious communities, we do not mean monastic or priestly communities, but rather communities of lay religious people. Conducted between 10 February and 11 March 2025, the questionnaire-based research (N = 133) employs Campbell’s Religious Social Shaping of Technology (RSST) framework to analyze attitudes toward AI across 15 religious functions. Six hypotheses explore gender differences, religiosity types (church-based vs. self-defined), and the acceptability, authenticity, and ethicality of AI applications. Findings reveal high acceptance for administrative tasks (e.g., email list updates: 64.7%) and technical functions (e.g., live translation: 65.4%), but low acceptance for spiritual roles (e.g., spiritual leadership: 12.8%). Self-defined religious individuals are significantly more accepting, perceiving AI as more authentic and ethical compared to those adhering to church teachings. No significant gender differences were found. The study contributes to digital religion studies, highlighting the influence of religiosity on AI adoption, though its non-representative sample limits generalizability.

Will ChatGPT undermine ethical values in nursing education, research, and practice?

This paper considers the combination of Artificial Intelligence (AI) and the IT project management field of project management risk in the context of Management Information Systems (MIS). In IT projects, risks are identified, analyzed, and responded to with varying degrees of efficiency. This study explores the use of AI tools (including machine learning regression and neural networks) to improve the processes of AI-enhanced tools integrated into established risk management processes. Improved decision-making capabilities are the result. Performance evaluation tools such as Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) as well as measures of precision, recall and the F1 score were the metrics of the study to measure the efficiency and effectiveness of AI as contrasted with the AI tools and the implementation of traditional risk systems management. AI, with respect to risk management, traditional, and non-AI systems, risk systems management design, measures, time, project success, and overall outcome, significantly AI MIS and risk management project are realized. AI systems, project management tools, and human cooperation, in project deliverables, management timely project streamline outcomes management is more project completion are combined with MIS. This paper considers project risk management and the use of project management AI tools in an organizational context

Integrating artificial intelligence (AI) technologies into academic writing presents opportunities and challenges, as use of AI promotes efficiency in knowledge production but also exacerbates existing disparities between developed and developing nations, with developing nations lagging behind in terms of access and the expertise for using them productively. Moreover, while AI tools provide support for innovative research, writing assistance, and data analysis, there are growing concerns about the quality of postgraduate student theses and publications, written using AI tools, as they contain false statements and violate research ethics. Based on survey data and secondary literature, this study investigated the current application of AI tools in academic writing by Humanities and Social Science postgraduate students in a Kenyan university. The study aimed to: establish the uptake and use of AI tools in academic writing, assess student attitudes on using AI tools in academic writing; and explore challenges influencing the use of AI tools in academic writing. The study revealed that students often use AI tools that generate content, provide analysis and paraphrase texts, such as chatGPT, Gemini Grammarly and Quillbot. Students had positive attitudes to adopting AI tools for academic writing, however, they reported limitations in proficient use of AI tools, poor writing and research skills, along with lack of ICT resources and AI tools. It is recommended that for effective integration of AI tools in academic writings, higher education institutions should provide ICT resources, AI tools and offer training in research skills, writing skills and use of AI tools for writing.

This study examines pre-service English language teachers’ grounds and connections between the use of generative Artificial Intelligence (AI) tools in EFL writing skills and future prospects to integrate them into their teaching practices. Employing a qualitative research paradigm, a researcher-developed survey was used to elicit the perspectives of 28 pre-service English language teachers and 10 teacher trainers. The stages of qualitative data analysis were followed, emergent ideas embedded in the responses were labeled and the codes were clustered into broader themes to obtain a description of their reflections. This study documented reflections on the transformative impact of generative AI in EFL writing. Benefits were reported considering the use of AI tools to overcome writer’s block and get language support, and instantaneous and personalized feedback to the texts. Foregrounding concerns regarding academic misconduct, a need was highlighted for ethical guidelines and enhancement to AI literacy to ensure the validity of AI-generated content. Further, they suggested reformulating assessment and evaluation in EFL writing skills and moving away from result-oriented exams suggesting the adoption of performance-based and process-oriented assessments. Accordingly, ethical and pedagogical implications were offered to adopt a critical stance to improve AI literacy skills in EFL writing development.

This study aims to develop kindergarten children's oral communication skills through a proposed educational unit based on the use of generative artificial intelligence tools. To achieve this, the researcher created a list of appropriate oral communication skills for kindergarten children and presented it to a group of specialized professors in the fields of Arabic language, kindergarten, and early childhood for review and finalization, A proposed educational unit was then designed to develop these skills through various activities. It relied on multiple teaching and learning strategies, most notably stories, songs, and games. The study followed a descriptive approach in presenting the proposed unit and defining its topics, objectives, and activities, as well as in clarifying the generative artificial intelligence tools used in its construction, The study yielded a number of recommendations, most notably: the need to train kindergarten teachers on how to employ artificial intelligence tools in education to facilitate their tasks. The study also proposed future research, including designing educational units based on the use of artificial intelligence tools to develop kindergarten

The purpose of this research is to understand the challenges, opportunities, and implications associated with the design and use of Artificial Intelligence (AI) tools to preserve the native Quechua language in Peru. To do so, we conducted a theoretical analysis regarding how AI could be applied to protecting Quechua. We also interviewed two Quechua speakers, an expert in the Quechua language, and two experts in language localization and translation. The purpose of the interviews was for the interviewees to express their opinions on the potential design and use of AI tools in the conservation of Quechua; considering the challenges, opportunities, and implications that this would have. The conclusion is that Quechua is one of the vital languages in Peru that helps maintain the social and cultural traditions of the country; it is necessary to maintain this state of vitality through various means. And, although technological projects for its preservation have been undertaken at the state level, these have not had a great impact on the population because the technologies created have not been attractive or dynamic for the dissemination and learning of the Quechua language.

Despite constant increase in the use of Artificial Intelligence tools in educational settings, nothing is known about students’ personality traits associated with the use of these resources. Thus, the objective of this study was to explore possible links between Artificial Intelligence use and personality traits among university students. A cross-sectional ex-post facto quantitative study was conducted with 1761 undergraduate students (Mage = 20.30; SD = 2.76). Validated questionnaires were administered for data collection, always under the supervision of members of the research team. According to multinomial regression analysis, neuroticism and extraversion were related to sporadic use and frequent use, respectively. Agreeableness increased the odds of using Artificial Intelligence to solve every day doubts and neuroticism to do academic work. Conscientiousness was negatively related to the use of Artificial Intelligence to do academic work and to create fake content. Higher scores in openness increased the likelihood of creating fake content using Artificial Intelligence. These results provide novel information about personal characteristics associated with the use of Artificial Intelligence tools among university students. Educators should consider this information when implementing Artificial Intelligence into their educational strategies.

Purpose: Artificial Intelligence (AI) is playing an increasingly important role in various areas of life, including higher education. The aim of this article is to assess the level of use of AI tools by students during academic classes and independent learning. It analyzes which available AI tools are used by students in the higher education system. The article also discusses the essence and role of AI development in the context of academic learning. Need for the study: Modern methods and tools of education may be insufficient in the process of educating students. There is a need to search for and offer modern educational tools such as the use of artificial intelligence, which can support academic institutions in monitoring and improving educational processes. Artificial Intelligence tools can contribute to more effective learning and achieving success. Methodology: Research study of students of the University of Szczecin who completed three surveys. The analyzed results concerned their use of the AI tool. You can use Python 3.12 and Pandas libraries Findings: The data obtained indicate that students are increasingly willing to use AI tools, but they have limited trust in them. The results suggest that AI should be a tool supporting student education processes. Practical Implications: AI is influencing the way students teach and learn, and its role in higher education is becoming increasingly important. Effective implementation of AI will require appropriate didactic preparation and a well-thought-out implementation strategy at the level of academic institutions.

This paper discusses the integration of artificial intelligence (AI) tools in education, delineating their potential to transform pedagogical practices alongside the challenges they present. Generative AI models like ChatGPT, had a disruptive impact on teaching and learning, due to their ability to create text, images, and sound, revolutionizing educational content creation and modification. However, nowadays the educational community is polarized, with some embracing AI for its accessibility and efficiency thus advocating it as an indispensable tool, while others cautioning against risks to academic integrity and intellectual development. This document is designed to raise awareness about AI tools and provide some examples of how they can be used to improve education and learning. From an educator’s perspective, AI is an asset for curriculum development, course material preparation, instructional design and student assessment, while reducing bias and workload. For students, AI tools offer personalized learning experiences, timely feedback, and support in various academic activities. The Turkish Biochemical Society (TBS) Academy recommends educators to embrace and utilize AI tools to enhance educational processes, and engage in peer learning for better adaptation while maintaining a critical perspective on their utility and limitations. The transfer of AI knowledge and methods to the teaching experiences should complement and not replace the educator’s creativity and critical thinking. The paper advocates for an informed embrace of AI, AI fluency among educators and students, ethical application of AI in academic settings, and continuous engagement with the evolving AI technologies, ensuring that AI tools are used to augment critical thinking and contribute positively to education and society.

The rapid advancements in artificial intelligence (AI) have significantly transformed various domains, including education, by introducing innovative tools that reshape teaching and learning processes. This research investigates the perceptions and attitudes of students towards the use of AI tools in their academic activities, focusing on constructs such as perceived usefulness, the perceived ease of use, security and privacy concerns, and both positive and negative attitudes towards AI. On the basis of Technology Acceptance Model (TAM) and the General Attitudes towards Artificial Intelligence Scale (GAAIS), this research seeks to identify the factors influencing students’ behavioral intentions and actual adoption of AI tools in educational settings. A structured survey was administered to students at Multimedia University, Malaysia, capturing their experiences and opinions on widely used AI tools such as ChatGPT, Quillbot, Grammarly, and Perplexity. Hypothesis testing was used to evaluate the statistical significance of relationships between the constructs and behavioral intention and actual use of the AI tools. The findings reveal a high level of engagement with AI tools among University students, primarily driven by their perceived benefits in enhancing academic performance, improving efficiency, and facilitating personalized learning experiences. The findings also uncover significant concerns related to data security, privacy, and the potential over-reliance on AI tools, which may hinder the development of critical thinking and problem-solving skills.