There are few current issues in education that have provoked more interest – or sounded more alarms – than artificial intelligence (AI) technology. While the issue has simmered for some time, it burst into the forefront of debate following OpenAI’s public release of ChatGPT. When given a prompt – e.g. “What were the causes of World War I?” or “How does the Krebs cycle work?” – ChatGPT (the acronym stands for “Generative Pretrained Transformer”) can generate text that reads, at least on superficial examination, like that written by a human – the basis of the famed Turing Test for machine intelligence.

Once the tool’s capabilities became known, it did not take long for fears to be voiced that students would turn to ChatGPT to write their assignments for them. Eye-grabbing headlines began to appear, not only in sensationalist newspapers like the New York Post (which dubbed the tool “CheatGPT”) but in more sober publications like the Atlantic, where an opinion piece bluntly claimed that “the college essay is dead”. Advocates for the worst-case scenario see a future in which human-generated and computer-generated text are indistinguishable, essay assignments are meaningless, and the very skill of academic writing is lost.

One need not accept this doomsday proposition to recognize that ChatGPT raises legitimate concerns for academic integrity. But if we are to address such concerns, we must first answer several key questions: what is ChatGPT, exactly? What are its affordances and limitations? And, assuming that ChatGPT and tools like it are here to stay (as seems overwhelmingly likely), how should we rethink pedagogy to address this new reality?

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.

The Framework is grounded in a shared vision of ethical Al in education and will help to enable all learners to benefit optimally from Al in education, whilst also being protected against the risks this technology presents. The Framework is aimed at those making procurement and application decisions relevant to AI in education.

Leaders and practitioners in educational settings are themselves key to ensuring that learners can benefit optimally from Al whilst being protected against its risks because it is they who have the final say over which resources are used. By using the Framework at the procurement stage, decision makers can help ensure that only ethically designed resources are used and procured, and can therefore ideally incentivise suppliers to design Al ethically and with learners' best interests at heart.

The Framework empowers leaders and practitioners to drive the design, procurement and application of AI on behalf of learners. But it cannot and must not be solely their responsibility to ensure that learners benefit optimally from Al in education. Those designing Al resources are ultimately responsible for ensuring that systems do not, amongst other things, discriminate against any group of learners, that they do not manipulate users, and that resources are designed in a pedagogically sound way.

Artificial Intelligence (AI) tools are constantly being released into the public domain. As with all new technological innovations, this brings a range of opportunities and challenges for education: primarily for educators and learners. There is an increasing interest in the academic community and beyond to use Artificial Intelligence in Education (AIED) to generate content. This presents opportunities and challenges for academic and research integrity.

The European Network for Academic Integrity (ENAI) is an international association gathering educational institutions and individuals interested in maintaining and promoting academic integrity. As the use of AI tools may not always be consistent with academic integrity, we consider it important to familiarise all education stakeholders with how to use AI tools responsibly and in accordance with academic integrity practices and values.

ENAI presents a set of recommendations with the aim of supporting academics, researchers and other educational stakeholders, including students’ organisations, on the ethical use of AI tools. The recommendations focus on the importance of equipping stakeholders with the skills and knowledge to use AI tools ethically and the need to develop and implement relevant educational policies addressing the opportunities and challenges posed by AIED.

The advancement of artificial intelligence in education (AIED) has the potential to transform the educational landscape and influence the role of all involved stakeholders. In recent years, the applications of AIED have been gradually adopted to progress our understanding of students’ learning and enhance learning performance and experience. However, the adoption of AIED has led to increasing ethical risks and concerns regarding several aspects such as personal data and learner autonomy. Despite the recent announcement of guidelines for ethical and trustworthy AIED, the debate revolves around the key principles underpinning ethical AIED. This paper aims to explore whether there is a global consensus on ethical AIED by mapping and analyzing international organizations’ current policies and guidelines. In this paper, we first introduce the opportunities offered by AI in education and potential ethical issues. Then, thematic analysis was conducted to conceptualize and establish a set of ethical principles by examining and synthesizing relevant ethical policies and guidelines for AIED. We discuss each principle and associated implications for relevant educational stakeholders, including students, teachers, technology developers, policymakers, and institutional decision-makers. The proposed set of ethical principles is expected to serve as a framework to inform and guide educational stakeholders in the development and deployment of ethical and trustworthy AIED as well as catalyze future development of related impact studies in the field.