Transforming academic integrity in the face of wide access to generative artificial intelligence

Abstract

The article provides a comprehensive analysis of the transformation of the concept of academic integrity in the context of the widespread use of generative artificial intelligence (GAI). The primary objective is to develop scientifically sound approaches and recommendations for the effective adaptation of the education system to the new challenges and opportunities emerging in this context. Methods. Theoretical methods, such as analysis and synthesis, as well as empirical methods, including observation and description, were employed. The analysis of modern language models (GPT-3, GPT-4, LaMDA, LLaMA, BLOOM), generative adversarial networks (DALL-E, Midjourney, StableDiffusion), and other technologies has allowed us to identify key challenges to academic integrity. Observation of the use of GAI in the educational process helped to systematize the ethical dilemmas and risks associated with its application. Results. It was found that academic integrity is a shared responsibility between teachers and learners in the context of implementing AI in education. It has been demonstrated that AI enables the individualization of learning by automating the writing of academic papers, but also generates risks, such as plagiarism and dependence on innovations, which can negatively impact the motivation for independent work and the development of academic competencies among education seekers. In addition, digital technologies are changing traditional ideas about academic integrity, presenting new ethical challenges, particularly regarding the determination of authorship. Under these conditions, teachers should serve as mentors, teaching learners to critically evaluate the results of using AI and establish new educational standards for transparency in the use of technologies. Recommendations for the ethical use of AI include reviewing integrity policies, developing rules for its application, and requirements for disclosing the contribution of AI to academic works. Conclusions. It was found that the integration of AI into the educational process changed approaches to assessing learner knowledge, transformed forms of cooperation between teachers and education seekers, and also emphasized the need to implement ethical principles of integrity when using technology in education.