Штучний інтелект як виклик академічній доброчесності: етичний вимір освітньої відповідальності

Abstract

У статті проаналізовано етичні виклики, що постають у зв‟язку з інтеграцією штучного інтелекту (ШІ) в освітній процес. Наголошено на необхідності переосмислення академічної доброчесності в умовах цифрової трансформації освіти. ШІ розглядається як фактор, що одночасно розширює можливості навчання та створює ризики академічної безвідповідальності. Увагу зосереджено на формуванні етичних стандартів, педагогічного супроводу й інституційних політик для забезпечення відповідального використання ШІ. Обґрунтовано важливість розвитку цифрової етики, критичного мислення та усвідомленого авторства учасників освітнього процесу.

Introduction. The rapid development and widespread adoption of artificial intelligence (AI) technologies in educational environments have significantly transformed traditional conceptions of academic integrity. The use of generative AI tools such as ChatGPT and similar services is reshaping the way students complete academic assignments, introducing new challenges related to authorship, independence, and ethical responsibility. The absence of clearly defined normative-ethical frameworks and pedagogical strategies for implementing such technologies in education complicates the maintenance of academic integrity standards. This situation calls for a conceptual rethinking of the ethical foundations of education in the digital age. Purpose. This study aims to conduct a comprehensive analysis of how AI tools affect academic integrity in higher education, with a specific focus on the ethical dimension of educational responsibility. The study seeks to identify ethical risks associated with the use of AI in academic contexts, to examine existing pedagogical practices, and to propose directions for establishing institutional mechanisms for the ethical application of AI technologies. Methods. The research employs a systematic analysis to generalize approaches to academic integrity in digital contexts, a comparative-analytical method to examine international and national experiences with AI implementation in education, content analysis of scholarly publications, policy documents, and institutional guidelines, and an interpretive analysis of ethical practices in the educational sphere. Results. The findings indicate that the impact of AI on educational processes is not uniformly positive or negative. On the one hand, AI technologies facilitate personalized learning, broaden access to educational resources, and support academic success–particularly for students from socially disadvantaged groups. On the other hand, they present risks of academic misconduct, undermine the principles of authorship, and weaken the development of critical thinking and independent intellectual work. Most educational institutions lack clearly defined ethical frameworks or internal regulations governing the use of AI. Moreover, existing AI-detection tools are limited in accuracy and general applicability. Academic integrity is therefore proposed to be viewed as a dynamic ethical practice requiring adaptation to digital conditions and emerging forms of interaction with information technologies. Originality. The originality of this study lies in its focus on the ethical dimension of AI use in academic contexts. The author suggests interpreting academic integrity not merely as a set of formal rules but as an interconnected system of ethical behavior shared between educators and students within the framework of digital transformation. For the first time, this study outlines the correlation between levels of digital culture, critical thinking skills, and the degree of adherence to academic integrity in the context of AI usage. A novel approach is proposed to distinguish supportive AI usage from violations of academic standards, based on the principles of transparency, openness, and authorial responsibility. Conclusion. In contemporary education, AI should be regarded as a tool that requires ethical oversight. The development of institutional policies that regulate the acceptable use of AI in teaching, learning, and research is essential for maintaining academic integrity. The study proposes the following measures: the implementation of institutional guidelines for ethical AI usage; the enhancement of digital literacy and critical thinking among educational stakeholders; the development of transparent procedures for attributing AI-generated content in academic work; the integration of automated control tools with expert evaluation; and the support of pedagogical strategies that cultivate responsible engagement with AI. These steps are crucial for shaping a new academic culture capable of meeting the ethical challenges of the digital era.