Analysis reveals AI technologies like ChatGPT present both opportunities and ethical risks in education.
The article examines the impact of artificial intelligence (AI) technologies on the global higher education system. To illustrate this impact, the author analyzes the phenomenon of ChatGPT, highlighting various opportunities and challenges currently facing the higher education sector in the context of its application. Specific examples of AI technology usage are considered, including idea generation, essay writing, and even exam composition. Particular attention is given to assessing the potential of this technology, specific cases of its implementation, and the response of educational institutions to the spread of ChatGPT. The article identifies risks associated with possible unethical or careless applications of this technology in education. The perspectives of international experts on potential limitations and biases related to ChatGPT usage are analyzed in detail. Ethical risks are emphasized, particularly the possibility of reinforcing biases and deepening social inequality through AI technologies. Various ethical challenges are presented as examples. The author provides a forecast regarding the future development of higher education in a society increasingly permeated by AI technologies. Potential risks and trends in AI development within the educational process are explored. The article reviews possible changes in everyday university practices, transformations in teaching methods and content, as well as shifts in assessment methods and ethical standards influenced by AI. The conclusion underscores the necessity of developing skills essential for effective interaction with AI technologies, as well as skills that compensate for their limitations, including critical thinking, fact-checking, and creativity. The article conceptualizes the strategic choice facing universities: whether to resist the influence of AI technologies in education or to embrace this new reality, positioning themselves as leaders in its implementation and adaptation.
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Marko Aharkov (2023) studied this question.
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