authors: Andrew Rutkas, Tetiana Korobkina
Abstract.
Relevance of the research. This study examines the impact of artificial intelligence (AI) on education for Generation Beta—children born after 2025, whose cognitive and social traits are shaped by digitalization and transhumanist concepts. The rapid advancement of AI and neural networks necessitates adapting pedagogical methods to meet the needs of this generation, characterized by clip-like thinking and intuitive technology use. The research is relevant due to the need for flexible educational models that address the challenges of the digital era.
Problem statement. The research problem focuses on identifying optimal ways to integrate AI technologies into education, considering the mental and cognitive characteristics of Generation Beta. Key challenges include modernizing education, ensuring accessibility, fostering digital competencies, and addressing ethical issues related to automation and data privacy.
Analysis of recent research and publications. McCrindle and Fell introduced the concept of Generation Beta, highlighting its digital characteristics. Bostrom explores transhumanist perspectives on technology-driven cognitive enhancement. Luckin et al. propose personalized learning through AI, particularly via Intelligent Tutoring Systems (ITS). Jordan and Mitchell discuss AI’s potential in data processing, while Selwyn warns of risks from over-automation. Unresolved issues include digital divide and balancing technology with traditional methods.
Research task. The article aims to analyze Generation Beta’s traits, evaluate AI’s role in transforming education, and assess ethical challenges of transhumanist technologies. Objectives include studying cognitive characteristics, analyzing AI applications, evaluating ethical risks, and proposing pedagogical models.
Main material presentation. Generation Beta exhibits clip-like thinking and virtual socialization, requiring adaptive teaching methods. Artificial Intelligence personalizes learning by tailoring content to cognitive needs. Transhumanist technologies, such as neurointerfaces, offer new opportunities but raise ethical concerns about accessibility and privacy. Human interaction remains crucial for social skills development.
Conclusions. Education for Generation Beta should be interactive and adaptive. AI enhances personalization but requires ethical oversight. Future research should explore AI platform efficacy, psychological impacts, and regulatory frameworks.
Keywords: Generation Beta, artificial intelligence, education, transhumanism, adaptive learning, AI ethics, digital divide.
References:
- Bostrom, N 2005, ‘A history of transhumanist thought’, Journal of Evolution and Technology, 14(1), pp. 1–25.
- Fadel, C, Holmes, W & Bialik, M 2019, Artificial intelligence in education: Promises and implications for teaching and learning, Boston: Centre for Curriculum Redesign.
- Bommasani, R, Hudson, DA, Adeli, E, Altman, R, Arora, S et al., 2021, On the Opportunities and Risks of Foundation Models, Stanford, CA: Center for Research on Foundation Models, Stanford University. 212 p. Available from: <https://arxiv.org/abs/2108.07258v3>. [28 Jun 2025].
- Jordan, MI & Mitchell, TM 2015, ‘Machine learning: Trends, perspectives, and prospects’, Science, 349 (6245), pp. 255–260.
- Luckin, R, Holmes, W, Griffiths, M & Forcier, LB 2016, Intelligence unleashed: An argument for AI in education. London: Pearson Education.
- Mangera, E, Supratno, H & Suyatno, 2023, ‘Exploring the relationship between Transhumanist and Artificial Intelligence in the Education Context: Particularly Teaching and Learning Process at Tertiary Education’, Pegem Journal of Education and Instruction, 13(2), pp. 35–44.
- McCrindle, M & Fell, A 2020, Generation Alpha: Understanding our children and helping them thrive. Sydney: Hachette Australia.
- Roll, I & Wylie, R 2016, ‘Evolution and revolution in artificial intelligence in education’, International Journal of Artificial Intelligence in Education, 26(2), pp. 582–
- Rutkas, AA 2024, ‘Normalized Difference Model of the Descriptor Control System’, In: Proceedings of the 13th International Scientific and Technical Conference, Part 1, Information Systems and Technologies IST-2024, 26-28 November, 2024, Kharkiv, Ukraine, pp. 29-34.
- Selwyn, N 2019, Should robots replace teachers? AI and the future of education. Cambridge UK: Polity Press.
- Yousef, AMF, Chatti, MA, Schroeder, U & Wosnitza, M 2014, ‘The state of video-based learning: A review and future perspectives’, International Journal on Advances in Life Sciences, 6(3-4), pp. 122–135.
