Abstract
In the context of the rapid development of artificial intelligence, the neural networks became part of the educational process, providing opportunities for personalization of training, processing large data arrays and solving routine problems. In this case, there is a need for philosophical reflection aimed at identifying the deep consequences of the technologicalization of education. Attention is focused on whether the neural networks really change our ideas about knowledge. In the context of the theory of social relayers, the specificity of knowledge generated by neuralities is analyzed. The traditional understanding of knowledge based on experience and creative rethinking is opposed to the algorithmic representation of data from neural networks, devoid of intentionality and metacognitive abilities inherent in a person as a participant in many social programs. The introduction of neural networks in the university education system also gives rise to a series of ethical issues. Neural networks remain an instrument, the use of which can lead to increased utilitarianism in teaching and weakening of students' interest in independent intellectual work. Existing risks of standardization and automation of the educational process, leading to the loss of the unique role of the teacher and a decrease in the significance of the student’s personal experience, are subject to assessment. The preservation of the humanistic measurement of education requires the development of ethical norms that regulate the use of neural networks and ensure the balance between technological resources and educational values.
Keywords
- education
- neural networks
- knowledge
- learning
- information
- philosophy
- ethical issues
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