EMOTIONAL INTELLIGENCE IN MACHINES: CAN AI CULTIVATE EMPATHY?

In the context of rapid digitalization and transformation of educational practices, there is a need to rethink the role of artificial intelligence in pedagogy. If in the first wave of digitalization, AI was considered primarily as a cognitive tool for automation and optimization of learning, then at present a new vector is being actualized - the study of its affective potential. Of particular importance is the question: is AI, deprived of its own emotional nature, capable of participating in the formation of such key competencies of the 21st century in humans as empathy, emotional regulation and social sensitivity? The article is devoted to the analysis of the concept of emotional intelligence of machines and consideration of AI not only as an intermediary in the transfer of knowledge, but also as an agent of the educational process. The novelty of the study lies in the integration of theories of emotional intelligence with modern developments in the field of affective computing, which allows us to propose an interdisciplinary model of “empathic AI pedagogy.” This model assumes a transition from traditional cognitive digitalization to “affective education,” where emotional AI becomes an accomplice in the development of the student’s personality. The article examines in detail the technological foundations of emotional AI: emotion recognition systems based on voice, facial expressions and behavioral signals; mechanisms for synthesizing empathically colored text and speech; multimodal architectures that combine cognitive and affective models of interaction. It is shown that the integration of such solutions into educational platforms opens up opportunities for supporting student motivation, reducing anxiety, developing empathy and developing soft skills. The practical significance of the study is that it offers conceptual guidelines for state educational policy, training of teachers to work with emotional AI, and international cooperation in the development of standards for affective education.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-15
DOI
https://doi.org/10.5281/zenodo.17213636
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
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article

EMOTIONAL INTELLIGENCE IN MACHINES: CAN AI CULTIVATE EMPATHY?

Zenodo (CERN European Organization for Nuclear Research)
Geochemistry and Geologic Mapping
article

EMOTIONAL INTELLIGENCE IN MACHINES: CAN AI CULTIVATE EMPATHY?

article en

Abstract

In the context of rapid digitalization and transformation of educational practices, there is a need to rethink the role of artificial intelligence in pedagogy. If in the first wave of digitalization, AI was considered primarily as a cognitive tool for automation and optimization of learning, then at present a new vector is being actualized - the study of its affective potential. Of particular importance is the question: is AI, deprived of its own emotional nature, capable of participating in the formation of such key competencies of the 21st century in humans as empathy, emotional regulation and social sensitivity? The article is devoted to the analysis of the concept of emotional intelligence of machines and consideration of AI not only as an intermediary in the transfer of knowledge, but also as an agent of the educational process. The novelty of the study lies in the integration of theories of emotional intelligence with modern developments in the field of affective computing, which allows us to propose an interdisciplinary model of “empathic AI pedagogy.” This model assumes a transition from traditional cognitive digitalization to “affective education,” where emotional AI becomes an accomplice in the development of the student’s personality. The article examines in detail the technological foundations of emotional AI: emotion recognition systems based on voice, facial expressions and behavioral signals; mechanisms for synthesizing empathically colored text and speech; multimodal architectures that combine cognitive and affective models of interaction. It is shown that the integration of such solutions into educational platforms opens up opportunities for supporting student motivation, reducing anxiety, developing empathy and developing soft skills. The practical significance of the study is that it offers conceptual guidelines for state educational policy, training of teachers to work with emotional AI, and international cooperation in the development of standards for affective education.

Zenodo (CERN European Organization for Nuclear Research)
ArcelorMittal (Canada) (CA), Karaganda State Industrial University (KZ)
Quality Education
Openalex Percentile: Top 26%
Geochemistry and Geologic Mapping
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