Intelligence Émotionnelle Artificielle: Applications en Psychologie et Perspectives Futures

This article examines the emergence of Artificial Emotional Intelligence (AEI) in psychology, an interdisciplinary field integrating deep learning, natural language processing, and affective computing. It explores its promising applications—such as therapeutic chatbots and predictive diagnostic tools—to democratize access to mental healthcare and personalize interventions. Major challenges, including interpreting cultural nuances, managing algorithmic biases, safeguarding sensitive data, and limitations in replicating human empathy, are critically analyzed. The study emphasizes the need for transdisciplinary collaboration (psychology, engineering, ethics) to guide its deployment, validate clinical efficacy, and preserve the integrity of therapeutic practices. Finally, AEI is framed as a technological adjunct to traditional methods, enhancing—without replacing—human interactions central to psychological care.

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Publication Details

Journal
International Journal of Humanities Education and Social Sciences
Published
2025-04-17
DOI
https://doi.org/10.58578/ijhess.v3i2.5399
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

Intelligence Émotionnelle Artificielle: Applications en Psychologie et Perspectives Futures

Hicham Brir
International Journal of Humanities Education and Social Sciences
Intelligent Tutoring Systems and Adaptive Learning
article

Intelligence Émotionnelle Artificielle: Applications en Psychologie et Perspectives Futures

Hicham Brir
article en

Abstract

This article examines the emergence of Artificial Emotional Intelligence (AEI) in psychology, an interdisciplinary field integrating deep learning, natural language processing, and affective computing. It explores its promising applications—such as therapeutic chatbots and predictive diagnostic tools—to democratize access to mental healthcare and personalize interventions. Major challenges, including interpreting cultural nuances, managing algorithmic biases, safeguarding sensitive data, and limitations in replicating human empathy, are critically analyzed. The study emphasizes the need for transdisciplinary collaboration (psychology, engineering, ethics) to guide its deployment, validate clinical efficacy, and preserve the integrity of therapeutic practices. Finally, AEI is framed as a technological adjunct to traditional methods, enhancing—without replacing—human interactions central to psychological care.

International Journal of Humanities Education and Social SciencesVol. 3(2)
Université Ibn-Tofail (MA)
Openalex Percentile: Top 97%
Intelligent Tutoring Systems and Adaptive Learning
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