Student Mental Health Monitoring Based on Artificial Intelligence and Emotion Recognition: Legal Risks and Regulatory Paths
Pengfei WangAbstract
Objective
Students face growing psychological pressure, with unstable mental states and potential mental health risks becoming increasingly prominent. AI and emotion recognition technologies are widely used in student mental health monitoring, bringing convenience to mental health intervention. This study explores legal risks in the monitoring process and proposes regulatory paths, aiming to protect students’ mental health and privacy while ensuring scientific monitoring of their mental state and psychological pressure.
Subjects and Methods
Taking AI-based student mental health monitoring systems and 70 students with different psychological pressure levels as subjects, this study combs relevant laws and regulations, uses questionnaire surveys and case analysis, investigates the application status of monitoring technologies, and analyzes legal risks related to mental health data collection, emotion recognition and mental state evaluation.
Results
AI and emotion recognition effectively identify students’ psychological pressure and abnormal mental states, providing timely early warning for mental health intervention. However, the monitoring process has obvious legal risks, including privacy infringement, improper use of mental health data, and inaccurate emotion recognition affecting mental health evaluation and students’ mental state.
Conclusions
AI and emotion recognition play a positive role in student mental health monitoring and psychological pressure early warning. Legal risks in the monitoring process seriously affect students’ legitimate rights and mental health protection. Improving relevant laws, clarifying technical application standards and establishing supervision mechanisms can effectively resolve risks, ensuring the healthy development of student mental health monitoring.
Corresponding Author
Pengfei Wang, Northwest University of Political Science and Law, Xi'an, 710122, China.