AI for Mental Health Assessment: Opportunities, Challenge and Ethical Consideration

Abstract

This work is describing the analysis of mental health (MH) illness of a human is based on Artificial Intelligence (AI). Describe a mechanism for identifying, monitoring and recognizing MH disorders using different data driven method such as machine learning (ML), natural language processing (NLP), and wearables. These techniques are considerable potential for improving accessibility, scalability, and accuracy in MH analysis. This is especially important where traditional approaches do not work. Implementing AI in such a sensitive and complex field raises concerns about ethical responsibility, data privacy, transparency, and algorithmic bias. This paper critically reviews AI for the purpose of evaluating MH wellbeing. In this work we will examine technological applications, clinical applications, challenges, and key areas for the future. In the resent research, current case studies, and interdisciplinary perspectives, it can be presents an argument for a balanced, human centered approach. That leverages the strengths of AI while retaining the fundamental principles of psychological practice. Therefore, with the help of data sets and larger sample sizes, evaluating different AI models used in MH care across districts is warranted to fill the current information gap in forthcoming comparative studies. AI technologies could help address some issues, concluded influential analytical models, intelligent dialogue, and language study with different users. However, the unexplored area is these studies. AI simplifies the application of more dedicated intrusions and modified handling strategies.

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