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Ethical AI in Psychiatric Care: Balancing Compassion and Computational Intelligence for Employee Well-Being
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Author(s): Saurabh Chandra (Bennett University, Greater Noida, India), Bhupinder Singh (Sharda University, India), Kittisak Wongmahesak (North Bangkok University, Thailand)and Santosh Kumar (Sharda University, India)
Copyright: 2025
Pages: 22
Source title:
Prioritizing Employee Mental Health and Well-Being for Organizational Success
Source Author(s)/Editor(s): Kittisak Wongmahesak (North Bangkok University, Thailand), Roy Rillera Marzo (Curtin University, Malaysia)and Uday Kumar Ghosh (Lincoln University, USA)
DOI: 10.4018/979-8-3373-2210-0.ch013
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Abstract
Psychiatric treatment is undergoing a transformation through computational intelligence (CI) in neurodisorder diagnosis and management for disorders like depression, schizophrenia and autism for employee welfare in organizational culture. CI leverages advanced algorithms such as machine learning and neural networks to discover complex relationships found in brain imaging, genetics, and behavioral metrics more accurately than ever before. The integration of CI into psychiatry, however, creates important ethical challenges. Considerations like data privacy, algorithmic bias and misdiagnosis need to be examined closely. A lack of transparency in AI systems could damage the relationship between patients and clinicians, with decisions based on biased datasets having the potential to reinforce inequities within society. These endeavors would allow the development of new, but still ethically sound, psychiatric practices that would restore public trust in mental healthcare and deliver better outcomes.
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