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Mapping out the philosophical questions of AI and clinical practice in diagnosing and treating mental disorders.

Susanne UusitaloJarno TuominenValtteri Arstila
Published in: Journal of evaluation in clinical practice (2020)
How to classify the human condition? This is one of the main problems psychiatry has struggled with since the first diagnostic systems. The furore over the recent editions of the diagnostic systems DSM-5 and ICD-11 has evidenced it to still pose a wicked problem. Recent advances in techniques and methods of artificial intelligence and computing power which allows for the analysis of large data sets have been proposed as a possible solution for this and other problems in classification, diagnosing, and treating mental disorders. However, mental disorders contain some specific inherent features, which require critical consideration and analysis. The promises of AI for mental disorders are threatened by the unmeasurable aspects of mental disorders, and for this reason the use of AI may lead to ethically and practically undesirable consequences in its effective processing. We consider such novel and unique questions AI presents for mental health disorders in detail and evaluate potential novel, AI-specific, ethical implications.
Keyphrases
  • artificial intelligence
  • mental health
  • machine learning
  • big data
  • deep learning
  • clinical practice
  • endothelial cells
  • high resolution
  • electronic health record
  • risk assessment
  • mass spectrometry
  • data analysis