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Artificial intelligence in forensic psychiatry: admissibility and relevance before courts.

Authors :
Bhattacharya, Reema
Khan, Aqueeda
Source :
International Journal of Systems Assurance Engineering & Management; May2024, Vol. 15 Issue 5, p1638-1649, 12p
Publication Year :
2024

Abstract

"Technology" and "Criminal law" are usually considered separate subjects. Artificial intelligence in courts has raised questions about criminal procedural law. Investigations and crime perception have changed due to the digital society. Humans have a duty to maintain the law, but the fast digital shift in people's lives is affecting how they do so. Technology and AI are crucial for the criminal justice system (CJS). In the scientific community, methodology, and approaches, AI is defined. It's usually used to describe something that simulates human cognition with a machine. Advances in neuroimaging, AI, and machine learning have led to the development of brain-reading technologies that could be used for lie detection, brain-computer interfaces, and brain mapping in the near future. Politicians, technicians, and lawyers, among others, must collaborate for the good socio-research of society, particularly in the criminal justice system. In this paper, we review and analyse the literature on the use of brain-reading AI for neuroprotection of violence and rearrest to identify opportunities and challenges in the future use of these techniques in the fields of forensic psychiatry and criminal justice, while taking legal implications and ethical concerns into account. More research on AI neuro-prediction techniques is needed, according to the study, to complete the investigation, and it is still important to understand how they might be employed in the field of forensic psychology. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09756809
Volume :
15
Issue :
5
Database :
Complementary Index
Journal :
International Journal of Systems Assurance Engineering & Management
Publication Type :
Academic Journal
Accession number :
178047068
Full Text :
https://doi.org/10.1007/s13198-023-02111-y