Dramatic advances in neuroscience have improved physicians’ abilities to diagnose and manage neurological and psychiatric disorders for their patients. Alongside established modalities such as computed tomography (CT), magnetic resonance imaging (MRI), and functional MRI (fMRI), advanced neuroimaging technologies provide new tools for understanding normal human behavior and diagnosing neuropsychiatric disorders impacting human behavior. But the application of these novel technologies, designed to help patients in the treatment setting, to the forensic setting presents unique ethics challenges. Forensic psychiatry is a subspecialty in which scientific and clinical expertise is applied in legal contexts, and in specialized clinical consultations in areas such as risk assessment or employment. In contrast to the treatment setting where advancing the patient’s welfare is primary, the primary duty in forensic settings is to foster truth. Thus, an honest forensic opinion based on good science and evidence may not necessarily benefit the person being evaluated and could cause that person harm. Similarly, artificial intelligence (AI) and machine learning technology are applied to a growing number of clinical and forensic settings, bringing potential to transform how psychiatrists assess an individual’s risk for violence and risk for suicide. Despite this promise, however, these emerging technological advances present significant ethical dilemmas, medico-legal limitations, and the risk of misuse if applied unethically. In this chapter, recent neuroscientific advances in the fields of functional neuroimaging and AI “deep learning” algorithms are reviewed in detail along with the relevant legal and ethical framework, advantages, and potential drawbacks.
- Artificial intelligence
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Darby, W.C., MacIntyre, M., Cockerill, R.G., Stephens, D.B., Weinstock, R., Darby, R.R. (2023). In the Courts: Ethical and Legal Implications of Emerging Neuroscience Technologies Used for Forensic Purposes. In: Roberts, L.W. (eds) Ethics and Clinical Neuroinnovation. Springer, Cham. https://doi.org/10.1007/978-3-031-14339-7_10
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