Ethical Suicide Prevention in an Artificial Intelligence Driven Society

Date
2023-08-10
Authors
Van Kessel, Kirsten
Orr, Martin
Parry, David
Supervisor
Item type
Journal Article
Degree name
Journal Title
Journal ISSN
Volume Title
Publisher
Journal of Ethics in Mental Health
Abstract

Objective To explore the drivers, objectives and challenges for ethical artificial intelligence-based suicide prevention in a technologically evolving clinical and societal context.

Method Narrative selected literature review.

Results There is an ethical need for more effective suicide prevention that is aware of the limitations of prediction. AI research needs to recognise the importance of clinical formulation and risk management and timely therapeutic engagement in suicide prevention. The AI transformation of society may change relationships and roles and alter suicide determinants and prevention. AI may contribute to suicide prevention by facilitating novel research and practice and building the understanding of suicide typology, lived experience, determinants, risk signal models, intervention effectiveness and priority. AI may transform suicide prevention, through enabling timely personal to societal level responses, and leveraging technologies from social media and natural language processing to intelligent digital clinicians and guardians and self-driving cars. AI is increasingly used to enhance engagement and sense, model and shape conscious thought, experience and action patterns at a population and personal level. AI can both protect or harm and guard against or help propagate cyber trauma and cyberbullying. The capacity to architect reality and modulate consciousness may have positive and negative consequences on mental health and suicide prevention and a need for psyche cybersecurity. The potential use of AI in assisted suicide also helps highlight key ethical issues that clinicians and society face.

Conclusions To optimise benefit and minimise algorithmic harm, clinicians have an ethical duty to be involved in the sociocultural and contextually aware co-design and governance of AI based suicide prevention.

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Source
Journal of Ethics in Mental Health, ISSN: 1916-2405 (Print), 11, 1-23.
DOI
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