Background

Artificial intelligence (AI) may offer potential to augment risk assessment and expand personalised treatment in prison psychiatry. In Queensland, prisoners experience high rates of mental illness, and Aboriginal and Torres Strait Islander people are overrepresented, placing additional demands on already overstretched services.

Purpose

To explore the potential role of AI in enhancing clinical decision–making, improving risk assessment (including recidivism, self–harm, and violence), and supporting more personalised treatment approaches within prison psychiatry.

Research Design

Conceptual and ethical discussion of AI applications in correctional mental health, considering clinical, cultural, and systemic implications.

Study Sample

Conceptual discussion focused on prison populations in Queensland, particularly individuals with mental illness and Aboriginal and Torres Strait Islander peoples.

Data Collection and/or Analysis

Critical synthesis of emerging AI risk–prediction models and their potential application in correctional psychiatry, alongside analysis of ethical considerations such as bias, transparency, and cultural competence.

Results

AI–based risk–prediction models may help identify emerging risks related to recidivism, self–harm, and violence, supporting earlier intervention and improved resource allocation. However, these models may also reproduce structural biases embedded in underlying data, raising concerns about equity and fairness.

Conclusions

AI has potential to support, but not replace, clinical judgement and therapeutic relationships in prison psychiatry. Ethical implementation requires rigorous validation, transparency, and sustained human oversight, with strong emphasis on cultural competence to ensure equitable outcomes.