This article provides a conceptual framework - “CRITiCS” - for potential use in the design and deployment of generative AI systems to support clinical decision making in mental health services. Recent advances in generative AI, via massive parameter transformer networks (large language models such as GPT4) have rendered possible the use of cognitive agents that may support clinical productivity in mental healthcare, particularly in secondary and tertiary services where information load is proportional to clinical complexity and chronicity. Thus, the way we conceptualise the ‘cognitive space’ that, up to 2023, was occupied solely by human clinical reasoning, will inevitably change. However, there are transparency issues in that the cognitive emulation observed in LLM outputs, while of obvious potential benefit as an analogue of clinical reasoning,is not amenable to granular understanding in the same way that clinical decision making is subject to interrogation by human governance and assurance bodies. A consensus conceptual framework is urgently needed, to direct the path of the use of generative agents in mental health care, which we argue has cognitive space features that distinguish it from physical medicine, towards which most AI deployment proposals to date have been directed. It is hoped that this paper will attract discussion and interest in both the clinical and development communities.

No abstract

No abstract

No abstract

No abstract