This paper examines the use of artificial intelligence (AI) for the diagnosis of autism spectrum disorder (ASD, hereafter autism). In so doing we examine some problems in existing diagnostic processes and criteria, including issues of bias and interpretation, and on concepts like the ‘double empathy problem’. We then consider how novel applications of AI might contribute to these contexts. We're focussed specifically on adult diagnostic procedures as childhood diagnosis is already well covered in the literature.@en

In 1950 Alan Turing asked whether machines could think. This question has been vigorously debated since, and its relevance for machine intelligence, or even agency, continues to provoke interdisciplinary debate. In fact, Turing's next step in his paper is to ask a far more nuanced question about imitation, which, we suggest, assumes a number of connections between intelligence, agency and the possibility of imitation. This paper will offer three key arguments against these assumptions, and in so doing make the following claims: (1) that intelligence is not a guarantee of personhood or agency, (2) that Turing's claims for imitation neither resolve the issue of intelligence, nor of agency, and that (3) recognition between agents (or recognition of agency) centres on the interpersonal relationship between agents, which in turn centres on the possibility for communication with a shared language. Our paper does not seek to argue either for or against the possibility of machine thought. Instead we seek to question whether any such processing would be recognized (by other agents) as thought or agency, and what this recognition might involve.@en

The incorporation of neural-based technologies into psychiatry offers novel means to use neural data in patient assessment and clinical diagnosis. However, an over-optimistic technologisation of neuroscientifically-informed psychiatry risks the conflation of technological and psychological norms. Neurotechnologies promise fast, efficient, broad psychiatric insights not readily available through conventional observation of patients. Recording and processing brain signals provides information from ‘beneath the skull’ that can be interpreted as an account of neural processing and that can provide a basis to evaluate general behaviour and functioning. But it ought not to be forgotten that the use of such technologies is part of a human practice of neuroscience informed psychiatry. This paper notes some challenges in the integration of neural technologies into psychiatry and suggests vigilance particularly in respect to normative challenges. In this way, psychiatry can avoid a drift toward reductive technological approaches, while nonetheless benefitting from promising advances in neuroscience and technology.@en