Large language models (LLMs) demonstrate remarkable linguistic fluency and semantic breadth, yet viewed through a neuropsychological lens, their capabilities are strikingly uneven—"jagged"—with exceptional strengths in semantic knowledge and language generation but profound limitations in episodic memory, emotional/affective processing, embodied cognition, and autonomous goal-directed behaviour.

Aims: This presentation aims to map LLMs' performance onto familiar neuropsychological constructs, illuminating areas of superhuman capability alongside persistent, fundamental deficits, and to explore the implications for rights-based neuropsychological practice amid the rise of specialised AI tools for report generation, summarisation, and synthesis.

Content: Drawing on emerging AI literature and clinical relevance, the talk will characterise LLMs' jagged cognitive profile, highlighting risks such as confident hallucinations leading to inaccurate documentation, embedded biases disadvantaging diverse or vulnerable clients, privacy/discoverability concerns in medicolegal contexts, erosion of independent clinical reasoning, and unchecked scope creep. These challenges will be framed against benefits like enhanced efficiency in high-demand settings.

Goals: By equipping neuropsychologists with a nuanced understanding of these limits, the presentation seeks to promote judicious, reflective integration of AI—upholding client-centred reasoning, transparency, cultural safety, professional accountability, and alignment with PsyBA standards and evolving regulatory expectations. Ultimately, this contributes to a rights-informed future where technology supports, rather than supplants, equitable and ethical neuropsychological care.

This practical and thought-provoking session focuses on how artificial intelligence and emerging technologies are beginning to reshape psychological and neuropsychological practice.
This presentation explores where AI can genuinely enhance clinical work — from documentation to decision support — while keeping the human relationship, empathy, and professional judgement at the centre of mental health care. While AI can replace some clinical and technical tasks, the "human skill premium" will become even more valuable.
This talk offers a grounded roadmap for clinicians navigating the wave of change currently occurring, and where it may lead clinical practice next. Today's tools that can support more precise assessment and real-time clinical insights. This presentation will explore how technology can strengthen evidence-based practice by making high-quality assessment more scalable, interpretable, and clinically actionable — while ensuring that human judgement remains central.
Whether you’re AI-curious, cautious, or already using an AI Scribe or other tools, this session will help you:
• Make informed, evidence-based decisions about AI in clinical practice
• Improve workflow efficiency without compromising care
• Understand ethical, privacy, and professional risks
• Prepare for the future of AI-enhanced mental health services

Artificial intelligence (AI) is already present in clinical spaces. Clients are increasingly using consumer-facing AI tools to seek psychological guidance, often without clinician knowledge, oversight, or governance. For individuals with cognitive vulnerabilities, including executive dysfunction, neurodevelopmental differences, acquired brain injury, or age-related decline, this presents significant ethical risk.

This presentation examines ethical responsibility in the age of AI through a neuropsychological lens. It explores how unregulated digital tools may affect consent, autonomy, privacy, clinical accuracy, and power dynamics. Particular attention is given to how cognitive impairment may influence a client’s capacity to evaluate AI-generated information and provide meaningful informed consent.

The aim of this presentation is to centre client rights within contemporary neuropsychological practice and consider how the profession can respond proactively. Content will include emerging patterns of AI use, risks for cognitively vulnerable populations, and principles for maintaining accountability and duty of care beyond the session. A clinician-governed digital model will be discussed as one example of how ethical oversight and transparency can be embedded into practice.

Participants will leave with a clearer understanding of professional responsibilities when clients engage with AI, practical risk mitigation strategies, and a framework for integrating digital tools in ways that uphold dignity, safety, and equitable access.

Neuropsychological practice is often associated with the careful administration and interpretation of psychometric tests. However, meaningful assessment also involves observing the person behind the data: how they enter the room, how they respond to challenge, how anxiety, effort, rapport, and context influence performance. These subtle behavioural patterns are often communicated through the language clinicians use when describing observations and interpreting findings.

The aim of this presentation is to explore how neuropsychologists can maintain clinical judgement and humane, client-centred communication while responsibly integrating artificial intelligence (AI) supported tools into documentation and report writing.

Drawing on the perspective of a clinical psychologist working extensively with trauma, disability, and complex systems of care, the presentation will examine how assessment interpretation occurs across three interconnected layers: clinical judgement, narrative framing, and the systems in which reports are read and interpreted.

Content will highlight how small observational details, such as hesitation, shifts in tone, humour, self-correction, or signs of apprehension during testing, can offer meaningful insights into how individuals experience assessment. The presentation will also explore how subtle differences in language can influence how clients understand themselves, how other professionals interpret findings, and how individuals are positioned within healthcare, workplace, disability, and legal systems.

A practical framework will be introduced for considering where AI-assisted tools may appropriately support clinicians, such as structuring or drafting reports, while ensuring that interpretation, behavioural observation, and narrative meaning remain under clinician oversight.

The goal of the presentation is to support clinicians to integrate emerging technologies thoughtfully while preserving professional judgement, dignity, and rights-based, person-centred care.