Are We Losing Our Minds? Humans, AI, and the Shifting Boundaries of Care and Learning

Neurodivergence can cause individuals to experience difficulties in understanding and regulating their emotional responses. Psychologists specialised in neuro-inclusion explore the utility of emotion focused group therapy to help neurodivergent individuals address challenges inherent to life in a neuro-typical world.
For therapists, monitoring every nuance and detail of expression through physical behaviour and verbal communication across a group of individuals becomes challenging over the duration of the therapy session. These sessions are typically recorded to allow therapists further analysis and understanding of each participants emotional regulation. Sessions which typically last an hour introduce more high-focus workload to therapists who often are already overburdened. This talk frames emotion recognition as a data-centred challenge and explores the use of machine learning in classifying emotion from speech, vocal-intonation and facial expressions. The proposed system suggests segments of interest to the therapist ultimately reducing the time required for post-analysis of therapy sessions.

Artificial intelligence can now write essays, create images, help doctors make decisions, and even support teaching and learning. As these tools become part of everyday life, they raise an important question: what makes us human? In this talk, we explore how AI is changing education and healthcare, what it means for how we think and learn, and why judgement, responsibility, and creativity may matter more than ever in an AI-driven world.

Generative AI is rapidly reshaping how students learn, think, and complete assessments, but much of the current response in higher education has focused on making existing assessments “AI-proof.” This talk challenges that approach. Drawing on experience in Life Sciences teaching, it asks a more fundamental question: are we simply patching a system under pressure, or should we be redesigning it for a world where AI is an everyday tool?
I will discuss this approach compared to a more proactive model: embedding AI literacy, critical evaluation, and ethical use directly into the curriculum. Rather than viewing AI as a threat to academic integrity, this approach treats it as part of the intellectual landscape students must learn to navigate.
This talk will offer practical reflections on what this shift might look like in STEM disciplines, highlighting both opportunities and tensions. Ultimately, it invites us to consider whether the goal is to defend existing practices or to rethink what meaningful learning and assessment look like in the age of generative AI.