Research Themes
Research themes at CCAI.
AI in Learning & Education
Education exemplifies AI's qualitative turn, where generative systems produce cultural outputs such as essays, explanations, and creative work that demand contextual interpretation rather than simple benchmarking. Yet current educational AI often operates through narrow metrics that homogenise learning, perpetuating limited conceptions of intelligence whilst marginalising alternative ways of knowing.
AI, Law & Regulation
This theme explores how legal and regulatory frameworks must evolve beyond technical compliance to engage with the interpretive complexity of AI governance.
AI, Work & Organisations
Artificial intelligence is fundamentally reshaping how we work, how organisations operate, and how citizens interact with employers, government services, and civic institutions.
Climate & Sustainability
What does justice look like when we expand our circle of concern beyond humans? How can AI support climate mitigation or thriving ecologies rather than just efficient systems? This theme examines how we design technologies that recognise our interdependence with the living world.
Communities, Democracy & Society
This theme explores how citizen-centred approaches can guide the design and deployment of AI so that it supports plural viewpoints, collective decision-making, and community agency. Rather than treating citizens as data sources or passive users, it considers them as co-designers, interpreters, and evaluators of AI systems.
Design & Co-Creation
This research theme explores how participatory design, creative practice, and interpretive methodologies can shape AI systems that engage meaningfully with ambiguity, plurality, and diverse human values.
Health & Wellbeing
How can artificial intelligence genuinely serve patients, carers, communities, and healthcare professionals whilst respecting the interpretive complexity of health and illness?
Identities, Security & Society
AI systems increasingly respond to identity information and seek to address privacy and security concerns, yet they often lack frameworks for interpreting the cultural complexity these domains entail.
Uncertainty, Explainability, Transparency and Bias in AI
This research theme explores uncertainty, explainability, transparency, and bias through the lens of interpretive depth and human agency.