Human‑centred AI
Human‑centred AI (HCAI) involves developing AI methodologies and Systems around human needs, values, and behaviours, ensuring that the AI systems support, empower, and interact effectively with people. HCAI research at the University of Glasgow’s School of Computing Science brings together interdisciplinary research and innovation aimed at designing such AI systems.
Rooted in a broader institutional mission to conduct world leading research while sustaining societal value, this thread focuses on AI research spanning Artificial Social Intelligence (Social AI), Responsible AI and Interactive AI systems. - Social AI focuses on building the next-generation AI technologies for detecting, interpreting, and generating human-centric social and emotional phenomena using interdisciplinary research methodologies spanning Deep Learning, Speech/Signal Processing, Graphics & Animation, and Behavioural Psychology.
- Responsible AI research involves the development and deployment of AI systems in ways that ensure safety, fairness, transparency, accountability, and alignment with human values. It also requires proactively assessing and mitigating potential AI harm so AI systems remain trustworthy and beneficial across diverse communities.
- Interactive AI builds AI systems to engage dynamically with people through conversation, feedback, or shared tasks, adapting their behaviour based on human input. These systems aim to support meaningful, intuitive, and collaborative interactions that feel responsive, natural, and socially aware.
Our research activities are supported by UKRI, EPSRC, EU H2020, Canada-UK AI Initiative, UK Defence Security & Technology Lab, Leverhulme Trust and by leading industries such as Intel and Nokia Bell Labs.
Project Highlights
SOCIAL AI CDT
The Centre for Doctoral Training in artificial social intelligence (2019 – 2027, UKRI) aims at endowing machines with social intelligence, the ability to deal with users’ intentions, attitudes, emotions, personality and expectations.
Centre for Doctoral Training in artificial social intelligence
PHAWM
The Participatory Harm Auditing Workbenches and Methodologies (2024 – 2028, RAI UK) Keystone Project is pioneering participatory AI auditing, where non-experts including regulators, end-users and people likely to be affected by the decisions made by AI systems will play a role in ensuring that those systems provide fair and reliable outputs. The project aims to bring AI auditing and assessment to people who do not necessarily have a technical background.