SAINTS research focuses on the lifelong safety assurance of increasingly autonomous AI systems in dynamic and uncertain contexts, building on methodologies and concepts in disciplines spanning computer science, philosophy, law, sociology and health sciences. Our research addresses the following two overarching research themes:
Lifelong safety of AI systems: Weaving in safety throughout the entire lifespan of AI systems, from early design decisions to post-deployment.
- Topics of interest: Risk-driven AI training, metrics and benchmarks; testing and simulation for uncertain operating environments; safe retraining and continual learning; proactive monitoring and dynamic safety cases; moral responsibility; legal liability; investigating AI-related incidents.
- Safety of increasingly autonomous AI systems: Addressing the implications of transferring decisions from humans to AI-enabled systems.
- Topics of interest: Understanding human-AI interaction; designing safe joint cognitive systems; assurance of safe transition between human and AI control; achieving effective human oversight and human-centred explainability; preserving human autonomy and accountability; reducing risk of diluting human value by human-AI teaming.
Our research considers both purpose specific AI, e.g. convolutional neural networks for detecting pedestrians in autonomous driving, and general-purpose foundational AI, e.g. large language models for triaging patients in healthcare. SAINTS research focuses on risk reduction in sectors where safety is paramount, such as healthcare, national security and transport, whilst taking a broader view of safety in its technical, legal, ethical and societal context. The broader perspective provided by the centre’s multidisciplinary structure is vital to the trustworthy and responsible development and adoption of AI, balancing technical safety with respect for other values, such as equity and explainability, and aligning research with legal requirements and societal needs and expectations.