SAINTS research focuses on the lifelong safety assurance of increasingly autonomous systems in dynamic and uncertain contexts, building on methodologies and concepts in disciplines spanning AI, safety science, philosophy, law, sociology and health sciences. Research within SAINTS addresses the following two research themes:
- Lifelong safety of AI systems: the need to weave safety assurance from the earliest stages of design through to post-deployment (lifelong) because of the increasingly open and dynamic contexts in which AI-enabled systems are deployed, and;
- Safety of increasingly autonomous AI systems: the need to address the implications of increasing transfers of decision-making functions (autonomy) from humans to AI-enabled machines.
SAINTS doctoral candidates are pursuing their research within multidisciplinary research teams that are focused on ‘grand challenges’ aligned to the CDT. The two grand challenges identified for researchers starting their PhDs in 2024 and 2025 are:
1. Safety of AI-enabled robotics
This grand challenge relates to physically embodied autonomous AI agents, including agents such as self-driving cars, surveillance drones and deep-sea exploration robots. For such systems, AI typically has two roles. First, building a model of the operational context, identifying and assessing objects, e.g., distinguishing static elements such as the sea bed from dynamic ones such as fish, and predicting the movement of the dynamic elements. Second, planning or decision-making, e.g., deciding on a route to meet the system’s goals whilst ensuring safety, including avoiding collisions with other objects. Possible research areas include ensuring robots or drones can navigate within different environments and make real time decisions, demonstrating the safety of AI-based functionality, legal liability of drivers vs vehicle manufacturers, risks around the normalisation of mass surveillance etc.
2. Safe Human-AI collaboration
This grand challenge will explore how humans and AI-based systems work together towards overall goals in domains such as air traffic services, healthcare, criminal justice, law enforcement and manufacturing. Humans may collaborate with AI-enabled embodied systems, such as robots or vehicles, and/or with stand-alone AI-based decision-support systems, for example, that recommend drug dosages. Possible areas of research include supporting effective human-AI teaming, use of explanations as part of assuring safety, considering responsibility in the case of incidents or accidents, understanding the change in the nature of jobs on safety and operator mental health etc.
