Research groups - Systems, Intelligent Automation, Supervising in Feminism CDT
Mental health, trust and robotics: How mental health mediates human-AS trust and reliance. The problem this research will be tackling is that of testing whether mental health factors influence an individual’s trusting decisions and reliance strategies towards automated systems. This research intends to consider common mental disorders (CMDs) as moderators such as generalised anxiety disorder (GAD) and depression. This area has enjoyed a recent rise in popularity by government, organisations and culture (particularly in the west) and therefore identifies both an important and highly demanded area of impact research for maximising collaborative automated system performance and individual employee wellbeing.
Representation of female stereotypes in embodied AI and Robots. The focus is on the changing aesthetic and gendered principles and theories which may underly the design of embodied AI and robots, the social clues of impression formation and how that may impact on women’s perception of themselves potentially as artefacts also.
Digitop. As manufacturing shifts towards smart factories, with interconnected production systems and automation, EPSRC has funded the £1.9m DigiTOP project to develop a predictive toolkit to optimise productivity and communication between human workers and robots. Academics at the University of Nottingham, Cranfield University, Loughborough University and the Bristol Robotics Lab are collaborating to deliver an open-access suite of digital tools to enable the real-time capture and prediction of impact, allowing digital technologies to be optimised for manufacturing system performance.
Using new human factors theories and data analytics approaches, tools will be designed to inform human requirements for workload, situation awareness and decision making in digital manufacturing. At the same time, demonstrators will be used to test the implementation of sensing technologies that will capture and evaluate performance change and build predictive models of system performance. The project will also provide an understanding of the ethical, organisational and social impact of the introduction of digital manufacturing tools and digital sensor-based tools to evaluate work performance in the future workplace. The work will look at barriers to acceptance, including various EDI issues. She looks at the impact of different types of culture (professional, national, organisational).
- Crawford, Jordan R; Hubbard, Ella-Mae; Goh, Yee (2019): Mental health, trust, and robots: towards understanding how mental health mediates human-automated system trust and reliance. Loughborough University. Conference contribution. https://hdl.handle.net/2134/9633035.v1