PhD Studentship: Learning to Trust Emerging Disruptive AI and Automated Technology

; Cardiff University, United Kingdom

Updated: 4 months ago
Location: Cardiff, WALES
Job Type: FullTime
Deadline: 01 Mar 2024

The UK aspires to lead in innovation and research on cutting-edge technologies like artificial intelligence (AI), automation, and robotics, as emphasized in recent Government Research and Development Roadmaps. These technologies are anticipated to significantly impact society, posing challenges related to data, climate change, and geopolitics. A crucial aspect tied to these advancements is the need for human-centered research on how individuals learn, accept, and adopt these technologies. An inherent challenge lies in the lack of baseline trust levels, particularly for technologies yet to be experienced widely, such as autonomous vehicles. Researchers have long warned of potential misuse and the importance of trust for resilient automated systems. Despite this, the theoretical and practical aspects of defining and measuring human trust in AI and automation remain contentious. Recent research indicates low reported trust levels, underscoring the urgency to find optimal ways to measure trust in emerging technologies. Ensuring adequate user experience through learning is pivotal for successful integration and reliance on these technologies. In this studentship, you will contribute to overcoming this important theoretical and practical gaps. The student, alongside a leading team of experts, aims to bridge this theoretical and practical gap. The focus will be on the following:

  • Review: The primary objective is to systematically review existing literature on defining and measuring trust in AI and automated technologies. This review will establish a robust theoretical framework for the project.
  • Paradigm: Building on the literature review, the second goal is to conduct experiments aimed at developing an optimal paradigm for enhancing and restoring trust in AI and automated technologies. This includes exploring boundary conditions and utilizing cutting-edge technologies in the Human Factors Excellence (HuFEx) Laboratory.
  • Transfer: Addressing the issue of trust specificity, the third objective involves applying computational theories of learning to develop guidelines for rapid trust acquisition in AI and automated technologies across various settings. This core aims to bridge gaps in understanding trust dependence on situational factors.
  • Dissemination: The final objective focus on implementing best education practices to effectively share the gained knowledge with stakeholders and policymakers. The goal is to showcase how the acquired insights can be appropriately communicated to ensure meaningful impact and informed decision-making.

    • Home students are UK Nationals and EU students who can satisfy UK residency requirements (students must have been in the UK for >3 years before start of course). As only a limited number of studentships are available across the Open School competition and a very high standard of applications is typically received, the successful applicants are likely to have a very good first degree (a First or Upper Second class BSc Honours or equivalent) and/or be distinguished by having relevant research experience.

    Studentships are awarded on a competitive basis in competition with other projects in the Open School competition. The studentship commences in October 2024, covers 3 years tuition fees and maintenance, with submission deadline of 4 years. The 2023/4 full-time maintenance grant was £18,662 p.a. Psychology students receive conference and participant money (~£2,250), computer, office space, access to courses and become members of the Doctoral Academy. Please select most appropriate advert for your Research and specify that you’re applying for this project and supervisor.

    For any queries about this studentship, please contact the supervisor by email - Phillip Morgan [email protected] .


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