PhD Psychology: Calibrating Trust between Humans and Autonomous Systems

An ESRC fully-funded 3-year PhD studentship is available in the lab of Professor Frank Pollick at the School of Psychology, University of Glasgow. The research is co-supervised by Professor Ben Jones and is in collaboration with Qumodo in London. The work will involve experiments to examine the problem of human trust in autonomous and intelligent systems.

The notion of trust between man and machine has become increasingly relevant as forms of artificial intelligence pervade technology. Now, just like with a human, we assess the predictability, reliability and motives of the machines we use
to inform our future behaviour with them. If a user does not ‘trust’ a machine, then it is unlikely that they will optimise their performance in using it. To remedy this situation, improving both mental health and productivity, we must be able to calibrate trust between man and machine.

The collaborative partner, Qumodo, is dedicated to advancing human-artificial intelligence teams and the project will include use of their software Intelligent Iris, a modular data analysis platform that is designed to facilitate human users in extracting meaningful information from large sets of data, including images (such as photos, medical scans, military sensor data, etc.). The visual nature of this task makes it challenging as humans bring a wealth of social expectancies and uniquely human visual processes to understand an image. The research will be guided by recent investigations of trust from domains like autonomous vehicles and social robotics and will involve experiments to examine which parameters influence the calibration of trust when interacting with the image understanding software.

The team at Qumodo will be a critical friend throughout this PhD, they will host the student for 2-4 weeks each year in London. Qumodo will assist by facilitating contact with their primary customers to enable experiments with end-users (for experiments involving Government end-users UK security clearance is required). The successful applicant will work closely with Qumodo team members, including technical specialists, developers, designers, data scientist and machine learning experts.

Applicants are expected to have a background in experimental psychology and the collection and analysis of data. Programming skills (e.g. Java, Python, Javascript) are desirable to enable more sophisticated involvement with the Qumodo software. Interest in topics such as vision, cognition, social cognition, eye movements, machine learning, artificial intelligence and human factors, among others would be an asset. Students should have successfully completed
 a Masters degree that provided subject specific and methods training relevant to Psychology. This will have included research training in the areas of research design and data collection plus a dissertation covering the specific required learning outcomes as set out by the ESRC.

To apply, please email Professor Frank Pollick ([Email Address Removed]) with a full CV including details of 2-3 referees, up-to-date transcripts and a cover letter explaining your interest in the project for
PhD studies. The successful candidate will also be required to formally apply for the +3 programme via the University’s normal application form; for details, please see Apply Now link above/below.