Social Science: Psychology
Robots will become increasingly common in many fields of work, from health care to fabrication to logistics. However, because robots look and act differently than other humans, they may not trigger the same mental state attribution processes that otherwise help us to understand what others know and want. This can severely undermine the effectiveness of interactions with robots, especially in fields where anxiety-free cooperation is crucial (e.g., health care). The goal of this interdisciplinary research project is to reveal the extent to which people spontaneously attribute the same mental states to robots as to humans, on which morphological (e.g., eyes) and behavioural features (e.g., biological motion, efficient goal seeking) such attributions rely, and whether manipulating these features can either encourage or discourage people from seeing robots as human-like interaction partners (instead of inanimate objects). It relies on two well-established experimental techniques developed by Bach, which robustly measure two central components of social sense-making in independent research streams: (1) how people predict another actor’s behaviour from the intentions they attribute to them, and (2) how they derive another actor’s knowledge from their particular visual perspective. By varying the robots’ morphological features and behaviours, we will be able to measure these two central types of mental state attribution and link them to explicit ratings of interaction quality and mind perception. In doing so, this project will not only provide new insights into how mental states are attributed to robots – and other humans – but also provide novel methods to give robots characteristics that encourage people to “see” them as endowed with mental states so that they can cooperate with them more confidently.
The student will be part of an interdisciplinary team involving Prof Patric Bach from the School of Psychology as primary supervisor and Dr Elena Giannaccini from the School of Engineering as secondary supervisor. They will be part of Bach’s Action Prediction Lab and be able to draw on the two supervisors’ long-term expertise in human social interaction and perception, engineering, and robotics.
Applicants must meet the following eligibility criteria:
This PhD studentship will be available for students wishing to start a PhD in October 2021. The studentship is funded for 3 years or 1+3 years (combined with a MRes in Psychology), situated within the School of Psychology, University of Aberdeen. The School provides an exciting and vibrant research environment for doctoral research programmes.
Students should have a passion for social robotics/human-robot interaction and prior qualifications/experience in Robotics, Psychology or a related discipline equal to a honours degree at a first or upper second class level or a masters from a UK academic research organisation, or an equivalent Degree qualifications from outside the UK. Some prior experience in programming is essential. Desirable is prior experience with working in (social) robotics as well as skills in experimental design and analysis of studies of human behaviour.
Please note that all applicants must also meet the ESRC eligibility criteria. ESRC eligibility information can be found here.
For full details and to apply for this studentship, please visit the Scottish Graduate School of Social Science (SGSSS) website here.
Applications will be ranked by a selection panel and applicants will be notified if they have been shortlisted for interview by 5th April 2021. Interviews will take place on 8th April 2021.
All scholarship awards are subject to candidates successfully securing admission to a PhD programme within the School of Psychology, University of Aberdeen. Successful scholarship applicants will be invited to apply for admission to the relevant PhD programme after they are selected for funding.
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