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Investigating the uncanny valley for hands: what makes a hand human?

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  • Full or part time
    Dr Poliakoff
    Dr Gowen
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

The concept of the ‘Uncanny valley’ was coined to describe a phenomenon in robotics, whereby people feel more affinity to robots as they become more humanlike, but humanoid robots which very closely resemble the human form are found to be odd and unnerving (Mori, 1970). Although the term is over 30 years old, empirical tests and psychological investigations of the mechanisms underlying this phenomenon remain limited (for a review, see Kätsyri et al., 2015). Mori hypothesised that artificial (prosthetic) hands would fall into the uncanny valley and we were the first to confirm this empirically, using ratings of pictures of static hands (Poliakoff et al., 2013). This PhD would take this work as a starting point to explore further unanswered questions. For example, Mori hypothesised that movement would accentuate the uncanny valley, but this hypothesis remains under-tested and it is not known how movement would integrate with other features (such as colour and texture).

It is also important to investigate behaviour towards ‘uncanny’ stimuli. People show visuomotor priming (or automatic imitation) when they view human versus non-human hand movements (Gowen & Poliakoff, 2012) but it not known whether people show this effect for hands that appear uncanny. Finally, the effect of experience on responses to these stimuli warrants further exploration (e.g. experience with people with prosthetic limbs or with video games with animated humans/hands).This area of work has implications for theoretical accounts of the uncanny valley and human perception, as well as broader relevance for the development of realistic and likeable animations, robots and prosthetics.

The successful candidate will be trained in a wide range of research skills including designing behavioural experiments, measuring eye movements, reaction times and physiological responses, as well as public engagement.

Candidates are expected to hold, or about to obtain, a minimum upper second class undergraduate degree (or equivalent) in psychology, cognitive neuroscience, neuroscience, sports science or another related subject. A Masters degree in a relevant subject would be an advantage.

This 3-year full-time PhD is open to candidates able to provide evidence of self-arranged funding/ sponsorship and is due to commence from January 2017 onwards.

Any enquiries relating to the project and/or suitability should be directed to Dr Poliakoff ([email protected]). Applications are invited on an on-going basis but early expression of interest is encouraged.

Funding Notes

This project has a Band 1 fee. Details of our different fee bands can be found on our website. For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website. Informal enquiries may be made directly to the primary supervisor.

References

1. Gowen E, Poliakoff E (2012) How does visuomotor priming differ for biological and non-biological stimuli? A review of the evidence. Psychological Research. 76: 407–420.
2. Kätsyri J, Förger K, Mäkäräinen M, Takala T (2015) A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness. Frontiers in Psychology, 6:390 DOI:10.3389/fpsyg.2015.00390
3. Mori M (1970) The Uncanny Valley. Energy, 7, 33-35. Translated by Karl F. MacDorman and Takashi Minato
4. Poliakoff E, Beach N, Best R, Howard T, Gowen E (2013) Can looking at a hand make your skin crawl? Peering into the uncanny valley for hands. Perception, 42, 998-1000.
5. Saygin A P, Chaminade T, Ishiguro H, Driver J, Frith C (2012) The thing that should not be: predictive coding and the uncanny valley in perceiving human and humanoid robot actions. Social Cognitive and Affective Neuroscience, 7, 413-422.

How good is research at University of Manchester in Psychology, Psychiatry and Neuroscience?

FTE Category A staff submitted: 67.70

Research output data provided by the Research Excellence Framework (REF)

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