A paper by Professor Sakiko Yoshikawa, Lecturer Yoshiyuki Ueda and colleagues has been published in the journal Cognitive Research: Principles and Implications
A research paper written by Professor Sakiko Yoshikawa and Lecturer Yoshiyuki Ueda, together with Associate Professor Rob Jenkins and Jet Sanders (currently, Assistant Professor, the London School of Economics and Political Science) of the University of York, has been published in Cognitive Research: Principles and Implications.
Research conducted at universities in Japan and Britain showed that it was difficult for participants viewing photographs of faces to distinguish between people’s real faces and people wearing lifelike silicon masks. This research suggests that security and crime prevention methods that rely solely on the appearance of facial photographs are fragile and call into question how effective the information gathered by such methods is.
Press Release from the University of York:
Check out the video below:
(The video is in English, and you can see the silicon masks used in the studies.)
Sanders, J. G., Ueda, Y., Yoshikawa, S., & Jenkins, R. (2019).
More human than human: a Turing test for photographed faces
Cognitive Research: Principles and Implications, 43.
Recent experimental work has shown that hyper-realistic face masks can pass for real faces during live viewing. However, live viewing embeds the perceptual task (mask detection) in a powerful social context that may influence respondents’ behaviour. To remove this social context, we assessed viewers’ ability to distinguish photos of hyper-realistic masks from photos of real faces in a computerised two-alternative forced choice (2AFC) procedure.
In experiment 1 (N = 120), we observed an error rate of 33% when viewing time was restricted to 500 ms. In experiment 2 (N = 120), we observed an error rate of 20% when viewing time was unlimited. In both experiments we saw a significant performance cost for other-race comparisons relative to own-race comparisons.
We conclude that viewers could not reliably distinguish hyper-realistic face masks from real faces in photographic presentations. As well as its theoretical interest, failure to detect
synthetic faces has important implications for security and crime prevention, which often rely on facial appearance and personal identity being related