Periodic Reporting for period 1 - NEUROBUKIMI (Affective neurocognitive model for the ‘Uncanny Valley’)
Reporting period: 2016-08-01 to 2018-07-31
A deeper understanding of UVH is important for society for two reasons: first, it can guide the development of human-like robots and virtual characters and second, it can help us predict how individuals will react to them. Various kinds of socially interactive robots have already begun to appear for consumer, service, and health care applications. Two examples include seal-like robot PARO that is being used for therapeutic purposes and ROBEAR robot that is being used in nursing care. Purposefully human-like robots are also being developed by companies such as Hanson Robotics. In entertainment, the first attempts to create fully animated human-like cinematic actors were already made shortly after the turn of the present millennium when films such as Beowulf and The Polar Express saw their premieres. Such films met an overall negative critical reception that focused on the “uncanniness” of their highly realistic animations, and the UVH was even explicitly mentioned in some reviews. In science, virtual characters are now being used increasingly more often to replace research stimuli recorded from real humans. This is the case for example for neurocognitive experiments on affects and social cognition, in which faces and facial expressions have long served as research stimuli. Because the UVH makes a general recommendation to avoid high levels of realism and human-likeness, it is of direct relevance to all of the aforementioned applications.
This project approached the UVH mainly from the perspective of social-affective neurocognitive research; however, its results were expected to be of more general societal relevance as well. We focused mainly on computer-generated (CG) faces given the importance of faces in social interaction and the wide-spread use of CG faces in neurocognitive studies. The overall objectives of this project included assessing whether and when the UV exists and investigating the similarities and differences in the neurocognitive processing of real and CG faces.
We include the following conclusions for the action (for explanations, see the section below): i) uncanny valley phenomenon exists but it is much weaker than usually thought and strongly influenced by social factors; ii) contrary to UVH, more realistic CG faces are actually more desirable; iii) CG faces elicit different cognitive, affective, and neural processing than real faces.
As an overview, the results show that i) there is evidence of the UV in animated film characters but this effect is much weaker than anecdotally claimed and it can also be modulated by exposure to critical film reviews; ii) there is a strong trend between higher realism and familiarity (more realistic faces elicit more favorable evaluations) and this effect shadows a weak UV effect occurring specifically for CG faces; iii) CG faces perform differently from real faces in a face memory task such that CG faces elicit a greater proportion of false recollections (the “they all look the same to me” phenomenon); and iv) CG faces trigger weaker fMRI responses in a face-sensitive brain network than real faces.
Results have been disseminated to the scientific community (and to some extent, industry) in four scientific conferences, via scientific publications, and via a guest lecture given at the course “Man-Machine Interaction” at Maastricht University (March 20th 2017); and to the general public via an interview published in New Scientist (October 29th 2016).
On the other hand, the present findings also emphasize the limits of virtual characters by showing that virtual as compared with realistic faces still trigger different cognitive and affective responses both at behavioral and neural levels. Notably, these differences were observed using static images of faces –even greater differences should be expected for moving and interactive artificial entities. The present findings are of significance for research (social-affective neuroscience in particular) but also for the wider societal context. The findings suggest that in order to reach identical neurocognitive processing as real faces, virtual characters need to be made practically identical to them. Bridging the gap between real and virtual characters remains a formidable challenge especially for fully-embodied, moving, and socially interactive characters.