Mapping Beyond the Uncanny Valley: A Delphi Study on Aiding Adoption of Realistic Digital Faces

Developers and HCI researchers have long strived to create digital agents that are more realistic. Voiceonly versions are now common, but there has been a lack of visually realistic agents. A key barrier is the “Uncanny Valley”, referring to aversion being triggered if agents are not quite realistic. To gain understanding of the challenges of the Uncanny Valley in creating realistic agents, we conducted a Delphi study. For the Delphi panel, we recruited 13 leading international experts in the area of digital humans. They participated in three rounds of qualitative interviews. We aimed to transfer their knowledge from the entertainment industry to HCI researchers. Our findings include the unexpected conclusion that the panel considered the challenges of final rendering was not a key problem. Instead, modeling and rigging were highlighted, and a new dimension of interactivity was revealed as important. Our results provide a set of research directions for those engaged in HCI-oriented information systems using realistic digital humans.

[1]  M. Mori.  THE UNCANNY VALLEY , 2020, The Monster Theory Reader.

[2]  W. P. Aguayo,et al.  La teoría de la abducción de Peirce: lógica, metodología e instinto Peirce's Theory of Abduction: Logic, Methodology, and Instinct , 2011 .

[3]  H. Ishiguro,et al.  The uncanny advantage of using androids in cognitive and social science research , 2006 .

[4]  A. Dubois,et al.  “Systematic combining”—A decade later , 2014 .

[5]  H. Freud.  Emotional Design Why We Love Or Hate Everyday Things , 2016 .

[6]  H. A. Lingstone,et al.  The Delphi Method: Techniques and Applications , 1976 .

[7]  Mark Sagar,et al.  Creating connection with autonomous facial animation , 2016, Commun. ACM.

[8]  Timothy W. Bickmore,et al.  Establishing and maintaining long-term human-computer relationships , 2005, TCHI.

[9]  Kai Riemer,et al.  The Work of belonging through Technology in Remote Work: a Case Study in tele-Nursing , 2016, ECIS.

[10]  Francesco Ferrari,et al.  Blurring Human–Machine Distinctions: Anthropomorphic Appearance in Social Robots as a Threat to Human Distinctiveness , 2016, International Journal of Social Robotics.

[11]  Mahdi Muhammad Moosa,et al.  Danger Avoidance: An Evolutionary Explanation of Uncanny Valley , 2010 .

[12]  Gregory J. Skulmoski,et al.  Journal of Information Technology Education the Delphi Method for Graduate Research , 2022 .

[13]  Martin Breidt,et al.  Face reality: investigating the Uncanny Valley for virtual faces , 2010, SIGGRAPH ASIA.

[14]  V. Leitáo,et al.  Computer Graphics: Principles and Practice , 1995 .

[15]  Karl F. MacDorman,et al.  Too real for comfort? Uncanny responses to computer generated faces , 2009, Comput. Hum. Behav..

[16]  Frank E. Pollick,et al.  In Search of the Uncanny Valley , 2009, UCMedia.

[17]  Himalaya Patel,et al.  The uncanny valley does not interfere with level 1 visual perspective taking , 2013, Comput. Hum. Behav..

[18]  Lars-Erik Gadde,et al.  Systematic combining: an abductive approach to case research , 2002 .

[19]  Karl F. MacDorman,et al.  Revisiting the uncanny valley theory: Developing and validating an alternative to the Godspeed indices , 2010, Comput. Hum. Behav..

[20]  Bryan R. Cole,et al.  Stability of response characteristics of a Delphi panel: application of bootstrap data expansion , 2005, BMC medical research methodology.

[21]  Gaurav Singal,et al.  Lateralization of face processing in the human brain , 2012, Proceedings of the Royal Society B: Biological Sciences.