Evaluating the Uncanny Valley Theory Based on Human Attitudes

Abstract

The uncanny valley theory is an idea pioneered by Masahiro Mori in 1970 in relation to the
\npsychological effects of lifelike robotics (Mori, 1970). The uncanny valley is a phenomenon
\nthat occurs in animation and robotic, wherein things that look extremely similar to the human
\nface, but with slight differences from the natural appearance or the natural movements and
\nexpressions of humans, that are found to be disturbing, uncanny, and revolting (Mewes &
\nHeloir, 2009). This study aimed to accomplish three goals: 1) analysing the participants’
\nattitudes towards digital characters based on a series of validated semantic differential
\nquestionnaires; 2) developing a conceptual model focusing on overcoming the uncanny
\nvalley theory in computer generated digital characters based on empirical findings; and
\n3) validating the theoretical model by providing specific guidelines for overcoming the
\nuncanny valley theory by avoiding negative human attitude responses. Based on results
\nfrom 229 participants, this study examined the key factors of digital characters from games
\nand movies which caused uncanny responses from the participants based on their attitudes.
\nThe structural model indicates that digital characters’ facial expressions have the strongest
\ninfluence on the participants’ perceived humanness, followed by the stimulus’s physical
\nmovements. Meanwhile, the digital characters’ animated hair has the next strongest
\ninfluence on the participants’ familiarity, followed by its facial expression.