Can Science Explain What Makes Robots Creepy?
What neuroscience and psychology reveal about the brain’s response to robots.
Posted Sep 17, 2020
Life-size dolls. Amusement park automatons. Realistic robots. Why do some of these humanlike forms elicit positive responses, while others seem disturbing and downright creepy? Are humans hard-wired to feel more uneasy and fearful the more realistic robots become? Last week Emory University psychologists published in the journal Perception a study that provides insights on the cognitive mechanisms of this phenomenon known as the uncanny valley.
Half a century ago, Masahiro Mori, a professor of robotics at the Tokyo Institute of Technology, published his uncanny valley hypothesis sans fanfare in the esoteric Japanese journal Energy. Mori put forth the theory that robots with humanlike features are more likeable than purely machine-like ones — up to a certain point. As a humanlike object becomes more realistic, it starts to approach the so-called uncanny valley, where it no longer elicits positive emotional responses from the viewer and starts to become disturbing and off-putting.
Mathematically, this can be expressed as a graph with viewer affinity on the y-axis, and human likeness on the x-axis. As an object such as a robot becomes more humanlike, the line that represents the relationship between the viewer’s affinity and human likeness of the object eventually dips significantly to form a valley. On the graph, likeable toy robots would be on the positive slope and prosthetic hands in the uncanny valley.
The Emory University research team of Wang Shensheng, Yuk Fai Cheong, Daniel Dilks and Philippe Rochat tested the hypothesis that the human brain is doing more than just anthropomorphizing when looking at androids.
Anthropomorphizing is attributing human traits, behavior, emotion or form to non-human beings or objects. Anthropomorphism can be commonly found in books, animation, and movies. Examples of anthropomorphized fictional characters include Pinocchio — a wily wooden marionette, C-3PO — an affable and quite courteous fictional robot from Star Wars, Thomas the Tank Engine — a cheeky, over-excitable steam engine of Sodor, and HAL 9000 — a conflicted sentient artificial intelligence (AI) computer from the epic film 2001: A Space Odyssey inspired by Arthur C. Clarke’s novels.
First, 62 participants provided feedback on emotional responses to and the human likeness of 89 synthetic and real human faces. Next, a different set of 62 participants performed a visual looming task with the same 89 faces so the team could measure the perceived threat. Then the study enlisted 36 participants to sort faces as synthetic or real in a timed task, allowing researchers to measure categorical uncertainty associated with the perception of how alive or animate the image seemed.
The researchers observed that the “perceived animacy decreased as a function of exposure time only in android but not in human or mechanical-looking robot faces.” When it was apparent that an object is human or mechanical, the perceived animacy (quality of being alive), did not lower over time. The uncanniness in androids are connected to the “temporal dynamics of face animacy perception.” This study suggests that the drop in perceived animacy of the viewer is the reason for the uncanny valley phenomenon.
In the past decades, there have been numerous research studies that attempt to explain the uncanny valley phenomena. These theories vary in approach and explanations.
From a social neuroscience perspective, is the uncanny valley a window into the social brain’s predictive processing? Scientists at the University of California San Diego (UCSD) monitored the brain activity of 20 participants, using electroencephalogram (EEG), while they viewed video clips in two modes (motion only and still-then-motion) with a humanoid robot, a realistic robot, and a human performing actions such as drinking from a cup, hand-waving, throwing a piece of paper, and so forth. In their study published in 2018 in Neuropsychologia, the researchers attribute the negative reaction of the uncanny valley to violations of a person’s predictions about human norms when confronted with an artificial but realistic human form.
Can the turning point to negativity for realistic robots be due to underlying neurological mechanisms? A team of psychology and neuroscience researchers from the University of Cambridge and University Duisburg-Essen published last summer in the Journal of Neuroscience their functional MRI (fMRI) study of the neural activity of 26 participants who were shown pictures of different robots and humans. The researchers posit that the uncanny valley response is due to the nonlinear value-coding in a key area of the brain’s reward system, the ventromedial prefrontal cortex.
“A distinct amygdala signal predicted rejection of artificial agents,” wrote the UK and German researchers. “Our data suggest that human reactions toward artificial agents are governed by a neural mechanism that generates a selective, nonlinear valuation in response to a specific feature combination (humanlikeness in nonhuman agents).”
Is it possible that the uncanny valley phenomenon is not related at all to the human-likeness factor, but rather is due to something like cognitive dissonance? Psychology researchers from the University of Guelph, Canada and the Yale University School of Medicine propose that the uncanny valley reflects a general form of stimulus devaluation that happens when inhibition is triggered to resolve conflicting stimulus-related representations. In their study published in Frontiers in Psychology, the authors attribute the uncanny valley to conflicting perceptual cues that elicit psychological discomfort. The researchers studied the reactions from 69 participants who viewed various computer-generated morph images such as human-robot, human-stag, human-tiger, human-lion, and human-bird.
“Negative affect for stimuli within an Uncanny Valley context may therefore occur to the extent that selecting one stimulus interpretation over the other requires inhibition of visual-category information associated with the non-selected interpretation,” wrote the researchers. “The greater the inhibition during identification, the greater the negative affect for the associated stimulus.”
What does the uncanny valley theory, a concept that emerged half a century ago, hold for the future? The worldwide robotics market is projected to increase at a compound annual growth rate of 26 percent to reach nearly $210 billion by 2025, according to figures from Statista. Factoring in the potential for the uncanny valley phenomenon may be rising in importance in the market segment of personal and service robotics, where there are high levels of interaction between humans and robots, as opposed to in the industrial robots sector. Going beyond aesthetics, and taking into account the numerous research studies of the uncanny valley phenomenon, may be a key competitive advantage in robotics design in the not-so-distant future.
Copyright © 2020 Cami Rosso All rights reserved.