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Abstract Uncanny Processing ABSTRACT UNCANNY PROCESSING: MISMATCHES BETWEEN PROCESSING STYLE AND FEATURAL CUES TO HUMANITY CONTRIBUTE TO UNCANNY VALLEY EFFECTS by Steven Michael Almaraz The uncanny valley is the tendency for highly humanlike, but non-human agents (e.g., robots, animated characters, dolls) to be perceived as creepy or unsettling, relative to their less humanlike counterparts. Recent research has pointed to mismatching signals of humanity as a possible explanation for the uncanny valley. The current work aimed to extend this hypothesis by investigating whether conflicting signals of humanity from face processing styles and featural cues can trigger negative affect. To this end, participants viewed faces that were morphed on a continuum from full dolls to full humans and indicated the extent to which these faces are unsettling. Critically, on half of the trials, faces were inverted to disrupt configural face processing, a processing style that involves viewing faces as a single Gestalt and is a cue for humanity. When faces were highly humanlike, they were experienced as less creepy than less humanlike faces, but when such targets were inverted, processing and featural signals did not disagree with one another, and some of the feelings of unease were alleviated. UNCANNY PROCESSING: MISMATCHES BETWEEN PROCESSING STYLE AND FEATURAL CUES TO HUMANITY CONTRIBUTE TO UNCANNY VALLEY EFFECTS A Thesis Submitted to the Faculty of Miami University in partial fulfillment of the requirements for the degree of Master of Arts by Steven Michael Almaraz Miami University Oxford, Ohio 2017 Advisor: Kurt Hugenberg Reader: Heather Claypool Reader: Jonathan Kunstman ©2017 Steven Michael Almaraz This Thesis titled UNCANNY PROCESSING: MISMATCHES BETWEEN PROCESSING STYLE AND FEATURAL CUES TO HUMANITY CONTRIBUTE TO UNCANNY VALLEY EFFECTS by Steven Michael Almaraz has been approved for publication by The College of Arts and Science and Department of Psychology ____________________________________________________ Kurt Hugenberg ______________________________________________________ Heather Claypool _______________________________________________________ Jonathan Kunstman Table of Contents Introduction ………………………………………………………………... 1 The Uncanny Valley …………………………………………………… 1 Configural Face Processing as a Perceptual Cue to Humanness ………. 4 Current Work …………………………………………………………... 7 k Experiment ………………………………………………………………… 8 Method …………………………………………………………………. 8 ….Participants ………………………………………………………….. 8 ….Materials …………………………………………………………….. 8 ….Procedure ………………………………………………………….… 9 Results ………………………………………………………………….. 9 ….Human Likeness ...…………………………………………………... 9 ….Uncannyness ……………………………………………………..... 10 k Discussion ………………………………………………………………... 11 References ………………………………………………………………... 16 k iii List of Figures Figure 1 ………………………...………………………………………… 20 Figure 2 ………………………...………………………………………… 21 Figure 3 ………………………...………………………………………… 21 Figure 4 ……………………...…………………………………………… 22 Figure 5 …………………………………………………………………... 23 k iv The uncanny valley is a phenomenon whereby people react to somewhat humanlike objects, usually dolls or robots with humanlike faces, with increasing positivity as the objects become more similar to humans, but only up to a point. As objects become very highly humanlike, they are often perceived negatively, and typically as “creepy” or “uncanny.” This sharp evaluative drop in appeal occurs just before a stimulus is perceived as truly human, and is known as the uncanny valley (see Figure 1). In his original observation of the uncanny valley, Mori (1970) proposed that understanding the uncanny valley is necessary if human-machine interactions are to improve as technology becomes more sophisticated. In the current work, I propose that understanding the uncanny valley can provide important insight into both how faces are processed, and how that face processing generates social inferences. Although extensive research has demonstrated that the uncanny valley is multiply determined, in the current work, I propose that the uncanny valley may be caused, at least in part, by perceivers employing configural face processing, which is typically reserved for human faces, for stimuli that are non- human. To this end, I begin with a discussion of the uncanny valley and its proposed causes, before moving on to discuss configural face processing and its relationship to the experience that a face is human. Finally, I then propose one study designed to test the relationship between configural face processing, the perception of humanness, and the uncanny valley. The Uncanny Valley Although the uncanny valley has a history of ad hoc demonstrations in literatures on robotics and human-machine interactions (Matsui, Minato, MacDorman, & Ishigoru, 2005; Minato, Shimada, Ishigoru, & Itakura, 2004; Mori, 1970), only recently have behavioral scientists worked to reliably replicate and explain the mechanisms behind the uncanny valley. The original concept devised to measure the uncanny valley (Mori, 1970), bukimi, translated loosely to “eeriness,” and a lack of shinwakan, which translates to “comfort.” These issues of eeriness and comfort remain central measurement foci in this research literature. More recently, some research has focused more on comfort or likeability (e.g., Bartneck, Kulić, Croft, & Zogbhi, 2009), other work has focused on discomfort or “eeriness,” associated with high arousal natural affect such as disgust, fear, and anxiety (e.g., Burleigh, Schoenherr, & Lacroix, 2013; Ho & MacDorman, 2010; Ho, MacDorman, & Pramono, 2008). In this latter vein, the most recent psychometric evidence (Ho & MacDorman, 2010) indicates that eeriness is a more optimal fit to the data in the uncanny valley literature. In the current paper, I will use the terms 1 uncanny, eerie, and creepy interchangeably (as is typical in the literature) to describe an affectively negative feeling incorporating nervousness, unattractiveness, disgust, and anxiety (e.g., MacDorman & Ishiguro, 2006; MacDorman et al., 2009; Mathur & Reichling, 2016; Pollick, 2009). In one of the first methodologically rigorous replications of the uncanny valley, MacDorman and Ishiguro (2006) morphed two images of robot faces with two images of human faces, creating images that varied in their objective humanness in 10% increments, ranging from fully robot to fully human. Participants rated each face morph, one at a time, along three dimensions: very machinelike to very humanlike, very strange to very familiar, and slightly eerie to extremely eerie. As predicted, they found that although there was a monotonic increase from machinelike to humanlike, ratings of familiarity (i.e., valence) showed an upward trend as the stimuli became more human, but with a dip near the middle, indicative of the uncanny valley. This drop in familiarity ratings approximately matched a peak on the eeriness scale, serving as one of the first rigorous demonstrations of the uncanny valley using highly controlled stimuli. More recently, Looser and Wheatley (2010) demonstrated similar findings using a closely related technique, but targeting perceptions of targets’ animacy. Similar to MacDorman and Ishiguro, Looser and Wheatley had participants judge a series of morphed doll-human faces, which ranged monotonically from 100% doll through 100% human, in 10% increments. Looser and Wheatley found that the perception that a stimulus is animate (i.e., is human; has a mind) is a non-linear function, relying heavily on high perceptual similarity to human faces. Highly humanlike, but inanimate faces are easily parsed from very similar but truly human faces. Further, and in line with the findings of the uncanny valley, these judgments are made categorically – that is, it is only when a face has a very strong perceptual signal of humanness is it judged as human. Somewhat human faces are still seen as inanimate. Although Looser and Wheatley did not collect data on evaluations, these humanlike yet inanimate faces would presumably be evaluated negatively (i.e., fall within the uncanny valley). Beyond establishing the uncanny valley effect, multiple researchers have recently investigated the causes of the uncanny valley. A number of theoretical mechanisms for the uncanny valley have been proposed, many of which argue that the uncanny valley is caused by perceivers experiencing conflicting signals of humanness and non-humanness from nearly human stimuli. 2 As previously noted, Looser and Wheatley (2010) established that perceptions of faces as possessing human traits is relatively categorical – we typically experience faces as either human or not. Some researchers have suggested that stimuli which fall right at the boundary between these two categories (human and non-human) generate ambiguity, and this disfluency in categorizing the stimuli may be experienced as unease or eeriness (i.e., the uncanny valley; MacDorman & Ishigoru, 2006; Pollick, 2009; Ramey, 2005). A closely related, but separable model suggests that inconsistencies between how people are expected to look or act, and how a humanlike entity actually looks or acts leads to the feelings of eeriness that constitute the uncanny valley (Brenton, Gillies, Ballin, & Chatting, 2005; Kätsyri, Förger, Mäkäräinen, & Takala, 2015; Pollick 2009). Though the basic form of this argument simply states that there will be unease in response to inconsistencies between expectations and perceptions, different scholars have argued for the importance of different inconsistencies. For example, both Brenton and colleagues (2005) and
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