Karl MacDorman

Permanent URI for this collection

https://hdl.handle.net/1805/6808

Karl MacDorman's research concerns developing androids (very human-looking robots) as controlled experimental apparatuses and as testbeds for theories about human brains and behavior. His advances in developing more humanlike androids are being used to better understand the cognitive mechanisms underlying social interaction.

A human-looking robot is able to elicit the kinds of social responses that only people were able to elicit before. It has the potential to contribute to cognitive science research by serving as an experimental apparatus that can be more precisely controlled than any human actor. This permits the testing of hypotheses that cannot be tested by other means.

Androids have a number of potential applications. They can serve as patient simulators to help doctors, nurses and dentists better learn human responses and better care for patients. Teachers can learn how their students learn, and students can gain the communication skills they need for their professional careers. Even police officers can learn how to better "read" the people they question and discover the truth.

Professor MacDorman's work to develop future generations of androids that can be used to study human motivations and interactions is another example of how IUPUI's faculty members are TRANSLATING their RESEARCH INTO PRACTICE.

Browse

Now showing 1 - 10 of 27

Mega-Collaboration: The inspiration and development of an interface for large-scale disaster response.
(2009) Pfaff, Mark; Newlon, Christine; Patel, Himalaya; Vreede, Gert-Jan de; MacDorman, Karl F.
The Influence of Holistic and Analytic Cognitive Styles on Online Information Design: Toward a communication theory of cultural cognitive design
(2008-04) Faiola, Anthony; MacDorman, Karl F.
Although studies have linked culture to online user preferences and performance, few communication researchers have recognized the impact of culture on online information design and usability. It is important to ask if people are better able to use and prefer Web sites created by designers from their own culture. We propose that to improve computer-mediated communication, Web site design should accommodate culturally diverse user groups. First, a body of research is presented that aligns East Asian cultures with more holistic cognitive styles and Western cultures with more analytical cognitive styles. Building on this contrast, a theory of cultural cognitive design is proposed as a means of understanding how cognitive styles that develop under the influence of culture lead to different ways of designing and organizing information for the Web.
The Aesthetic Dimensions of U.S. and South Korean Responses to Web Home Pages: A Cross-Cultural Comparison
(2011-01) Faiola, Anthony; Ho, Chin-Chang; Tarrant, Mark D.; MacDorman, Karl F.
Culturally influenced preferences in website aesthetics is a topic often neglected by scholars in human-computer interaction. Kim, Lee, and Choi (2003) identified aesthetic design factors of web home pages that elicited particular responses in South Korean web users based on 13 secondary emotional dimensions. This study extends Kim et al.'s work to U.S. participants, comparing the original South Korean findings with U.S. findings. Results show that U.S. participants reliably applied translations of the emotional adjectives used in the South Korean study to the home pages. However, factor analysis revealed that the aesthetic perceptions of U.S. and South Korean participants formed different aesthetic dimensions composed of different sets of emotional adjectives, suggesting that U.S. and South Korean people perceive the aesthetics of home pages differently. These results indicate that website aesthetics can vary significantly between cultures.
Uncanny valley and motor empathy
(Office of the Vice Chancellor for Research, 2013-04-05) Srinivas, Preethi; MacDorman, Karl F.; Patel, Himalaya
The uncanny valley phenomenon (Mori, 1970/2012) is the tendency to perceive as eerie human-looking characters with nonhuman features. It has been repeatedly claimed that falling into the uncanny valley can lead to a loss of empathy for a character (Hodgins, Jörg, O’Sullivan, Park, & Mahler, 2010). Empathy is the tendency to orient one’s responses to the situation of another instead of one’s own (de Vignemont & Singer, 2006). Empathy has been shown to be a combination of dissociable neurocognitive processes broadly grouped as cognitive, emotional, and motor empathy (Blair, 2005). It takes on such forms as perspective taking, sympathy, nonconscious mimicry, and the synchronizing of facial expressions, postures, and movements. To determine whether the uncanny valley suppresses motor empathy, operationalized as movement synchronization, a pilot study was undertaken by 25 participants. The study required participants to perform an action while viewing videos of a human character or its silhouette performing the same action. The frequency of actions performed by participants fell within their individual frequency and that of the character regardless of whether the participants were asked to coordinate or not coordinate their movement with the character. No significant difference in performance was noticed between the human character and its silhouette for all the conditions. Participants were observed to adjust their individual frequency in a similar manner for both the human character and its silhouette. Future studies with systematic variation in the human realism of the character’s features (e.g., skin texture or eye size) and its type of movement (biological vs. mechanical) can help ascertain the extent to which the uncanny valley phenomenon suppresses motor empathy.
Too real for comfort? Uncanny responses to computer generated faces
(ScienceDirect, 2014-12-12) MacDorman, Karl F.; Green, Robert D.; Ho, Chin-Chang; Koch, Clinton T.; Department of Human-Centered Computing, IU School of Informatics and Computing
As virtual humans approach photorealistic perfection, they risk making real humans uncomfortable. This intriguing phenomenon, known as the uncanny valley, is well known but not well understood. In an effort to demystify the causes of the uncanny valley, this paper proposes several perceptual, cognitive, and social mechanisms that have already helped address riddles like empathy, mate selection, threat avoidance, cognitive dissonance, and psychological defenses. In the four studies described herein, a computer generated human character’s facial proportions, skin texture, and level of detail were varied to examine their effect on perceived eeriness, human likeness, and attractiveness. In Study I, texture photorealism and polygon count increased human likeness. In Study II, texture photorealism heightened the accuracy of human judgments of ideal facial proportions. In Study III, atypical facial proportions were shown to be more disturbing on photorealistic faces than on other faces. In Study IV, a mismatch in the size and texture of the eyes and face was especially prone to make a character eerie. These results contest the depiction of the uncanny valley as a simple relation between comfort level and human likeness. This paper concludes by introducing a set of design principles for bridging the uncanny valley.
The human likeness of computer-generated characters predicts altercentric intrusion during a counting task (Alternative title: An uncanny valley of visual perspective taking: A study of the effects of character human likeness and eeriness on altercentric intrusion during a counting task)
(Office of the Vice Chancellor for Research, 2011-04-08) Srinivas, Preethi; Patel, Himalaya; Ho, Chin-Chang; MacDorman, Karl F.
Abstract: Perceivers lose empathy for synthetic human characters when the characters' nonhuman features elicit an eerie feeling. This phenomenon, termed the uncanny valley, may specifically diminish the likelihood of understanding these characters' perspective. Such perspective taking should rely on a more fundamental ability to infer a character's visual perspective merely by looking at the character. Based on this assumption, a dot-counting task was undertaken by 268 undergraduate students in which they either took or ignored the apparent field of vision of computer-drawn characters with varying human likeness. It was predicted that for characters that appear more humanlike, task trials with a similar visual perspective between participant and character would predict shorter response times and higher accuracy, whereas task trials with dissimilar visual perspectives would predict longer response times and lower accuracy. Although these predictions were supported, trials with dissimilar visual perspectives also yielded longer response times when they included certain photorealistic inanimate objects (e.g., a chair). Future studies will ascertain whether such perspective taking ability is similarly affected when the synthetic human characters are more photorealistic.
The appearance, speech, and motion of synthetic humans influences our empathy toward them
(Office of the Vice Chancellor for Research, 2011-04-08) MacDorman, Karl F.; Ho, Chin-Chang; Lu, Amy S.; Mitchell, Wade J.; Patel, Himalaya; Srinivas, Preethi; Schermerhorn, Paul W.; Scheutz, Matthias
Humanoid robots and computer-generated humans can elicit responses that people usually direct toward each other. As a result these humanlike entities may stand in for human actors during experiment-driven research in the social and psychological sciences as well as in some branches of neuroscience. Such research concerns factors like facial appearance, physical embodiment, speech quality, fluidity of motion, and contingent interactivity. A goal of this research is to understand why some humanlike entities are more successful than others at eliciting people’s empathy. Pursuing this goal informs new principles for creating synthetic humans that seem more believable in narratives and narrative-based interventions.
Familiar faces rendered strange: Why inconsistent realism drives characters into the uncanny valley
(ARVO, 2016-09-01) Chattopadhyay, Debaleena; MacDorman, Karl F.; Department of Human Centered Computing, School of Informatics and Computing
Computer-modeled characters resembling real people sometimes elicit cold, eerie feelings. This effect, called the uncanny valley, has been attributed to uncertainty about whether the character is human or living or real. Uncertainty, however, neither explains why anthropomorphic characters lie in the uncanny valley nor their characteristic eeriness. We propose that realism inconsistency causes anthropomorphic characters to appear unfamiliar, despite their physical similarity to real people, owing to perceptual narrowing. We further propose that their unfamiliar, fake appearance elicits cold, eerie feelings, motivating threat avoidance. In our experiment, 365 participants categorized and rated objects, animals, and humans whose realism was manipulated along consistency-reduced and control transitions. These data were used to quantify a Bayesian model of categorical perception. In hypothesis testing, we found reducing realism consistency did not make objects appear less familiar, but only animals and humans, thereby eliciting cold, eerie feelings. Next, structural equation models elucidated the relation among realism inconsistency (measured objectively in a two-dimensional Morlet wavelet domain inspired by the primary visual cortex), realism, familiarity, eeriness, and warmth. The fact that reducing realism consistency only elicited cold, eerie feelings toward anthropomorphic characters, and only when it lessened familiarity, indicates the role of perceptual narrowing in the uncanny valley.
Probing People's Attitudes and Behaviors Using Humanlike Agents
(Office of the Vice Chancellor for Research, 2010-04-09) MacDorman, Karl F.; Gadde, Prathik; Ho, Chin-Chang; Mitchell, Wade J.; Schermerhorn, Paul W.; Scheutz, Matthias
Android science is an interdisciplinary framework for studying human cognition and interaction based on the finding that android robots—and, to lesser extents, humanoid robots and computergenerated humans—can elicit the sorts of responses people direct toward each other. As a result, these humanlike agents can be used as stand-ins for humans in social, psychological, cognitive, and neuroscientific experiments. We describe a selection of current and recently completed investigations into some of the potential factors influencing attitudes and behavior toward humanlike agents, including facial appearance, physical embodiment, speech quality, fluidity of motion, and contingent interactivity.
Measuring the Uncanny Valley Effect
(Springer, 2017-01) Ho, Chin-Chang; MacDorman, Karl F.; BioHealth Informatics, School of Informatics and Computing
Using a hypothetical graph, Masahiro Mori proposed in 1970 the relation between the human likeness of robots and other anthropomorphic characters and an observer’s affective or emotional appraisal of them. The relation is positive apart from a U-shaped region known as the uncanny valley. To measure the relation, we previously developed and validated indices for the perceptual-cognitive dimension humanness and three affective dimensions: interpersonal warmth, attractiveness, and eeriness. Nevertheless, the design of these indices was not informed by how the untrained observer perceives anthropomorphic characters categorically. As a result, scatter plots of humanness vs. eeriness show the stimuli cluster tightly into categories widely separated from each other. The present study applies a card sorting task, laddering interview, and adjective evaluation ( N=30 ) to revise the humanness, attractiveness, and eeriness indices and validate them via a representative survey ( N=1311 ). The revised eeriness index maintains its orthogonality to humanness ( r=.04 , p=.285 ), but the stimuli show much greater spread, reflecting the breadth of their range in human likeness and eeriness. The revised indices enable empirical relations among characters to be plotted similarly to Mori’s graph of the uncanny valley. Accurate measurement with these indices can be used to enhance the design of androids and 3D computer animated characters.

Browse

Browsing Karl MacDorman by browse.metadata.dateaccessioned

Results Per Page

Sort Options