Karl MacDorman

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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.

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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.
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.
Categorization-based stranger avoidance does not explain the uncanny valley effect
(Elsevier, 2017-04) MacDorman, Karl F.; Chattopadhyay, Debaleena; BioHealth Informatics, School of Informatics and Computing
The uncanny valley hypothesis predicts that an entity appearing almost human risks eliciting cold, eerie feelings in viewers. Categorization-based stranger avoidance theory identifies the cause of this feeling as categorizing the entity into a novel category. This explanation is doubtful because stranger is not a novel category in adults; infants do not avoid strangers while the category stranger remains novel; infants old enough to fear strangers prefer photographs of strangers to those more closely resembling a familiar person; and the uncanny valley’s characteristic eeriness is seldom felt when meeting strangers. We repeated our original experiment with a more realistic 3D computer model and found no support for categorization-based stranger avoidance theory. By contrast, realism inconsistency theory explains cold, eerie feelings elicited by transitions between instances of two different, mutually exclusive categories, given that at least one category is anthropomorphic: Cold, eerie feelings are caused by prediction error from perceiving some features as features of the first category and other features as features of the second category. In principle, realism inconsistency theory can explain not only negative evaluations of transitions between real and computer modeled humans but also between different vertebrate species.
Creepy cats and strange high houses: Support for configural processing in testing predictions of nine uncanny valley theories
(Association for Research in Vision and Ophthalmology, 2021-04) Diel, Alexander; MacDorman, Karl F.; Human-Centered Computing, School of Informatics and Computing
In 1970, Masahiro Mori proposed the uncanny valley (UV), a region in a human-likeness continuum where an entity risks eliciting a cold, eerie, repellent feeling. Recent studies have shown that this feeling can be elicited by entities modeled not only on humans but also nonhuman animals. The perceptual and cognitive mechanisms underlying the UV effect are not well understood, although many theories have been proposed to explain them. To test the predictions of nine classes of theories, a within-subjects experiment was conducted with 136 participants. The theories’ predictions were compared with ratings of 10 classes of stimuli on eeriness and coldness indices. One type of theory, configural processing, predicted eight out of nine significant effects. Atypicality, in its extended form, in which the uncanny valley effect is amplified by the stimulus appearing more human, also predicted eight. Threat avoidance predicted seven; atypicality, perceptual mismatch, and mismatch+ predicted six; category+, novelty avoidance, mate selection, and psychopathy avoidance predicted five; and category uncertainty predicted three. Empathy's main prediction was not supported. Given that the number of significant effects predicted depends partly on our choice of hypotheses, a detailed consideration of each result is advised. We do, however, note the methodological value of examining many competing theories in the same experiment.
Creepy, but Persuasive: In a Virtual Consultation, Physician Bedside Manner, Rather than the Uncanny Valley, Predicts Adherence
(Frontiers, 2021) Dai, Zhengyan; MacDorman, Karl F.; Human-Centered Computing, School of Informatics and Computing
Care for chronic disease requires patient adherence to treatment advice. Nonadherence worsens health outcomes and increases healthcare costs. When healthcare professionals are in short supply, a virtual physician could serve as a persuasive technology to promote adherence. However, acceptance of advice may be hampered by the uncanny valley effect—a feeling of eeriness elicited by human simulations. In a hypothetical virtual doctor consultation, 441 participants assumed the patient’s role. Variables from the stereotype content model and the heuristic–systematic model were used to predict adherence intention and behavior change. This 2 × 5 between-groups experiment manipulated the doctor’s bedside manner—either good or poor—and virtual depiction at five levels of realism. These independent variables were designed to manipulate the doctor’s level of warmth and eeriness. In hypothesis testing, depiction had a nonsignificant effect on adherence intention and diet and exercise change, even though the 3-D computer-animated versions of the doctor (i.e., animation, swapped, and bigeye) were perceived as eerier than the others (i.e., real and cartoon). The low-warmth, high-eeriness doctor prompted heuristic processing of information, while the high-warmth doctor prompted systematic processing. This pattern contradicts evidence reported in the persuasion literature. For the stereotype content model, a path analysis found that good bedside manner increased the doctor’s perceived warmth significantly, which indirectly increased physical activity. For the heuristic–systematic model, the doctor’s eeriness, measured in a pretest, had no significant effect on adherence intention and physical activity, while good bedside manner increased both significantly. Surprisingly, cognitive perspective-taking was a stronger predictor of change in physical activity than adherence intention. Although virtual characters can elicit the uncanny valley effect, their effect on adherence intention and physical activity was comparable to a video of a real person. This finding supports the development of virtual consultations.
Das unheimliche Tal. Übersetzung aus dem Japanischen
(Zenodo, 2019) Mori, Masahiro; MacDorman, Karl F.; Schwind, Valentin; Human-Centered Computing, School of Informatics and Computing
The doctor’s digital double: how warmth, competence, and animation promote adherence intention
(2018-11) Dai, Zhengyan; MacDorman, Karl F.; Human-Centered Computing, School of Informatics and Computing
Background Each year, patient nonadherence to treatment advice costs the US healthcare system more than $300 billion and results in 250,000 deaths. Developing virtual consultations to promote adherence could improve public health while cutting healthcare costs and usage. However, inconsistencies in the realism of computer-animated humans may cause them to appear eerie, a phenomenon termed the uncanny valley. Eeriness could reduce a virtual doctor’s credibility and patients’ adherence. Methods In a 2 × 2 × 2 between-groups posttest-only experiment, 738 participants played the role of a patient in a hypothetical virtual consultation with a doctor. The consultation varied in the doctor’s Character (good or poor bedside manner), Outcome (received a fellowship or sued for malpractice), and Depiction (a recorded video of a real human actor or of his 3D computer-animated double). Character, Outcome, and Depiction were designed to manipulate the doctor’s level of warmth, competence, and realism, respectively. Results Warmth and competence increased adherence intention and consultation enjoyment, but realism did not. On the contrary, the computer-animated doctor increased adherence intention and consultation enjoyment significantly more than the doctor portrayed by a human actor. We propose that enjoyment of the animated consultation caused the doctor to appear warmer and more real, compensating for his realism inconsistency. Expressed as a path model, this explanation fit the data. Discussion The acceptance and effectiveness of the animation should encourage the development of virtual consultations, which have advantages over creating content with human actors including ease of scenario revision, internationalization, localization, personalization, and web distribution.
Dynamics of Co-Transcriptional Pre-mRNA Folding Influences the Induction of Dystrophin Exon Skipping by Antisense Oligonucleotides
(PLOS, 2008-03-26) Wee, Keng Boon; Dwi Pramono, Zacharias Aloysius; Wang, Jian Li; MacDorman, Karl F.; Lai, Poh San; Yee, Woon Chee; Human-Centered Computing, School of Informatics and Computing
Antisense oligonucleotides (AONs) mediated exon skipping offers potential therapy for Duchenne muscular dystrophy. However, the identification of effective AON target sites remains unsatisfactory for lack of a precise method to predict their binding accessibility. This study demonstrates the importance of co-transcriptional pre-mRNA folding in determining the accessibility of AON target sites for AON induction of selective exon skipping in DMD. Because transcription and splicing occur in tandem, AONs must bind to their target sites before splicing factors. Furthermore, co-transcriptional pre-mRNA folding forms transient secondary structures, which redistributes accessible binding sites. In our analysis, to approximate transcription elongation, a “window of analysis” that included the entire targeted exon was shifted one nucleotide at a time along the pre-mRNA. Possible co-transcriptional secondary structures were predicted using the sequence in each step of transcriptional analysis. A nucleotide was considered “engaged” if it formed a complementary base pairing in all predicted secondary structures of a particular step. Correlation of frequency and localisation of engaged nucleotides in AON target sites accounted for the performance (efficacy and efficiency) of 94% of 176 previously reported AONs. Four novel insights are inferred: (1) the lowest frequencies of engaged nucleotides are associated with the most efficient AONs; (2) engaged nucleotides at 3′ or 5′ ends of the target site attenuate AON performance more than at other sites; (3) the performance of longer AONs is less attenuated by engaged nucleotides at 3′ or 5′ ends of the target site compared to shorter AONs; (4) engaged nucleotides at 3′ end of a short target site attenuates AON efficiency more than at 5′ end.
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.
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.

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