Dimension Human Likeness
Dimension Human Likeness - Related Videos
07:34
Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
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Cited by 25 •
2013
Investigation of the Uncanny Valley Hypothesis and affective experience requires an understanding of the hypothesis' dimension of human likeness (DHL). This protocol allows representation of the DHL and examination of categorical perception. Use of the same stimuli and fMRI to distinguish brain regions responsive to physical and category change is illustrated.
14:05
One Dimensional Turing-Like Handshake Test for Motor Intelligence
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Cited by 10 •
2010
We present a Turing-like Handshake test administered through a telerobotic system in which the interrogator is holding a robotic stylus and interacting with another party (human or artificial). We use a forced choice method, and extract a measure for the similarity of the artificial model to a human handshake.
08:31
Three-dimensional Alginate-bead Culture of Human Pituitary Adenoma Cells
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Cited by 5 •
2016
Three-dimensional culture in alginate beads, due to its simplicity and reproducibility, was chosen to maintain the pituitary adenoma cells. The procedures included an initial enzymatic digestion and mechanical dissociation of the tumor tissue, and the subsequent cell suspension was encapsulated in alginate beads.
11:22
Three-dimensional Imaging of Nociceptive Intraepidermal Nerve Fibers in Human Skin Biopsies
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Cited by 5 •
2013
In order to study the changes of nociceptive intraepidermal nerve fibers (IENFs) in painful neuropathies (PN), we developed protocols that could directly examine three-dimensional morphological changes observed in nociceptive IENFs. Three-dimensional analysis of IENFs has the potential to evaluate the morphological changes of IENF in PN.
09:32
Human Cartilage Tissue Fabrication Using Three-dimensional Inkjet Printing Technology
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Cited by 85 •
2014
The methods described in this paper show how to convert a commercial inkjet printer into a bioprinter with simultaneous UV polymerization. The printer is capable of constructing 3D tissue structure with cells and biomaterials. The study demonstrated here constructed a 3D neocartilage.
FAQs
Human-associated cues influence judgments by giving observers signals about whether an artificial system seems socially understandable or person-like. Facial features and movement contribute perceptual information, while language, emotional expression, and social responses provide communicative and behavioral information. Together, these cues can shape whether people attribute intentions, emotions, or social capabilities to the entity.
The cues matter because observers do not respond only to an entity’s physical appearance. Communication, emotional expression, movement, and social responses can alter how they interpret the system and what capacities they believe it has. In behavioral research, examining these cues helps connect observable design features with perceptions of anthropomorphism and with patterns of interaction.
Dimension Human Likeness is broader than a judgment based only on visual appearance. It considers whether an entity resembles a person through appearance, communication, and behavior, so a system may be evaluated through language, movement, emotional expression, or social responses as well as facial features. This broader view is relevant when appearance alone cannot explain observers’ reactions.
Emotional expression and social responses provide cues about an artificial entity’s apparent capacity for participation in social interaction. Observers may use those cues when deciding whether the system has emotions, intentions, or social capabilities. Consequently, these features are important components of behavioral assessment, especially when a study examines how people interpret or engage with robots or virtual agents.
Researchers can apply the framework by evaluating the human-associated cues presented by an artificial system and then examining observers’ perceptions and interactions. The assessment can consider facial features, language, movement, emotional expression, and social responses rather than relying on one cue. This links properties of the system to perceived anthropomorphism and behavior toward the system.
It can reveal whether observers attribute intentions, emotions, or social capabilities to an artificial entity. Those outcomes help explain how people interpret and interact with the system, providing behavioral evidence about the social meaning of its design. The framework therefore supports research into how human-associated cues influence perception and engagement with artificial agents.
Applications include the design and evaluation of social robots, virtual environments, and human-computer interaction systems. In these settings, the framework helps researchers consider how an entity’s appearance, communication, and behavior may affect perceived anthropomorphism. It also provides behavioral context for assessing whether users interpret an artificial agent as having intentions, emotions, or social capabilities.