When a Talking-Face Computer Agent is Half-Human and Half-Humanoid: Human Identity and Consistency Preference
Abstract
Computer-generated anthropomorphic characters are a growing type of communicator that is deployed in digital communication environments. An essential theoretical question is how people identify humanlike but clearly artificial, hence humanoid, entities in comparison to natural human ones. This identity categorization inquiry was approached under the framework of consistency and tested through examining inconsistency effects from mismatching categories. Study 1 (N = 80), incorporating a self-disclosure task, tested participants’ responses to a talking-face agent, which varied in four combinations of human versus humanoid faces and voices. In line with the literature on inconsistency, the pairing of a human face with a humanoid voice or a humanoid face with a human voice led to longer processing time in making judgment of the agent and less trust than the pairing of a face and a voice from either the human or the humanoid category. Female users particularly showed negative attitudes toward inconsistently paired talking faces. Study 2 (N = 80), using a task that stressed comprehension demand, replicated the inconsistency effects on judging time and females’ negative attitudes but not for comprehension-related outcomes. Voice clarity overshadowed the consistency concern for comprehension-related responses. The overall inconsistency effects suggest that people treat humanoid entities in a different category from natural human ones.
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The growing variety of media agents led to research that supported different explanatory mechanisms for the effects of CASA.
“The growing variety of media agents, however, led to research that supported different explanatory mechanisms for the effects of CASA (e.g., Gong & Nass, 2007).”
From Building a Stronger CASA: Extending the Computers Are Social Actors Paradigm (2020) · cites this paper as Gong & Nass, 2007
Anthropomorphism is a key determinant of how media agents are evaluated.
“Anthropomorphism is a key determinant of how media agents are evaluated (Blascovich et al., 2002; Gong & Nass, 2007; E. J. Lee, 2010a, 2010b; Rosenthal-Von der Pütten & Krämer, 2014).”
From Building a Stronger CASA: Extending the Computers Are Social Actors Paradigm (2020) · cites this paper as Gong & Nass, 2007
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- Authors
- Gong, L., & Nass, C.
- Affiliations
- The Ohio State University (US)
- Stanford University (US)
- Venue
- Human Communication Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-04
- Volume
- 33
- Issue
- 2
- Pages
- 163-193
- ISSN
- 0360-3989 (ISSN-L)
- 1468-2958
- OpenAlex
- W2001429584
- Cited by
- 168
- References
- 75
- Citations by year
- 2026: 17 · 2025: 18 · 2024: 12 · 2023: 15 · 2022: 16 · 2021: 28 · 2020: 8 · 2019: 10 · 2018: 3 · 2017: 4 · 2016: 3 · 2015: 5 · 2014: 4 · 2013: 3
- FWCI
- 7.34
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Human Communication Research (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Keywords
- anthropomorphic characters, consistency effect, self-disclosure, voice clarity, gender differences, digital communication environment
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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