A meta-analysis of the uncanny valley's independent and dependent variables

Diel, Alexander, Weigelt, Sarah and Macdorman, Karl F. 2022. A meta-analysis of the uncanny valley's independent and dependent variables. ACM Transactions on Human-Robot Interaction 11 (1) , pp. 1-33. 10.1145/3470742

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Abstract

The uncanny valley (UV) effect is a negative affective reaction to human-looking artificial entities. It hinders comfortable, trust-based interactions with android robots and virtual characters. Despite extensive research, a consensus has not formed on its theoretical basis or methodologies. We conducted a meta-analysis to assess operationalizations of human likeness (independent variable) and the UV effect (dependent variable). Of 468 studies, 72 met the inclusion criteria. These studies employed 10 different stimulus creation techniques, 39 affect measures, and 14 indirect measures. Based on 247 effect sizes, a three-level meta-analysis model revealed the UV effect had a large effect size, Hedges’ g = 1.01 [0.80, 1.22]. A mixed-effects meta-regression model with creation technique as the moderator variable revealed face distortion produced the largest effect size, g = 1.46 [0.69, 2.24], followed by distinct entities, g = 1.20 [1.02, 1.38], realism render, g = 0.99 [0.62, 1.36], and morphing, g = 0.94 [0.64, 1.24]. Affective indices producing the largest effects were threatening, likable, aesthetics, familiarity, and eeriness, and indirect measures were dislike frequency, categorization reaction time, like frequency, avoidance, and viewing duration. This meta-analysis—the first on the UV effect—provides a methodological foundation and design principles for future research.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Schools > Psychology
Publisher:	ACM
ISSN:	2573-9522
Date of First Compliant Deposit:	8 March 2022
Date of Acceptance:	1 May 2021
Last Modified:	01 Dec 2024 12:45
URI:	https://orca.cardiff.ac.uk/id/eprint/148120

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