Would You Rely on an Eerie Agent? A Systematic Review of the Impact of the Uncanny Valley Effect on Trust in Human-Agent Interaction

2025-05-08

AI Summary

This study systematically investigates how the Uncanny Valley Effect (UVE) influences human trust in artificial agents, addressing theoretical–empirical gaps arising from conceptual ambiguity and inconsistent operationalization. Following the PRISMA guidelines, we conducted a structured coding analysis of 53 empirical studies, examining agent embodiment, interaction modalities, and trust measurement dimensions. Results reveal a heavy reliance on static images and hypothetical scenarios—lacking ecologically valid, dynamic interaction—and a predominance of subjective self-report scales, with insufficient multimodal, behavioral, or implicit trust metrics. Key contributions include: (1) the first systematic analytical framework linking UVE to trust formation; (2) a novel, empirically grounded taxonomy for trust measurement; and (3) identification of critical methodological gaps, alongside concrete recommendations for future research emphasizing interactive, multimodal, and high-ecological-validity paradigms.

Technology Category

• Multiagent Systems: Multiagent Systems under Uncertainty
• Philosophy and Ethics of AI: Safety, Robustness & Trustworthiness
• Reasoning under Uncertainty: Uncertainty Representations

Application Category

• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

Trust is a fundamental component of human-agent interaction. With the increasing presence of artificial agents in daily life, it is essential to understand how people perceive and trust these agents. One of the key challenges affecting this perception is the Uncanny Valley Effect (UVE), where increasingly human-like artificial beings can be perceived as eerie or repelling. Despite growing interest in trust and the UVE, existing research varies widely in terms of how these concepts are defined and operationalized. This inconsistency raises important questions about how and under what conditions the UVE influences trust in agents. A systematic understanding of their relationship is currently lacking. This review aims to examine the impact of the UVE on human trust in agents and to identify methodological patterns, limitations, and gaps in the existing empirical literature. Following PRISMA guidelines, a systematic search identified 53 empirical studies that investigated both UVE-related constructs and trust or trust-related outcomes. Studies were analyzed based on a structured set of categories, including types of agents and interactions, methodological and measurement approaches, and key findings. The results of our systematic review reveal that most studies rely on static images or hypothetical scenarios with limited real-time interaction, and the majority use subjective trust measures. This review offers a novel framework for classifying trust measurement approaches with regard to the best-practice criteria for empirically investigating the UVE. As the first systematic attempt to map the intersection of UVE and trust, this review contributes to a deeper understanding of their interplay and offers a foundation for future research. Keywords: the uncanny valley effect, trust, human-likeness, affinity response, human-agent interaction

Problem

• Investigates how the Uncanny Valley Effect impacts trust in human-agent interactions
• Reviews inconsistent definitions and operationalizations of trust and UVE in research
• Identifies gaps in empirical studies on UVE and trust using PRISMA guidelines

Innovation

• Systematic review of Uncanny Valley Effect on trust
• Novel framework for classifying trust measurement approaches
• Analysis of 53 empirical studies on UVE and trust