When to dehumanize a chatbot: effects of humanlike design and individual differences on the uncanny valley

Abstract

Humanlike chatbots are becoming increasingly popular with the rise of Artificial Intelli- gence (AI). However, their humanlike nature can also evoke fear and skepticism. People tend to anthropomorphize these chatbots—attributing a mind to the AI—which can lead to discomfort, a phenomenon known as the uncanny valley. Existing research lacks clar- ity on how perceived humanlikeness relates to the uncanny valley and which individual factors shape its perception.This study examines the relationship between perceived humanness and feelings of dis- comfort or strangeness, identifying the behavioral and design features that contribute to these effects. Additionally, it explores which user groups are more likely to perceive an agent as uncanny. Grounded in anthropomorphism theory, an online experiment was con- ducted, comparing interactions with a humanlike and a machinelike chatbot. The study examined individual differences in the tendency to anthropomorphize and their relation to the uncanny valley. Furthermore, it investigated whether higher perceived anthropomor- phism intensifies eerie feelings. Qualitative feedback on behavioral and humanlike design cues provided insights into which features contributed to uncanniness.Findings indicate that humanlike cues significantly impact perceived anthropomorphism and the uncanny valley, suggesting a linear relationship between perceived humanlikeness and perceived strangeness. Individual factors, such as the tendency to anthropomorphize and age, further positively influence this effect. Qualitative insights provide guidance for chatbot designers, highlighting which features should be carefully implemented to avoid the uncanny valley and how to integrate humanlike cues effectively.author: Julienne BuecheleEnthält Literaturverzeichnis auf Seite 68-78Masterarbeit Paris-Lodron-University Salzburg, Joint Master Programme on Human-Computer Interaction 2025Masterarbeit Salzburg University of Applied Sciences 202

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Last time updated on 27/04/2025

This paper was published in eplus (Univ. of Salzburg).

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