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Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

Data-driven psychophysical methods to diversify SIAs and address bias.

Valentina Gosetti¹, Rachael E Jack¹

¹School of Psychology and Neuroscience, University of Glasgow, 62 Hillhead Street, Glasgow, G12 8QB Scotland, UK.

Journal on Multimodal User Interfaces

|March 30, 2026

Summary

Socially Interactive Agents (SIAs) need cultural adaptation for effective engagement. Using reverse correlation, we can model user expectations to design culturally inclusive SIAs, enhancing trust and reducing bias.

Keywords:

Bias mitigation Cultural diversity Data-driven modeling Human social perception Socially interactive agents

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Last Updated: Mar 31, 2026

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

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Published on: June 3, 2013

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A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

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Published on: March 1, 2022

Area of Science:

Human-Computer Interaction
Artificial Intelligence
Social Robotics

Background:

Socially Interactive Agents (SIAs) often exhibit White- and Western-centric biases.
These biases limit SIAs' ability to interpret and express social cues across diverse cultures.
Current SIAs struggle with effective engagement due to a lack of cultural adaptability.

Purpose of the Study:

To address limitations in current SIAs' cross-cultural social cue interpretation and expression.
To propose a data-driven method for creating culturally adaptive and inclusive SIAs.
To enhance user engagement and trust in SIAs by grounding them in user-specific models.

Main Methods:

Utilizing the data-driven psychophysical method of reverse correlation.
Modeling users' perceptual expectations, preferences, and sociocultural norms.
Integrating user insights into the design of SIA appearance and expressive behavior.

Main Results:

Demonstrated the potential of reverse correlation for modeling user-specific social expectations.
Showcased how this method enables SIAs to exhibit psychologically grounded social signals.
Provided examples of culturally adaptive and ethnically inclusive SIA designs.

Conclusions:

Reverse correlation offers a viable approach to developing culturally sensitive SIAs.
Empirically derived user models can improve SIA engagement, trust, and inclusivity.
This approach contributes to mitigating algorithmic bias and real-world prejudice.