Cognitive Anthropomorphism of AI: How Humans and Computers Classify Images
Document Type
Article
Publication Date
7-1-2020
Department
Department of Cognitive and Learning Sciences
Abstract
© 2020 by Human Factors and Ergonomics Society. Modern artificial intelligence (AI) image classifiers have made impressive advances in recent years, but their performance often appears strange or violates expectations of users. This suggests that humans engage in cognitive anthropomorphism: expecting AI to have the same nature as human intelligence. This mismatch presents an obstacle to appropriate human-AI interaction. To delineate this mismatch, I examine known properties of human classification, in comparison with image classifier systems. Based on this examination, I offer three strategies for system design that can address the mismatch between human and AI classification: explainable AI, novel methods for training users, and new algorithms that match human cognition.
Publication Title
Ergonomics in Design
Recommended Citation
Mueller, S.
(2020).
Cognitive Anthropomorphism of AI: How Humans and Computers Classify Images.
Ergonomics in Design,
28(3), 12-19.
http://doi.org/10.1177/1064804620920870
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/2210