Cognitive Anthropomorphism of AI: How Humans and Computers Classify Images

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 year

  2020

• Venue

  Ergonomics in design

• Publication date

  2020-02-07

• Fields of study

  Computer Science, Psychology

• Identifiers
  DOI 10.1177/1064804620920870arXiv 2002.03024
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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