论文标题
AI的认知拟人化：人类和计算机如何对图像进行分类
Cognitive Anthropomorphism of AI: How Humans and Computers Classify Images
论文作者
论文摘要
近年来，现代AI图像分类器取得了令人印象深刻的进步，但它们的性能通常看起来很奇怪或违反了对用户的期望。这表明人类从事认知拟人化：期望AI的性质与人类智力相同。这种不匹配给适当的人类互动带来了障碍。为了描绘这种不匹配，我检查了与图像分类器系统相比，我研究了人类分类的已知特性。基于此检查，我为系统设计提供了三种策略，可以解决人与AI分类之间的不匹配：可解释的AI，培训用户的新方法以及与人类认知相匹配的新算法。
Modern AI image classifiers have made impressive advances in recent years, but their performance often appears strange or violates expectations of users. This suggests 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 to 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.
