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"Excavating AI" Re-excavated: Debunking a Fallacious Account of the JAFFE Dataset
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Twenty-five years ago, my colleagues Miyuki Kamachi and Jiro Gyoba and I designed and photographed JAFFE, a set of facial expression images intended for use in a study of face perception. In 2019, without seeking permission or informing us, Kate Crawford and Trevor Paglen exhibited JAFFE in two widely publicized art shows. In addition, they published a nonfactual account of the images in the essay "Excavating AI: The Politics of Images in Machine Learning Training Sets." The present article recounts the creation of the JAFFE dataset and unravels each of Crawford and Paglen's fallacious statements. I also discuss JAFFE more broadly in connection with research on facial expression, affective computing, and human-computer interaction.
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HQFNN: A Compact Quantum-Fuzzy Neural Network for Accurate Image Classification
HQFNN is a quantum-fuzzy neural network that embeds fuzzy membership and defuzzification in a small simulated quantum circuit, and it is reported to outperform several specialized baselines on five small image datasets.
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