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Interpretable Machine Learning Through Teaching
OpenAI published a method in 2018 that trains AI systems to teach each other using examples that are also interpretable to humans. The approach automatically selects maximally informative examples to convey a concept, such as representative images for a category like 'dogs'. Experiments showed the method effective at teaching both AI systems and humans, bridging machine learning interpretability with pedagogical example selection.