Interpretable Machine Learning Through Teaching
Analysis
The article describes a novel approach to improve the interpretability of AI models. The method focuses on having AIs teach each other using human-understandable examples. The core idea is to select the most informative examples to explain a concept, like using the best images to represent 'dogs'. The article highlights the effectiveness of this approach in teaching AIs.
Key Takeaways
Reference
“Our approach automatically selects the most informative examples to teach a concept—for instance, the best images to describe the concept of dogs—and experimentally we found our approach to be effective at teaching both AIs”