Recent work by Google shows progress on applying AI to diagnosing breast cancer. This work also highlights some key points.
- need to integrate machine learning models into hybrid human/AI systems
- need “explainablity” from machine learning models
- need to be able to seed machine learning models with existing knowledge to improve their performance
Here is the relevant observation:
While the AI system caught cancers that the radiologists missed, the radiologists … caught cancers that the AI system missed. Sometimes, all six U.S. readers caught a cancer that slipped past the AI, and vice versa … The cancers that the AI system caught were generally more invasive than those caught by the radiologists; the researchers didn’t have an explanation for the discrepancies.