Pichai outlined a bevy of artificial intelligence enhancements and moves to put more machine learning models on devices, but the bigger takeaway for developers and data scientists may be something called TCAV. TCAV is short for Testing with Concept Activation Vectors. In a nutshell, TCAV is an interpretability method to understand what signals your neural network models use for prediction.
In theory, TCAV's ability to understand signals could surface bias because it would highlight whether males were a signal over females and surface other issues such as race, income and location. Using TCAV, computer scientists can see how high value concepts are valued.
TCAV, which doesn't require models to be retrained to use it, is an effort to dissect models and illustrate why a model is making a certain decision. For instance, a model that identified a zebra may identify it using more high level concepts. Here's an illustration: