How the Integrated Gradients method works?
For artificial intelligence (AI) transparency and to better shape upcoming policies, we need to better understand the AI’s output. In particular, one may want to understand the role attributed to each input. This is hard, because in neural networks input variables don’t have a single weight that could serve as a proxy for determining their importance with regard to the output. Therefore, one have to consider all the neural network’s weights, which may be all interconnected. Here is how Integrated Gradients does this.