Again the non-sequitur argument of an explainable model must be worse than a deep learning system and there has to be a tradeoff. You don’t need to reduce comp

Again the non-sequitur argument of an explainable model must be worse than a deep learning system and there has to be a tradeoff. You don’t need to reduce complexity to induce explainability. You just need to decompose the function into smaller parts which you can understand. Contrastive LRP for example is a Function decomposition technique for explaining deep neural networks with high fidelity.