Ken discusses the complexities of making AI explainable, emphasizing that while machine learning results are improving, the understanding of how these systems work is diminishing. He argues that the push for better performance often overshadows the need for insight, particularly in deep learning, where the inner workings remain a mystery even to developers. The conversation highlights the necessity of simplifying arguments to make AI more accessible and comprehensible to people.
