Serg discusses the evolution of interpretable machine learning, emphasizing the integration of counterfactuals and causal algorithms. He envisions a future where no-code and low-code tools streamline processes, allowing users to focus on hypothesis testing rather than programming. The convergence of automation, interpretability, and legal frameworks will revolutionize how machine learning models are developed and understood.
