A researcher questions why the AI industry isn't combining modern neural networks with deterministic rule-based systems—an approach that could address current AI reliability issues. Classical expert systems offered explainability and consistency but required expensive human expertise to build; today's AI achieves expert-level performance but lacks interpretability and reliability guarantees.
Why it matters: As enterprises face growing pressure to deploy trustworthy, auditable AI in regulated industries, hybrid architectures combining neural networks with rule-based reasoning could unlock both performance and explainability—a potential competitive advantage being largely ignored.