The Longevity Revolution: How Artificial Intelligence is Challenging the Paradigm of Evolutionary Canalization (Preprint)

UNSTRUCTURED Classical evolutionary theory, notably Riedl’s concept of canalization, suggests that human lifespan is constrained by deeply entrenched developmental architectures, implying that aging is an immutable biological reality. However, rapid advancements in artificial intelligence (AI) from 2023 to 2025 have begun to challenge this pessimism. This viewpoint synthesizes recent developments to argue that AI is reframing aging from a biological mystery into a tractable engineering challenge. We examine two primary frontiers: the use of autonomous AI agents and generative models to discover geroprotective interventions, including the identification of compounds like ouabain via large-scale omics re-analysis; and the maturation of multi-modal “aging clocks” that utilize deep learning to enable precision diagnostics and personalized healthspan optimization. While acknowledging significant limitations regarding safety, translation from animal models, and the risks of commercial hype, we conclude that the integration of AI with mechanistic geroscience offers a plausible pathway toward a proactive, engineering-based approach to human longevity.