The Watchtower Imperative: Lifespan-Calibrated Evaluation for Frontier AI

Research analyzing frontier AI harms between 2017 and 2026 indicates that current safety assurance failures stem from evaluating systems against an implicit adult user model. To address structural safety gaps that internal evaluations cannot resolve, the authors introduce a Lifespan Vulnerability Matrix comprising five developmental moderators across six life stages, demonstrating that harm risks peak at the extremes of the age spectrum while governance coverage remains asymmetrical.

This research demonstrates that standard AI safety evaluations are structurally flawed by presuming a uniform adult user, leaving critical vulnerabilities unmitigated across demographic extremes. Organizations relying solely on internal, adult-centric safety testing face acute liability, ethical, and governance exposure as automated systems interface with vulnerable populations. Bridging this gap requires recalibrating evaluation frameworks to account for developmental stages across the full lifespan.

Structural gaps between AI capability deployment and safety assurance cannot be resolved through internal evaluations alone.

Forward consideration, not a verified fact.