From Containment to Coexistence: A Resilience-First Social Model for Human-AI Cybersecurity

Artificial intelligence can expand both cyber offense and defense, yet reliable control of individual AI systems does not ensure lasting control over the societal distribution of comparable capabilities. This paper develops a conceptual framework for cybersecurity under the planning assumption that operationally useful offensive AI may diffuse beyond effective centralized control. It does not predict that such diffusion is inevitable. The framework connects capability-proliferation risk, Regulatory Delay, a broader Defense Window, Defense Democratization, reduction of effective Defense Gaps, digital resilience, and independent cyber-physical safety. Its central mechanism is the conversion of temporary regulatory and technological advantages into maintained defensive capacity across organizations, especially those unable to sustain specialist security teams. AI may multiply scarce expertise, but access must become affordable, integrated protection rather than additional tools or alerts. The Defense Gap describes the difference between effective offensive and defensive capability in a specified organizational and threat context; numerical use requires a defensible common scale. Because prevention and defensive AI can fail, the architecture also requires containment, trustworthy recovery, graceful degradation, and separately protected mechanisms for reaching or maintaining safe physical states. The contribution is an integrative societal transition architecture, not a claim to originate preparation windows, offense-defense comparisons, or resilience. A source-grounded literature discussion identifies these overlaps, and conditional propositions specify where the framework would require revision or rejection. The equations provide conceptual structure, not empirical estimates, and do not establish society-wide effectiveness, an optimal policy, or feasibility under every threat scenario.