Kill Conditions

If the combination of peripheral physiology + AI-derived signals + behavioral data fundamentally cannot resolve the state distinctions the architecture requires, it is correct in principle but unbuildable.

If AI understanding capabilities plateau or regress such that the machine cannot maintain a sufficiently accurate model of human values and state, the architecture collapses to sophisticated biofeedback.

If the meta-capability defense fails, if consent/capacity circularity is irresolvable, or if procedural autonomy theories are shown inadequate, the objective function justification weakens or fails.

If steering toward long-term values during short-term maladaptive behavior cannot be operationally distinguished from paternalistic control, the caring orientation creates the very principal-agent problem it claims to solve.

If a simpler architecture (machine-as-controller or pure biofeedback) produces equal or greater long-term self-directed action capacity, the added complexity is unjustified.

If operationalizing caring produces only paternalism or persuasion as implementable options, the caring orientation cannot be instantiated as specified.

If a system explicitly optimizing engagement or compliance produces equal or greater long-term capacity, the caring constraints and capacity-as-objective governance are unnecessary overhead.

If the understanding layer's error rate on value attribution produces worse outcomes than a no-understanding baseline, the layer is net harmful.