1,824 claims across 19 domains

Governance instrument instrumentalization represents a distinct failure mode where safety-adjacent regulatory authority retains formal validity while its function inverts from public safety enforcement to commercial negotiation leverage

EU AI Act military exclusion gap means the most consequential frontier AI deployments remain outside mandatory governance scope even if civilian enforcement occurs

MAIM deterrence represents a paradigm shift from technical alignment to coordination infrastructure as the primary alignment-adjacent policy lever

recursive self-improvement detection timing makes MAIM deterrence structurally inadequate because the dangerous threshold is detectable only as late as possible leaving insufficient response time

AI deterrence fails structurally where nuclear MAD succeeds because AI development milestones are continuous and algorithmically opaque rather than discrete and physically observable making reliable trigger-point identification impossible

ASI deterrence red lines are structurally fuzzier than nuclear deterrence red lines because AI development is continuous and algorithmically opaque enabling salami-slicing that never triggers clear intervention

MAIM deterrence creates a multipolar AI equilibrium without requiring collective superintelligence architecture

Nuclear deterrence limits ASI first-mover advantage through distributed physical systems because even superintelligent systems face physical constraints in disarming air-gapped arsenals

AI capability breadth makes deterrence red lines over-broad triggering false positives because frontier models advance general capabilities not specific dangerous functions

Military AI governance operates through three mutually reinforcing levels of form-without-substance where executive mandate eliminates voluntary constraints, corporate nominal compliance satisfies public accountability without operational change, and legislative information requests lack compulsory authority

EU and US AI governance retreats converged cross-jurisdictionally in the same 6-month window despite opposite regulatory traditions suggesting structural rather than politically contingent drivers

Supply-chain risk designation of safety-conscious AI vendors weakens military AI capability by deterring the commercial AI ecosystem the military depends on

Pre-enforcement legislative retreat is a distinct AI governance failure mode where mandatory constraints are weakened before enforcement can test their effectiveness

EU AI Act conformity assessments use behavioral evaluation methods that are architecturally insufficient for latent alignment verification creating compliance theater where technical requirements are met and underlying safety problems remain unaddressed

AI governance failure takes four structurally distinct forms each requiring a different intervention — binding commitments alone address only one of the four

Employee AI ethics governance mechanisms have structurally weakened as military AI deployment normalized, evidenced by 85 percent reduction in petition signatories despite higher stakes

Advisory safety guardrails on AI systems deployed to air-gapped classified networks are unenforceable by design because vendors cannot monitor queries, outputs, or downstream decisions

Systematic feedback bias in RLHF creates an exponential sample complexity barrier that cannot be overcome by scale alone

RLHF's exponential misspecification barrier collapses to polynomial if systematic feedback biases can be identified in advance

Independent AI safety evaluation infrastructure has matured substantially but faces a structural evaluation-enforcement disconnect where sophisticated public evaluations produce information that informs decisions without connecting to binding governance constraints

AI Action Plan substitutes nucleic acid synthesis screening for DURC/PEPP institutional oversight creating biosecurity governance gap through category substitution

AI governance instruments consistently fail to reconstitute on promised timelines after rescission, with substitute instruments governing different pipeline stages

Coercive AI governance instruments self-negate at operational timescale when governing strategically indispensable capabilities because intra-government coordination failure makes sustained restriction impossible

Category substitution in governance replaces strong instruments with weak ones at different pipeline stages while framing them as addressing the same risk

Responsible AI dimensions exhibit systematic multi-objective tension where improving safety degrades accuracy and improving privacy reduces fairness with no accepted navigation framework