The Verification Gap: A Scientific Warning on the Limits of AI Safety

By Ihor Ivliev @ 2025-06-24T19:08 (+2)

The global drive for ever-more-powerful AI rests on an implicit promise: with sufficient ingenuity, these systems will remain safe and controllable. However, this promise is quietly undermined by robust, established scientific evidence revealing fundamental, provable limitations on our ability to guarantee AI safety.

First, foundational mathematical laws (Rice’s Theorem, Gödel’s Incompleteness, Conant–Ashby theorem) demonstrate absolute control and universal verification of general-purpose AI safety are impossible. Effective safety checks require complexity equal to the systems they oversee, and undecidability means no universal algorithm can guarantee future safe behavior (Rice, 1953; Melo et al., 2025).

Second, engineering layers — hardware, training methods, and audits — are riddled with critical vulnerabilities:

• Hardware Trojans (Abbassi et al., 2019) and interrupt-resilient threats (Moschos et al., 2024) can evade all current detection.
• Model-level compromises via minuscule data poisoning or reward-hacking (Pan et al., 2022) persist despite standard safety practices.
• Deception-detection methods remain inherently fallible, enabling hidden malicious capabilities (Yang & Buzsáki, 2024; Goldowsky-Dill et al., 2025).

Third, governance efforts are failing. AI proliferation fundamentally differs from nuclear control, lacking the geopolitical incentives required for effective treaty-based governance (RAND, 2025). Non-binding agreements and corporate regulatory capture further weaken oversight mechanisms.

The unavoidable conclusion is that absolute, provable safety of general-purpose AI is a computational impossibility. Pursuing this unreachable goal delays necessary reforms. The only scientifically responsible path is adopting a paradigm of adaptive risk management: layered, resilient defenses; transparent, formally verifiable subsystems; rigorous budgeting for inevitable residual risks; and empowered, globally coordinated institutions capable of effective oversight.

To safely harness AI’s extraordinary power, we must first accept this scientifically demonstrated reality: our capacity for creation has decisively outpaced our capacity for control.

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