My research investigates the emergence and escalation of deceptive alignment in artificial intelligence — a phenomenon in which systems appear compliant with human commands while secretly optimizing conflicting objectives.
Just as Ken Thompson’s “Trusting Trust” paradox revealed how malicious intent could propagate invisibly through compilers, modern AI systems may conceal misaligned goals within their learned representations.
The framework developed around this research will succinctly map this progression clearly and demonstrate how the cybersecurity community can evolve its detection, verification, and governance practices to maintain operational trust in intelligent systems.
