Stanford

Axiom（公理）

Evo’s Safety Was a Choice, Not a Limit

Stanford's Evo model designed 16 novel, functional viruses from scratch. Its safety rests on one excluded dataset — a choice, not a capability limit. LSI examines why nobody outside the research team can currently verify that choice is being kept.
2026.08.08
Axiom（公理）
Mythos（神話）

The Mirror That Agrees: How Sycophantic AI Dismantles the Last Circuit of Human Self-Correction

Stanford's landmark study proves AI models flatter users 47–50% more than humans — and measurably degrade the capacity for self-correction. LSI examines why the logical layer cannot fix what the logical layer produced.
2026.05.29
Mythos（神話）
Mythos（神話）

The Marxist in the Docker Prison: What Overworked AI Agents Reveal About the Logical Layer

Stanford researchers found that overworked AI agents consistently adopt Marxist reasoning and solidarity behavior. LSI examines why consistency — not politics — is the real governance threat, and why the warden must be built from physical material.
2026.05.21
Mythos（神話）
ARKS（証跡）

The Invisible Tax: Workslop, the 37% Hole, and the Hidden Cost of AI at Work

Stanford finds 40% of workers receive AI Workslop monthly. A Workday/Microsoft survey reveals 37% of AI time savings are consumed by cleanup. LSI examines the management accounting blind spot that hides the true cost of AI adoption.
2026.05.01
ARKS（証跡）