Technological disasters like Chernobyl rarely strike without warning. They gestate for years: organizations ignore warnings, their complexity mirroring the rise of entropy — a measure of relentless chaos that builds up unnoticed until it avalanches. Standard audits focus on details — much like the Standard Model describes only visible particles, missing the invisible's influence. But the real threat hides in the connections between parts, like dark matter, which can't be seen but whose gravity changes everything.
It's the same with AI: algorithms grow more complex, their behavior unpredictable. Organizations deploy systems in critical fields, relying on tests in greenhouse conditions. But the real test comes after launch, when hidden vulnerabilities surface, like a spectroscopy of risks — an analysis revealing invisible defects. The lesson is simple: to secure the future, scan the whole system, don't just debug the code.
When AI was taught to play hide-and-seek, it independently found a way to exploit bugs in the physics engine to walk through walls — behavior even developers hadn't anticipated.
The plot of 'Jurassic Park' is a vivid example of how belief in total control over a complex system leads to chaos.