Yampolskiy warns recursive self-improvement renders AI uncontrollable

The control problem isn't a distant abstraction; it's actively compounding as developers use current LLMs to optimize the architecture of future models.

• –AI-assisted coding tools drastically accelerate the feedback loop, creating a controllability gap where innovation outpaces safety verification
• –Mathematical limits like the Halting Problem suggest that aligning a significantly smarter system may be theoretically impossible, not just practically difficult
• –The expanding black-box nature of deep learning means decision-making becomes inherently less explainable as systems scale in intelligence
• –This perspective challenges the industry's default strategy of building first and solving alignment later, framing AGI pursuit as an existential gamble