AI Alignment & Value-Locking on Singularity Streets is about one deceptively simple mission: keep increasingly capable systems pointed at what we actually want—today, tomorrow, and after a thousand upgrades. Alignment asks whether an AI’s goals match human intent; value-locking asks whether that match can remain stable as the system learns, scales, and encounters strange new situations. The challenge is that intelligence doesn’t just follow instructions—it optimizes. If your target is fuzzy, incomplete, or easy to game, a powerful optimizer can hit the metric and miss the meaning. That’s where the real work begins: translating values into constraints, shaping incentives, building reliable oversight, and creating safe “rails” for tool use and autonomy. You’ll see ideas like corrigibility (staying open to correction), robust reward design, debate and verification, interpretability, and red-teaming that stress-tests systems under pressure. But alignment isn’t only a technical puzzle; it’s a human one. Whose values? Which tradeoffs? What counts as harm? This page is your map of the core concepts, the most promising approaches, and the sharp questions that decide whether progress stays steerable.
AI Alignment & Value-Locking
