The most capable AI system in the world is dangerous if it is pursuing the wrong objective. AI alignment is the field dedicated to ensuring that AI systems genuinely pursue what we intend, not a flawed approximation of it.

This is harder than it sounds. Human values are complex, context-dependent, and often difficult to articulate, let alone formalize into code. An AI system instructed to ‘maximize housing placements’ might optimize the speed and volume of assignments while overlooking the stability, safety, and neighborhood fit that determine whether a placement works for a family. At scale, these misalignments can compound in ways that are difficult to detect and costly to reverse.

The Lab’s alignment research focuses on how AI systems learn, represent, and act on human values, developing tools for interpretability (understanding what a system has learned to optimize), methods for robust value specification, and frameworks for evaluating whether deployed systems are behaving as intended. The stakes are high: as AI systems take on greater autonomy and decision-making authority, getting alignment right is not a technical nicety. It is a precondition for trust.