Anthropic Fellows Program AI Safety, Economics, And Research Methods Practice Test

Constitutional AI centers on a formal set of high-level, verifiable principles—the AI’s constitution—that guide what the model should output and how it should defer to other judgments. This creates auditable constraints on behavior rather than relying on opaque, ever-shifting human preference signals used to shape rewards. The idea is to reduce value drift: by grounding decisions in a transparent rule set, the model stays within agreed norms even as tasks change or data shifts occur. Outputs are produced with the constitution in mind, and the system can defer or escalate when a principle is ambiguous or conflicts arise, keeping safety and alignment more predictable. This stands in contrast to approaches that depend on fixed reward signals, non-verifiable guidelines, or post-hoc explanations to enforce safety.