CONCEPT
Responsive Governance
Jasanoff's prescription for governing under uncertainty: treating decisions as provisional experiments — monitored, revised, and adapted as consequences emerge.
Responsive governance is Jasanoff's institutional model for decision-making under conditions of genuine uncertainty. It treats every governance choice as provisional rather than final — as a hypothesis to be tested through deployment, monitored for consequences, and revised in light of what monitoring reveals. The model requires four institutional capacities: mechanisms for detecting emergent consequences (including consequences no one predicted), processes for incorporating new evidence into governance revisions, authority to revise decisions without waiting for crisis, and cultural acceptance that revision is not failure but appropriate response to learning. Responsive governance stands in contrast to the stability paradigm that dominates most regulatory frameworks, which treat rules as permanent settlements requiring extraordinary justification to change. For AI, where capabilities and consequences evolve faster than any previous technology, the stability paradigm guarantees obsolescence. Responsive governance offers an alternative: institutions designed to learn at the pace reality demands.
In The You On AI Field Guide
Jasanoff introduced responsive governance in dialogue with adaptive management frameworks from ecology (C.S. Holling) and learning-organization theory from management (Peter