We study a novel model in which agents arrive sequentially one after the other and each in turn chooses one action from a fixed set of actions to maximize his expected rewards given the information he possesses at the time of arrival. The information that becomes available affects the incentives of an agent to explore and generate new information. We characterize the optimal disclosure policy of a planner whose goal is to maximizes social welfare. The planner's optimal policy is characterized and shown to be intuitive and very simple to implement. As the number of agents increases the social welfare converges to the optimal welfare of the unconstrained mechanism. One interpretation for our result is the implementation of what is known as the 'Wisdom of the crowds'. This topic has become more relevant during the last decade with the rapid adaptation of the Internet. This is a joint work with Ilan Kremer and Motty Perry.