An organization is presented for implementing solutions to knowledge- based Artificial Intelligence problems. The hypothesize-and-test paradigm is used as the basis for cooperation among many diverse and independent knowledge sources (KS's). The KS's are assumed individually to be errorful and incomplete. A uniform and integrated multi-level structure, the blackboard holds the current state of the system. Knowledge sources cooperate by creating, accessing, and modifying elements in the blackboard. Each level in the blackboard specifies a different representation of the problem space; the sequence of levels forms a loose hierarchy in which the elements at each level can approximately be described as abstractions of elements at the next lower level. The elements at each level in the blackboard are hypotheses about some aspect of that level. The internal structure of an hypothesis consists of a fixed set of attributes; this set is the same for hypotheses at all levels of representation in the blackboard. These attributes are selected to serve as mechanisms for implementing the data-directed hypothesize-and-test paradigm and for efficient goal-directed scheduling of KS's. The HearsayII speech- understanding system is an implementation of this organization; it is used here as an example for descriptive purposes.