Examples of computability in group organizations include: probabilistic computation of quantum groups and Satoshi Nakamoto's longest chain computation in Bitcoin. Individual Turing machine computability is the mainstream of what we currently consider computable. There’s a fundamental difference between group organization computability and individual Turing machine computability: Individual Turing machine computability pursues consistency/determinism. Group organization computability, on the other hand, pursues completeness, where the consistency of the group is not deterministic. For example, a class is a group. The student with the shortest hair in the class is a group computation attribute, not an individual computation attribute. The student with the shortest hair in the class changes dynamically and does not belong to any specific individual but rather to the organization of the class as a group. Before Satoshi Nakamoto created Bitcoin, in the field of computability, people automatically treated group computation as individual computation. That is, the entire computability industry only had the theory of individual Turing machine computability and no theory of group computability. If we want to solve production relationships and address the group organizational relationships in social sciences, we need to rethink and establish a new theory of group organization computability, rather than using individual Turing machine computability theory to construct a centralized, deterministic organization that loses the uncertainty of the group.