The overarching idea of Jupyter is that humans matter. The context of this statement is that in data science and computationally intensive research and development, the weight of technical concerns often dominates: algorithms, programming languages, systems and software architecture, and so on. In this context, human concerns and problems are often secondary at best. Jupyter lives in this universe: its software and users are technically sophisticated and its primary usage case is solving complex problems with code and data. In spite of this, we claim that the primary problems that Jupyter solves are uniquely human. What are these human problems that Jupyter solves? To answer this, we briefly discuss three dimensions of Jupyter: interactive computing, computational narratives, and the idea that Jupyter is more than software. We conclude by describing how these ideas have enabled communities of practice to be created across a broad range of computational domains.