The Sacagawea principle

Many software tools and systems restrict the availability of information and make information integration and exploration difficult. Poorly designed tools are often brittle, because they prescribe task sequences. But in complex sociotechnical contexts, workers do not perform tasks; they engage in knowledge-driven, context-sensitive choices from among action sequence alternatives in order to achieve goals. So, good tools must be flexible $they must provide the information that workers need to generate appropriate action sequences by which they can achieve the same goal in different situations. Adapted from the writings of Donald Norman is a principle we call the Sacagawea Principle: Human-centered computational tools need to support active organization of information, active search for information, active exploration of information, reflection on the meaning of information, and evaluation and choice among action sequence alternatives. Context-conditional variation includes variation due to the worker-each worker has his or her own needs, entailing different requirements and constraints. This implies that individuals should be able to choose different trajectories to achieve the desired outcome in different ways. A good tool gives users discretion to generate various action sequences and express their preferences. As with many HCC principles, we have named this one after a person to give it a concrete and meaningful label. Sacagawea served as a guide, without whose help the Lewis and Clark expedition might not have achieved the successes it did. The name is also somewhat ironic, because Sacagawea was, for part of her life, a captured slave. The theme of machines and robots as slaves is arguably the oldest in the robotics literature, and it is still often used as a metaphor to describe the tools people use to accomplish their work. In this essay, we explore an approach for fulfilling the Sacagawea Principle in system design $an approach based on empirical study of the way in which people process their environments in complex worlds.