_Computational thinking cisely. Stating the difficulty of a problem accounts builds on the power and for the underlying power of the machine—the com- limits of computing puting device that will run the solution. We must processes, whether they are exe- consider the machine’s instruction set, its resource cuted by a human or by a constraints, and its operating environment. machine. Computational In solving a problem efficiently,, we might further methods and models give us ask whether an approximate solution is good (...) the courage to solve prob- enough, whether we can use randomization to our lems and design systems that no one of us would advantage, and whether false positives or false nega- be capable of tackling alone. Computational think- tives are allowed. Computational thinking is refor- ing confronts the riddle of machine intelligence: mulating a seemingly difficult problem into one we What can humans do better than computers? and know how to solve, perhaps by reduction, embed- What can computers do better than humans? Most ding, transformation, or simulation. fundamentally it addresses the question: What is Computational thinking is thinking recursively. It computable? Today, we know only parts of the is parallel processing. It is interpreting code as data answers to such questions. and data as code. It is type checking as the general- Computational thinking is a fundamental skill for ization of dimensional analysis. It is recognizing everyone, not just for computer scientists. To read- both the virtues and the dangers of aliasing, or giv- ing, writing, and arithmetic, we should add compu- ing someone or something more than one name. It tational thinking to every child’s analytical ability. is recognizing both the cost and power of indirect Just as the printing press facilitated the spread of the addressing and procedure call. It is judging a pro- three Rs, what is appropriately incestuous about this gram not just for correctness and efficiency but for vision is that computing and computers facilitate the aesthetics, and a system’s design for simplicity and spread of computational thinking. (shrink)

In the future systems of ambient intelligence will include decision support systems that will automate the process of discrimination among people that seek entry into environments and to engage in search of the opportunities that are available there. This article argues that these systems must be subject to active and continuous assessment and regulation because of the ways in which they are likely to contribute to economic and social inequality. This regulatory constraint must involve limitations on the collection and use (...) of information about individuals and groups. The article explores a variety of rationales or justifications for establishing these limits. It emphasizes the unintended consequences that flow from the use of these systems as the most compelling rationale. (shrink)