One of the most noticeable trends in recent years has been the increasing reliance of public decision-making processes on algorithms, i.e. computer-programmed step-by-step instructions for taking a given set of inputs and producing an output. The question raised by this article is whether the rise of such algorithmic governance creates problems for the moral or political legitimacy of our public decision-making processes. Ignoring common concerns with data protection and privacy, it is argued that algorithmic governance does pose a significant threat (...) to the legitimacy of such processes. Modelling my argument on Estlund’s threat of epistocracy, I call this the ‘threat of algocracy’. The article clarifies the nature of this threat and addresses two possible solutions. It is argued that neither solution is likely to be successful, at least not without risking many other things we value about social decision-making. The result is a somewhat pessimistic conclusion in which we confront the possibility that we are creating decision-making processes that constrain and limit opportunities for human participation. (shrink)

What psychological and philosophical significance should we attach to recent efforts at computer simulations of human cognitive capacities? In answering this question, I find it useful to distinguish what I will call "strong" AI from "weak" or "cautious" AI. According to weak AI, the principal value of the computer in the study of the mind is that it gives us a very powerful tool. For example, it enables us to formulate and test hypotheses in a more rigorous and precise fashion. (...) But according to strong AI, the computer is not merely a tool in the study of the mind; rather, the appropriately programmed computer really is a mind, in the sense that computers given the right programs can be literally said to. (shrink)

Examines the author's idea of object-oriented philosophy, wherein things, and how they interact with one another, are the center of philosophical interest.

_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)