In one of the most unorthodox yet necessary programming books ever to appear, Daniel Kohanski, a seasoned programmer and systems consultant, delves into the foundational concepts and basic mechanics of computers and computer programming. Rather than writing yet another book that teaches readers how to write code, Kohanski penetrates more deeply into the nature of programming istelf. By exploring what programming is all about, The Philosophical Programmer: Reflections on the Moth in the Machine offers an introduction for the computer neophyte as well as an opportunity for experienced programmers to understand better the fundamental nature of their craft.

Anyone who develops software for a living needs a proven way to produce it better, faster, and cheaper. The Productive Programmer offers critical timesaving and productivity tools that you can adopt right away, no matter what platform you use. Master developer Neal Ford not only offers advice on the mechanics of productivity-how to work smarter, spurn interruptions, get the most out your computer, and avoid repetition-he also details valuable practices that will help you elude common traps, improve your code, and become more valuable to your team. You'll learn to: Write the test before you write the code Manage the lifecycle of your objects fastidiously Build only what you need now, not what you might need later Apply ancient philosophies to software development Question authority, rather than blindly adhere to standards Make hard things easier and impossible things possible through meta-programming Be sure all code within a method is at the same level of abstraction Pick the right editor and assemble the best tools for the job This isn't theory, but the fruits of Ford's real-world experience as an Application Architect at the global IT consultancy ThoughtWorks. Whether you're a beginner or a pro with years of experience, you'll improve your work and your career with the simple and straightforward principles in The Productive Programmer.

In this fascinating look at the computer's brain and the people who designed it, Kohanski assesses the programmer's trade, including the demands, limitations, and challenges of creating computer systems, and defines the important role they play in the modern world. of photos.

Colburn (computer science, U. of Minnesota-Duluth) has a doctorate in philosophy and an advanced degree in computer science; he's worked as a philosophy professor, a computer programmer, and a research scientist in artificial intelligence. Here he discusses the philosophical foundations of artificial intelligence; the new encounter of science and philosophy (logic, models of the mind and of reasoning, epistemology); and the philosophy of computer science (touching on math, abstraction, software, and ontology).

Object Thinking blends historical perspective, experience, and visionary insight - exploring how developers can work less like the computers they program and more like problem solvers.

Can humans and artificial intelligences share concepts and communicate? One aim of Making AI Intelligible is to show that philosophical work on the metaphysics of meaning can help answer these questions. Cappelen and Dever use the externalist tradition in philosophy of to create models of how AIs and humans can understand each other. In doing so, they also show ways in which that philosophical tradition can be improved: our linguistic encounters with AIs revel that our theories of meaning have been excessively anthropocentric. The questions addressed in the book are not only theoretically interesting, but the answers have pressing practical implications. Many important decisions about human life are now influenced by AI. In giving that power to AI, we presuppose that AIs can track features of the world that we care about (e.g. creditworthiness, recidivism, cancer, and combatants.) If AIs can share our concepts, that will go some way towards justifying this reliance on AI. The book can be read as a proposal for how to take some first steps towards achieving interpretable AI. Making AI Intelligible is of interest to both philosophers of language and anyone who follows current events or interacts with AI systems. It illustrates how philosophy can help us understand and improve our interactions with AI.