Brian Cantwell Smith

A groundbreaking critique of the philosophical foundations of computing. Computational Reflections is a wholly original investigation into the philosophical foundations of computing. Brian Cantwell Smith distills a lifetime of work into this volume which explores what it means to compute. The standard theoretical foundations of computer science address the fundamental concept of "mechanism," but almost completely ignore the crucial role of "meaning" in any computational practice. Cantwell Smith takes the reader through these missing foundational gaps, including a historical analysis of why the field has reached its current state. Despite its lack of treatment of semantics ("meaning"), computer science has borrowed and adopted semantic vocabulary to refer to mechanistic concepts, thus aggravating confusion within and without the field, especially so in philosophy, cognitive science, and contemporary artificial intelligence. This book's arguments help to illustrate why computer science theory has almost nothing to say about "computation in the wild"--or the real-world practice of programmers and engineers who design the software and devices that we all use. The author argues that a true account of computation must do justice to the incredible complexity juggled by programmers in creating software that works, and he offers not only criticism, but also directions for a successor account of computing.

An argument that-despite dramatic advances in the field-artificial intelligence is nowhere near developing systems that are genuinely intelligent.In this provocative book, Brian Cantwell Smith argues that artificial intelligence is nowhere near developing systems that are genuinely intelligent. Second wave AI, machine learning, even visions of third-wave AI: none will lead to human-level intelligence and judgment, which have been honed over millennia. Recent advances in AI may be of epochal significance, but human intelligence is of a different order than even the most powerful calculative ability enabled by new computational capacities. Smith calls this AI ability "reckoning," and argues that it does not lead to full human judgment-dispassionate, deliberative thought grounded in ethical commitment and responsible action.Taking judgment as the ultimate goal of intelligence, Smith examines the history of AI from its first-wave origins ("good old-fashioned AI," or GOFAI) to such celebrated second-wave approaches as machine learning, paying particular attention to recent advances that have led to excitement, anxiety, and debate. He considers each AI technology's underlying assumptions, the conceptions of intelligence targeted at each stage, and the successes achieved so far. Smith unpacks the notion of intelligence itself-what sort humans have, and what sort AI aims at. Smith worries that, impressed by AI's reckoning prowess, we will shift our expectations of human intelligence. What we should do, he argues, is learn to use AI for the reckoning tasks at which it excels while we strengthen our commitment to judgment, ethics, and the world.