Introduction Artificial intelligence is a fast-growing branch of computer science, a discipline famous for its interdisciplinarity and free-spirited interest in next-generation chal- lenges of automation. Within universities, it encompasses the study of intelligent agents, autonomous programs that sense and actively respond to data collected in an environment. The virtual assistants Alexa and Siri are examples of intelligent agents. Agents may be embedded in smart robots, such as driverless cars and unmanned aerial vehicles. More broadly, artificial intelligence describes real or imagined efforts to simu- late cognition and creativity. The term distinguishes machine and code from the natural intelligence of animals and people. But artificial intelligence (AI) research- ers often view the brain as a natural computer and the mind as a human-made computer program. AI pioneer Herbert Simon distinguished them this way: natu- ral occurrences possess an “air of ‘necessity’ about them” as they observe physical laws artificial phenomena have an “air of ‘contingency’ in their malleability” (Simon 1981, ix–xi). Even so, humans have only a handful of natural characteris- tics that limit their ability to learn, improve, and invent. Indeed, they are very good at adding complexity to their environment. The way forward, Simon rea- soned, is not to retreat to the natural state, but to create more of the artificial world that people cannot do without. A lot of AI has disappeared into the applications and devices we use every day. It’s become so routine we don’t even recognize it anymore. Bank software and Internet search engines are examples. Journalist Pamela McCorduck has identified this as the AI effect: “[I]t’s part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something— play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, but ‘that’s not thinking’” (McCorduck 2004, 204). Instead, it might be helpful to frame artificial intelligence analogous to the way computer science generally has been defined by the “new new” and “next big” things—as transformative smart systems and technologies that haven’t been invented yet. Mathematician John McCarthy coined the term “artificial intelli- gence” in 1956 to attract participants to the Dartmouth Summer Research Project, the Constitutional Convention of AI, and also boldly mark the divide between new and old approaches to understanding brain and machine. This liberating view is
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