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What is artificial intelligence? Why is it important, and what does it have to do with engineering?

The AI learning adventure explores intelligence and its connection to engineering and technology.  Using ideas about human intelligence and intelligence more broadly, engineers can create “artificial intelligence,”; that is, impart “human” intelligence into machines or technology (Classical AI) or design technology that can itself “create” intelligence (future AI).  In fact, understanding how the brain works—”reverse-engineering the brain”—and understanding how engineers design intelligent machines—machines that replicate human intelligence—is one of the “Grand Challenges of Engineering” as set forth by The National Academy of Engineering (NAE).

The implications and benefits of understanding the brain are many.  In addition to advances in the treatment of brain injuries and diseases and advancements in communications technology and computer simulations, understanding the brain will allow the design of intelligent machines with even more signicant societal impacts.  Already, machines that compute, perform voice or facial recognition, respond to human prompts, and sense and monitor human activity are routine in today’s society.  The future capabilities of these machines—the limits and extremes of their “intelligence” and their ability to replicate human thinking—are dependent upon the engineer’s insight into human intelligence and the workings of the human brain.

One example of artificial intelligence is computers that try to appear more human in what they can do.  (You may have seen “chatterbots” computers that act like humans, on shopping websites like Ikea, for example.)  Other important themes in the learning adventure include how articial intelligence fits into the broader scope of technology's human roots and place in human society. For example, (“intelligent”) computers are the result of human invention and are used to further human goals.

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This material is based upon work supported by the National Science Foundation under Grant Nos. 1223868 and 1223460.  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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