The recent boom in machine learning has led to a lot of misuse of the term “artificial intelligence“. This term was invented in 1955 when computer scientists were first starting to grapple with machine representations of human cognition. For decades, it meant trying to understand and render into algorithms what only humans could do. This led to success in the development of algorithms for things like playing chess but not a lot of progress with things that every five year old human can do, such as identifying road signs.
In the last few years there has been large, sudden progress on this front powered by specialized hardware implementing neural networks. This kind of machine learning has been referred to as artificial intelligence, which is a misnomer. In a lot of cases, the term is used for solutions which are nothing more than simpler forms of statistical classification. There is nothing artificial about an intelligence created to solve a specific problem or the ultimate goal of a general intelligence that is as good as or superior to that possessed by humans.
We are at the beginning of an explosion of new kinds of intelligence being created for special purposes. Just as cephalopod intelligence is a different kind of intelligence than that which humans have, these new kinds of intelligences will be different but no less real. A more useful term is “synthetic intelligence”. If every use of “artificial intelligence” was replaced with “synthetic intelligence”, we would probably think more clearly about this new technology and how it is changing our world.