Moving AI out of its infancy: changing our preconceptions

Explicit symbolic logic has faded from prominence, but the close coupling of AI and the digital computer, and of thought and the stepwise algorithm, seem about as strong and unquestioned as ever. Of course there's connectionism, but this too is mired in false assumptions that date back a long way. And it seems to have dragged neuroscience down with it to the extent that we now seem unable to think about real brains without resorting to models that owe too much of their inspiration to the three-layer perceptron. Traditional AI has excelled at solving certain kinds of problems. It can make systems that learn but not in any generally applicable way. AI is about making machines do what humans use intelligence to do, and often this doesn't actually require the machines to show any intelligence at all. But for many tasks, especially in robotics, the ability to see, learn, and perform complex motor actions is a prerequisite that the traditional approach has utterly failed to fulfill.