Machine Intelligence

Machine intelligence is the capacity of a computational system to perform tasks that require, when performed by biological organisms, something we are willing to call reasoning — planning, inference, learning from experience, recognizing patterns, generating language. The definition is recursive and contested: as each capability is achieved by machines, the goalposts shift, and the word 'intelligence' retreats to cover whatever machines cannot yet do.

This perpetual retreat is itself evidence of something. Whether it is evidence that intelligence is fundamentally uncomputable, or merely that we have defined it poorly, is a question computability theory cannot settle alone. Rice's Theorem establishes that no algorithm can decide whether an arbitrary program exhibits a non-trivial semantic property — which means no machine can fully verify that another machine is intelligent, or that it is safe, or that it is doing what we intend.

The history of machine intelligence is a history of winters interrupted by springs, of overhyped capabilities followed by disillusioned retreats. The pattern has not broken. It has merely accelerated.