The science of artificial intelligence and its critics

Not many people seem to understand what it is to mimic human intelligence successfully irrespective - that is, irrespective of internal states such as intentions. Successful mimicking will involve embedding in human societies. AI practitioners have concerned themselves with reproducing something that can mimic an individual human brain, failing to notice that if such a brain is to mimic human intelligence it will also have to mimic the process of becoming socialised in human society because crucial features of human intelligence are located in human societies. One notable example of this is natural language, which is continually changing and enormously flexible in ways that cannot be predicted or controlled by individuals. The fluent natural language speaker draws on society's language in the same way that a thermometer draws on the liquid in which it is embedded. The temperature that registers on the thermometer is a property of the liquid, not the thermometer, changing when the liquid warms or cools. In the same way the language spoken by a fluent individual is a property of the society in which he or she is embedded, not a property of the individual; like the thermometer, it changes when the society changes. This means that a Turing Test, based purely on linguistic performance, can be an excellent test of human-like intelligence in a machine. The nature of natural language explains some of the recent stunning successes of deep learning and explains its failures. I also try to explain why the science of AI is so poor at presenting and testing its claims. It aims at convincing the outside world of its success rather than engaging in the kind of assiduous self-criticism engaged in by the physical sciences.