…..or reason, or be intelligent, or know what it is doing, and so on. These are challenges that have excercised philosophers and artificial intelligence scientists and many others since Alan Turing first posed the question in his seminal paper for Mind, Computing Machinery and Intelligence. Rumour has it that in the 1980s Prime Minister Thatcher saw a certain Professor Fredkin on TV explain that superintelligent machines would soon surpass the human race in intelligence and that if we were lucky they find human beings interesting enough to keep us around as pets. She decided that the ‘artificial intelligentsia”, whom she was just proposing to give lots of research funds under the Alvey Initiative, were seriously deranged and slashed their budget.
Il-considered pronouncements like the one above are often made about AI by people too easily impressed by computers, but they detract from a serious point that Turing was attempting to consider. Turing was an academic mathematician who during the second world war was engaged by military intelligence to produce mathematical procedures that could decipher German coded messages. 
Working through these procedures was extremely complex and could only be done by rooms full of ‘computers’, which in the days before digital computers were humans, usually women, employed to make routine calculations.
Turing was impressed that although these people were unaware of what they were doing, collectively their achievement, code-breaking, should be judged as intelligent. As he was also working on rudimentary computing devices he was aware that the tasks done by ‘human computers’ could one day be done by machines. In his celebrated Turing Test he subsequently speculated on whether or not intelligence had to come from a human, or indeed whether it needed a source that was singular, human, or conscious at all.
Rather than have a machine pretend to be human, in the Chinese Room mind experiment, John Searle makes the human act like a machine, and thereby attempting to prove Turing wrong – that appearance and essence can be very different. We may want to attribute intelligence based on what seems to be the case, but we have no grounds for doing so. While these may appear esoteric academic disputes they address issues that confront us in our everyday lives of which, it seems, our understanding is extremely shallow.
Carol Beer in “Little Britain” gets a lot of laughs everytime she says “computer says no“, but how often do we, in our everyday lives blindly follow instructions without any understanding of what they mean. Surely these scenarios have their representation in both the mind experiments above.
Perhaps we can take comfort in relying on people who know better than us, but what happens if the experts are doing it too? An interesting point was made by the US economist Frech in a paper titled European versus American Economics, Artificial Intelligence and Scientific Content, who noted that it was the US economists who won all the Nobel prizes. Unlike their European counterparts, the US academics were concerned almost exclusively with symbols and the relationships between them, and they had little or no appreciation of what they meant in the outside world – just like the person in the Chinese Room.
So if Nobel prizewinners are doing, what hope for the rest of us?
