The measurement of Artificial Intelligence – An IQ for machines

Once talking about the possibilities of creating ‘thinking machines’, Turing properly said that this task should start by defining of what is understood as ‘machines’ and of what is ‘think’. Regarding the pursuit of modeling intelligence, two large avenues were opened by researchers in almost the same epoch: Symbolic Artificial Intelligence – SAI – and Connectionist Artificial Intelligence – CAI – based respectively on symbols and rules and in artificial neurons. It seems that the time is come to start thinking (and acting) to establish a standard of comparison, that could objectively tell how far we have gone along the road of constructing ever better AI systems. Devising an Intelligence Quotient IQ – for machines or any intelligent system would be, perhaps, an advancement but unfortunately, the history of the development of techniques to measure human IQ, the first source checked to find applications to AI, points to a very fuzzy zone. Admitting that possibility, we present some conjectures. For example, introducing some metric to evaluate the redundancy of the rules of an Expert System, or the efficiency of a given topology in a Neural Net could bring new insights on ranking AI paradigms and indicate which are the most promising ones.