This paper will look at the various predictions that have been made about AI and propose decomposition schemas for analysing them. It will propose a variety of theoretical tools for analysing, judging and improving these predictions. Focusing specifically on timeline predictions (dates given by which we should expect the creation of AI), it will show that there are strong theoretical grounds to expect predictions to be quite poor in this area. Using a database of 95 AI timeline predictions, it will show that these expectations are born out in practice: expert predictions contradict each other considerably, and are indistinguishable from non-expert predictions and past failed predictions. Predictions that AI lie 15 to 25 years in the future are the most common, from experts and non-experts alike.
Armstrong, S. , Sotala, K. (2015)., How we're predicting AI – or failing to, in J. Romportl, E. Zackova & J. Kelemen (eds.), Beyond artificial intelligence, Dordrecht, Springer, pp. 11-29.
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