We introduce an innovative technique that quantifies human expertise development in such a way that humans and artificial systems can be directly compared. Using this technique we are able to highlight certain fundamental difficulties associated with the learning of a complex task that humans are still exceptionally better at than their computer counterparts. We demonstrate that expertise goes through significant developmental transitions that have previously been predicted but never explicated. The first signals the onset of a steady increase in global (...) awareness that begins surprisingly late in expertise acquisition. The second transition, reached by only a very few experts in the world, shows a major reorganisation of global contextual knowledge resulting in a relatively minor gain in skill. We are able to show that these empirical findings have consequences for our understanding of the way in which expertise acquisition may be modelled by learning in artificial intelligence systems. This point is emphasised with a novel theoretical result showing explicitly how our findings imply a non-trivial hurdle for learning for suitably complex tasks. (shrink)

A fundamental question facing the cognitive sciences is why it is so difficult for us to look at the world in new ways. Experts, in particular, appear to have extreme difficulty in questioning the foundations for their belief. This I argue is because we can only view our world through mental paradigms. Such paradigms, our mindsets, have evolved so that we can respond automatically to things of importance but, by having mindsets, we are intrinsically prejudiced. I suggest that infantile autism (...) provides valuable insight into what a mind would be like if it were not to have paradigms. Because we are constrained to look at the world through our mindsets, the only way to see more is to acquire more mindsets. But, to actually be original, it is also necessary to subvert conventional wisdom and this would appear to be culturally dependent. Accordingly, understanding creativity necessitates examining the collective perspectives of diverse disciplines, encompassing abnormal minds as well as the historical transformations of different cultures. (shrink)

A fundamental question facing the cognitive sciences is why it is so difficult for us to look at the world in new ways. Experts, in particular, appear to have extreme difficulty in questioning the foundations for their belief. This I argue is because we can only view our world through mental paradigms. Such paradigms, our mindsets, have evolved so that we can respond automatically to things of importance but, by having mindsets, we are intrinsically prejudiced. I suggest that infantile autism (...) provides valuable insight into what a mind would be like if it were not to have paradigms. Because we are constrained to look at the world through our mindsets, the only way to see more is to acquire more mindsets. But, to actually be original, it is also necessary to subvert conventional wisdom and this would appear to be culturally dependent. Accordingly, understanding creativity necessitates examining the collective perspectives of diverse disciplines, encompassing abnormal minds as well as the historical transformations of different cultures. (shrink)

We provide the first demonstration of an artificial neural network encoding the perceptual templates that form an important component of the high level strategic understanding developed by experts. Experts have a highly refined sense of knowing where to look, what information is important and what information to ignore. The conclusions these experts reach are of a higher quality and typically made in a shorter amount of time than those of non-experts. Understanding the manifestation of such abilities in terms of both (...) the psychology of expert performance and the underlying neural mechanisms constitutes one of the most challenging problems in the cognitive sciences. Using perceptual templates we show how the amount of contextual information can change significantly even within a given task, the relationship between local and non-local contexts and finally why there is very little correlation between measures of intelligence and level of expertise in many of the most complex tasks performed by humans. (shrink)