Proceedings of the Annual Meeting of the Cognitive Science Society

The last few years have witnessed amazing breakthroughs in machine intelligence, using systems that rely on neural networks as advocated in Parallel Distributed Processing (Rumelhart, McClelland et al, 1986). Yet in this talk, I will argue, in agreement with Lake et al. (2017) and others, that we still have a long way to go before any machine has truly captured human like cognitive and learning abilities. Unlike Lake et al., I will argue that we should seek the reasons for many of the amazing achievements of human intelligence not in built in biases or special purpose start-up software, but in a fuller appreciation of the roles of culture and experience. I will argue for a central role for culturally constructed formal systems as powerful tools that extend human abilities beyond what can be achieved without these resources. I will also argue for a central role of language-based instruction and explanation.