Abstract
When designing artificial intelligent systems, one could do worse, at first glance, than take inspiration from the system whose performance one tries to match: the human brain. The continuing failure to produce such an inspired system is usually blamed on the lack of computational power and/or a lack of understanding of the neuroscience itself. This does not, however, affect the fundamental interest in neuroscience as studying the only known mechanism to date to have produced an intelligent system.
This paper adds another consideration (to the well-established observation that our knowledge of how the brain works is sketchy at best) which needs to be taken into account when taking inspiration from neuroscience: the human brain has evolved specifically to serve the human body under constraints imposed by both the body and biological limitations. This does not necessarily imply that it is futile to consider neuroscience in such endeavours; however, this paper argues that one has to view results of neuroscience from a somewhat different perspective to maximise their utility in the creation of artificial intelligent systems and proposes an explicit separation of neural processes into three categories.
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Thill, S. (2011). Considerations for a Neuroscience-Inspired Approach to the Design of Artificial Intelligent Systems. In: Schmidhuber, J., Thórisson, K.R., Looks, M. (eds) Artificial General Intelligence. AGI 2011. Lecture Notes in Computer Science(), vol 6830. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22887-2_26
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