“Another problem with building knowledge bases is that they can work only in highly interpretable settings. This property is embedded into the inherent nature of knowledge bases, as humans construct them with their semantic insights. While an interpretable knowledge base might seem to be a virtue at first glance, it is also a problem because many intelligent decisions made by humans cannot be easily enunciated in words. For example, a chess grandmaster or an expert player of the game of Go might sometimes be unable to concretely explain why they choose a particular move, beyond the fact that their experience from previous games translates into an intuitive but hard-to-enunciate understanding of favorable spatial patterns. Trying to handcraft this type of intuitive knowledge into a semantically interpretable board evaluation function is often a source of inaccuracy, as it misses the intangibles in the decision-making process.”