The Tyranny of Tacit Knowledge: What Artificial Intelligence Tells us About Knowledge Representation

Polanyi's tacit knowledge captures the idea "we can know more than we can tell." Many researchers in the knowledge management community have used the idea of tacit knowledge to draw a distinction between that which cannot be formally represented (tacit knowledge) and knowledge which can be so represented (explicit knowledge). I argue that the deference that knowledge management researchers give to tacit knowledge hinders potentially fruitful work for two important reasons. First, the inability to explicate knowledge does not imply that the knowledge cannot be formally represented. Second, assuming the inability to formalize tacit knowledge as it exists in the minds of people does not exclude the possibility that computer systems might perform the same tasks using alternative representations. By reviewing work from artificial intelligence, I will argue that a richer model of cognition and knowledge representation is needed to study and build knowledge management systems.