Abstract
The definition of knowledge has always been a contentious issue in knowledge management. Effective knowledge management requires a definition of knowledge that is consistent, useful and true. Whilst most definitions today fulfil the first two criteria, none accurately address all three, including the true, biological nature of knowledge. This is where autopoiesis can help. Autopoiesis was developed to try answer the question of what makes something living, using a scientific methodology. It proposes living things are discrete, self-producing entities and constantly cognising entities. Autopoiesis has long inspired definitions of knowledge, with ideas such as: knowledge cannot be transferred, or knowledge can only be created by the potential ‘knower’. Using the theory of autopoiesis, it is possible to create a biologically grounded model of knowledge, representing the latest thinking in neuroscience. However, before this new, biologically grounded model of knowledge can be integrated into new or existing knowledge management theories, it needs to be tested, else it falls into the trap of being conceptual, and remaining that way. This paper uses the theory of autopoiesis to redefine the concepts of data, information and, most importantly, knowledge, and goes on to develop a model of knowledge that has the potential to be used as a new foundation for knowledge management.
Recommended Citation
Parboteeah, Paul; Jackson, Thomas W.; and Ragsdell, Gillian, "Using Autopoiesis to Redefine Data, Information and Knowledge" (2009). ACIS 2009 Proceedings. 4.
https://aisel.aisnet.org/acis2009/4