A new paradigm of knowledge management: Crowdsourcing as emergent research and development
Drawing from knowledge management theory, this paper argues that the knowledge aggregation problem poses a fundamental constraint to knowledge creation and innovation, and offers a potential solution to this problem. Specific consequences of innovation failure include the failure of research and development to deliver new medicines to address threats such as widespread and increasing antibiotic resistance, the rise of airborne multidrug-resistant or totally drug-resistant tuberculosis, as well as a lack of new drugs to deal with emerging threats such as Ebola. Persistent constraints to knowledge creation exist in the form of market failure, or the failure of profit-seeking models of innovation to internalise the positive externalities associated with innovations, as well as academic failure, or the failure of academic research to provide much needed innovations to address societal problems. However, a lack of theory exists as to how to transcend these constraints to knowledge aggregation. This paper presents a probabilistic theoretical framework of innovation, suggesting that the ‘wisdom of the crowd’, or emergent properties of problem-solving, may emerge as a function of scale when crowdsourcing principles are applied to research and development. It is argued in this paper that the consequences of a lack of knowledge of innovation failure are already upon us, and that a radical new approach to knowledge management and innovation is needed.
Keywords: probabilistic innovation, knowledge management, innovation, crowdsourcing, crowdsourced R&D