Solving Ebola, HIV, Antibiotic Resistance And Other Challenges: The New Paradigm Of Probabilistic Innovation

The global innovation pipeline that provides new drugs to counter threats like Ebola or totally drug resistant tuberculosis and bacteria has slowed; fewer drugs are being produced and higher levels of investment are yielding lower outputs. This paper argues that the innovation process that underlies proprietary, or profit-seeking, innovation faces an S-curve effect, which is reflected in diminishing returns to investment. A new S-curve is identified, in the form of second generation innovation (SGI) and second generation research and development (SGR). What SGI and SGR have in common is their use of probabilistic mechanisms of knowledge creation. Probabilistic mechanisms refer to the exposure of problem solving processes to very large numbers of problem solvers. An example of this is crowdsourced R&D and crowdsourced innovation contests. The overarching argument made in this paper is that many of the medical and social problems faced today can be solved by a more extensive use of processes associated with this new paradigm in innovation. Chris William Callaghan