How do companies can be better informed when choosing research trajectories and partners in R&D? How could we understand knowledge that is kept secret under open document like patents? How balancing this tension between cooperation and competition?

Innovation is a complex system, characterized first and foremost by the interplay of various constituents, such as companies and their customers, public agencies and governments, and academic institutions. Innovative trajectories are often fragmented because propriety rights are owned by different constituents. Digitization and machine learning techniques could provide a great advance in this respect, by increasing the ability to better map prior creations and to better position a particular innovation’s claim to novelty. However,  the interplay between collaboration and competition is a common thread between all innovative processes. Companies tend to avoid exposing themselves to potential imitation leaks even more when algorithms could reveal easily big data information.  This in turn challenges how well we can interpret what knowledge circulates freely within the system and what is left concealed.

This lecture will try to open a debate on these topics and to close with some solutions.