Now we look for a similar situation for Knowledge Markets.
In the cuurent times, the hiring manager is the person to know if you want to get a job. The manager would read your resume and compare it with “bell curve” in their brain about what has worked or not worked in their past. This was a great system for the industrial economy, but it falls far short in the innovation economy.
The world is evolving so fast with new technology, new disciplines, and global cultures that what worked in the past may not work in the future. Innovation favors different combinations of knowledge where the Industrial economy favored similar knowledge. A hiring manager may not accumulate sufficient experience in a lifetime to make a proper assessment in the complexities of a diverse, global, and technical future market.
If we look in society, there are many vetting mechanism in place. Social networks are by far among the most exciting and important new technology that can serve this purpose. Social networks must now evolve to become a local vetting mechanism for knowledge assets.
Just like the reporting agencies in the credit system, Social Networks can serve an extremely valuable function in permitting human knowledge to emulate a financial instrument by acting as the “Recording Agencies” who have verified the asset in terms of quality and quantity. The knolwedge Inventory acts as the independent variables that are used to calculate the probability of market success. The difference is that the credit score measures mostly negative events while the new system will seek only positive events and can be designed to give the participants much greater influence on how they appear to the market.
One thing is missing. The credit score uses the FICO equation; Innovation Economics will use something called the Percentile Search Engine.