We are attracted to patterns. A pattern appeals to our sense of order and gives us the impressing that things are following a law, can be predicted, everything in a system. It’s all nice.
Innovation, however, may suggestion a change in a pattern, a repair of a break or defect in a pattern, or an addition or completion of the pattern. Adding to a pattern is a matter for innovation from within. Adding to a pattern is like working towards the official future, where innovation means improvement under orderly control of planning and execution. Fixing a pattern is similar, but involves replacing defective parts with working ones, and may mean accommodating or mitigating the work of others. Thus, it may fall to someone other than a mining company to figure out how to prevent pollutants from reaching groundwater. It’s innovation, but at some potential expense to the mining company.
It’s innovation that breaks the pattern, that does something different–that’s the stuff that scares the bejesus out of the status quo, that the status quo rigs to defend itself from, to hedge its bets on, to prevent from happening.
To play with the idea of partial patterns, here’s a simple one:
3 5 7 11
A simple sequence. Is it defective? Should there be a 9 between the 7 and 11? If so, then it’s a partial pattern of odd numbers, and the next number should be 13.
3 5 7 [9] 11 13
Sure nuff. But the sequence without the 9 also consists of the odd prime numbers. That’s a less obvious sequence, but a perfectly fine one. The 13 doesn’t differentiate between the odd numbers and odd primes sequences. But if the next number is 17 rather than 15, then we might begin to suspect, but even up to 23, we have some competition
3 5 7 [9] 11 13 [15] 17 19 [21] 23 (odds, defective, fixed)
3 5 7 11 13 17 19 23 (odd primes, fine)
3 5 7 9 11 13 15 17 19 21 23 (odd primes, made defective by being “fixed”)
The point is, the second sequence can be interpreted as a defective obvious sequence or a less conventional but perfectly well formed sequence. With a smaller sample.. 3 5 7… one has no idea what sequence it might be–but it still may look obviously like odd numbers, leading one to insist on a 9 rather than wait for, say, an 11.
It gets worse. The sequence above from 3 to 23 could just as easily be random numbers. They just happen to be in a sequence that we recognize as having a pattern. But the next number could be 108 or 76212. It would be odd to find numbers in a sequence just so, because they are recognizable as forming a pattern, but there’s nothing that requires the next number to add to the pattern we first recognized.
Furthermore, the pattern could be all the numbers under 25, starting from 3 and doing the odds in some skippy fashion and then the evens. Again, not as obvious, but once a rule is stated, the nature of the pattern becomes clear and one can run with it.
In this simple sequence we see that there are multiple patterns that one can jump to based on a partial set. In a strange twist of Ockham’s razor, there is a tendency to take the first pattern that presents, the most obvious pattern from the “data” at hand. This is especially the case if we assume that patterns in the big wide world typically present as partial and with defects. We tend toward the pattern we see first. We “snap to grid” and adjust our expectations to the first pattern we presume is there. We enforce that pattern against efforts to change it, to break it. We write policy that makes the pattern more important than the sequence from which we got the idea for the pattern in the first place.
If our interest is in finding a simple pattern, fixing its defects, and completing it, and enforcing the pattern on all later efforts, then we have, essentially, the present situation in US university technology transfer. A partial pattern presents in the activities of using patents on inventions arising in research to attract private investment to create commercial product. Get invention reports, file patents, seek industry partners, make money. This pattern is then extended to make this effort more efficient by requiring assignment of ownership and adopting a model committed to “commercialization”. The pattern is simplified further to “own inventions, make money”. Litigation is as good as licensing. It’s unethical for inventors to do things that would preclude the university making money, and it is an ethical mandate for the university to make money so it can pay inventors a share (and it is an ethical mandate that the inventors take that share). Evidence of past practices that differ from the model is effaced, and training is instituted to teach faculty and others how the patterned “process” “works”. That is, life must imitate bureaucracy.
This is not a particularly great outcome for innovation behaviors. The patterns of university research innovation are ones that potentially break the patterns of the status quo. It’s no good to attempt to create a system that “captures value” by compelling all IP to go through a bureaucracy, and to compel the bureaucracy to manage all IP it gets this way for the purpose of making money from monopoly partners exploiting patent rights. It is possible that such deals get done. There are instances. But not nearly as many as one might think over the past thirty years, from the tens of thousands of inventions and the trillion or so dollars of federal funding to universities, and not so compelling in their operation as the amount of money in those few deals might indicate. Money can be had from shakedown, speculation, desperation, and mistake–all without resulting in innovation, and especially not in innovation arising from research discoveries. Money is a lousy metric for university IP management effectiveness.
Once a partial pattern becomes confused with the truth, however, or with efficiency, or with “best practices”, it’s really difficult to get unsnapped from the grid. The bozonet loves the grid. The bozonet, in a real way, is the grid. Once one is in a bozonet, “peer review” and “comparables” are signals for doing foolish things because they look safer, more practical, more commonplace, than other things.
And folks wonder why university technology transfer is so difficult, the transactions that matter so rare, the interactions so fraught with bitterness, misunderstanding, and ineffectiveness. We need to re-assess the partial patterns that present on the road to innovation and be ready to give up the obvious ones for a greater diversity of possibilities.