Limits of Causation Models in Technology Transfer

There is an article by Jonah Lehrer in the latest Wired magazine that is worth the read.  It’s called “Trials and Errors” with the subtitle “Dead-end experiments, useless drugs, unnecessary surgery. Why Science is Failing Us.” Lehrer discusses the growing awareness that the reported science in the archival literature is proving way more unreliable than one would be led to expect.

One of the problems stems from our ideas of causation:

The truth is, our stories about causation are shadowed by all sorts of mental shortcuts.  Most of the time, these shortcuts work well enough… However, when it comes to reasoning about complex systems–say, the human body–these shortcuts go from being slickly efficient to outright misleading.

Lehrer discusses the work of John Ioannidis, which I have discussed here, who shows that a lot of papers published in elite scientific journals simply do not hold up. I’ve commented on how the problems in reporting science have a direct bearing on technology transfer. One can’t transfer technology if, in fact, it isn’t actually technology that’s any good. Nor can one expect companies to jump up and invest in something just because it has been published in a nice journal. It isn’t true because it is published in an “elite” journal–that’s for certain.

Lehrer’s article has another implicit challenge for technology transfer, and that’s the problem of causation:

Hume’s skeptical insight was that we don’t see gravity–we see only an object tugged toward the earth.  We look at X and then at Y, and invent a story about what happened in between.  We can measure facts, but a cause is not a fact–it’s a fiction that helps us make sense of facts.

…Causal explanations are oversimplifications.  This is what makes the useful–they help us grasp the world at a glance…

…the brain wasn’t seeking literal truth–it just wanted a plausible story that didn’t contradict observation…

…However, those same shortcuts get us into serious trouble in the modern world when we use our perceptual habits to explain events tha we can’t perceive or easily understand…

That’s a problem we have with how “technology transfer” operates.  “Models” are little more than arrangements of the details we have chosen to focus on. Models do not provide causes, but rather provide narrative substitutes for cause. A patent license must have motivated development. A technology licensing effort resulted in commercial success. These are just oversimplifications designed to be plausible and not contradict reports. Tech transfer models don’t take into account things like luck. We don’t have:  first we document the invention, and then we hope we get lucky. Models also don’t consider things like saying thank-you. Yet one of our most successful licensing programs was motivated in a great way by the lead inventor, who was thoughtful enough to send birthday cards to the lead sales reps at the companies that were handling our stuff. Funny thing, that’s not in any “models” of technology transfer.  Models are heuristics.

The huge problem comes when we mistake models for reality, when we think that the sense of order, of process, reduced to a neat diagram, actually represents knowledge about the world, about the complex systems by which new things come into the world. The worst comes about when universities implement policies to try to force the world to conform to a heuristic, such as a patent licensing strategy. It just doesn’t work this way. Even if a patent license, at times, really does appear to motivate commercial development, you can’t turn around and demand that all patents get licensed to motivate commercial development.  You can’t write policies that require it.  Well, you can write those policies, but it’s pointless.  It’s not how it works.  It’s just fictions to try to make sense of complex stuff that we don’t really understand, that is constantly changing.

The best we can do is press on it anew, and find out whether we are rewarded by doing so. If a policy says, always press on it this way, say, with a patent license, because we have some stories that say this is what happened in 1983, then of course there will be people willing to try to do just this, if they are paid for it, and others willing to expect that they will be successful for their efforts or they should be replaced with others who will be better at it. But it’s all fiction. The fact is, sometimes “it works” and sometimes “it doesn’t.” There’s no point in making things compulsory. There’s no point in trying to reason from our simplifying stories to the next opportunity. There’s certainly no point in demanding the next opportunity follow the previous one, for efficiency, for a love of order, for consistency, or to demonstrate that senior officials really know what’s going on or ought to be made to look like they do. None of that.

When we press on the future to make it, we will use whatever we have available. If we have policy that limits our resources, then that’s what we will use, or we will work outside of policy, screw policy, go rogue. So why not write a policy that beats back on policies that force order on what is not going to be ordered, on the unknown that won’t conform to the past, on innovation, when innovation is exactly that which disrupts the present in new, often unexpected ways?

It’s very possible to do technology transfer work in these circumstances, without policy guidance, without oversight of institutional authorities, without a demand that things proceed in orderly ways. A university may promote technology transfer without taking ownership positions, without demanding money for licenses, without contracts. A technology transfer office may specialize in patent licensing without requiring all inventions to show up on its doorstep. University inventors may choose how they deploy their work without having to commercialize anything, and without having to give everything away that they’ve worked toward in their research. You can’t decide in advance. You can’t expect a committee to decide for you.  And you can’t write a policy that lays out a process for deciding what to do.

At best, you can ask that when something is done, there’s some story left that tries to make sense of what happened–whether it was luck or diligence or good will or a mistake. Not that the story should be followed the next time–but rather that the diversity of such stories might remind us of how complex the system is, and how little any one of us knows about it, or what might come next, even when we press on the future to make it so.



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