Thinking about efficiencies….

One odd thing about the scientific process itself: unlike industrialization, scientific productivity doesn’t really lend itself to the sort of efficiencies that drive many business texts. Which is not to say that convergent technological advances haven’t been hugely important in driving recent progress in science–particularly in science of the trans-disciplinary variety that we do at Krasnow. Rather that a central part of science success comes directly out of contemplative thinking about information/clues from the very edge of human knowledge. To be perfectly clear, a successful scientist needs to allot significant periods of time for quiet thinking.

For myself, one of my own successes in neuroscience came directly out of the realization from my thesis work that imaging metabolic rates in brains wasn’t going to be very useful for imaging learning and memory because those metabolic rates had very high between- and within-variabilities. I needed instead to image the activation of a molecule that was central to mnemonic function (think close to rate-determining) so that the experimental signal-to-noise could be improved upon. That quiet thinking led me to consider protein kinase C less than a decade after it had been discovered within the context of cancer.

But there are roles for efficiencies in science. The advent of new general purpose simulators for computational neuroscience combined with Moore’s law, make for in silico experiments that take minutes rather than weeks.

Robotics allows genome-wide analysis for a small fraction of the cost of Craig Venter’s initial success with his own DNA more than a decade ago.

There are also roles for efficiencies in the administrative support that we provide to scientists. One important consideration is the ever-increasing burden of regulations that, if not checked, can literally eat away at the time a scientist can devote to creating new knowledge. There is of course an important balance between compliance work done to protect society from scientific mistakes (of many types) and the scientific process itself (work of directed creativity). At this institute, we do our level best as administrators to shield our scientists from as much as possible of the regulational burden, by taking it on ourselves–but there are certain areas where that is not possible (such as certifying that a project has no conflict-of-interest).

A part of the life of the very best scientists is close to dreaming. New seemingly random pieces of data (and knowledge) are fitted up against conventional ideas to create novel “idea combinations” (hypotheses) which then can be tested at the bench. Dreaming has never been a good metaphor for efficiency, but it may well be pretty good for describing what it is to scientifically break open a new paradigm.

Creating a garden for scientific success

Nobel laureate Ahmed Zewail’s editorial in Nature is here. Hat tip Harry Erwin.

Money quote:

How can we ensure that such research is encouraged today? Curiosity-driven research requires that creative scientists work in an environment that encourages interactions between researchers and collaborations across different fields. But such attributes cannot and should not be orchestrated by structured and weighty management, as creative minds and bureaucracies do not work harmoniously together.

What is science?

When I’m reading the popular media (as opposed to talking with other scientists), I’m often struck by the apparent disconnect between the intelligent lay public view of science and the understanding of science held by most practitioners. In particular, there is a real confusion between technology, applied science and basic science. And then secondarily there is, among many members of the public, little understanding of the scientific method itself.

With regards to the first confusion, I would define technology as the material and sometimes non-material artifacts, built by human labor, that facilitate or enable some portion of human behavior. Thus the wheel is certainly technology, but so also is the Google search algorithm. By the same token, the I-Phone is technology, but so too is the Pub Med database of journal articles. But these things, material and non-material, are not science. Even though Pub Med contains scientific data and is used by scientists, Pub Med, from my point of view is technology.

Applied Science, on the other hand, is scientific research that can more or less, lead directly to the invention and deployment of new technologies. Thus, I view much of biomedical research (translational research in fact) as applied science because it can be used to develop new practical therapies to advance the public health. In the same way, agent-based modeling, applied to economics, potentially offers decision makers new computational tools for predicting and avoiding systemic risk.  The key difference here is that while a prototype technological artifact may emerge from the practice of applied science, a mature technology generally does not.

Basic science, in contrast, is scientific research aimed at understanding the rule-set of the universe–usually by the hypothesis-based practice we call the scientific method.

It is this scientific method, that I think deserves a much better public explanation–it may well help to depoliticize public policy decisions that are based on scientific research, especially basic research. Most discussions of the scientific method, inevitably refer to Karl Popper. Popper’s key point was the the centrality of falsifying a hypothesis. That is, the aim and design of scientific experiments is to produce data which can serve as a test for an underlying hypothesis being true.

Thus, science is constrained by questions that are in fact testable. The ones that aren’t testable (and they are surely out there) aren’t science. In my opinion, it is this notion that’s terribly important for decision makers to understand: a policy issue, sub served by an implicit theory that can’t be tested, is a bad match for scientific research, applied or otherwise.

One last thought: there is a lot of good science out there that is non-hypothesis based. It’s exploratory science–the Human Genome Project was an excellent example of this. Exploratory science aims at adding to our knowledge of the universe, not by gleaning its rule-set, but rather by collecting and curating its facts. And with the technology of modern databases, collecting and curating may offer great practical utility.

Collegiality in science

One of the most important things in science is to maintain collegiality in the face of a certain tendency among some to view their research as proprietary. This notion of one’s science as one’s “intellectual property” goes against my own grain–it’s at variance with the way my parents practiced neuroscience in their own laboratory at Caltech while I was growing up. So perhaps it’s just my own lack of familiarity with a modern fact-of-life. Perhaps. But it strikes me as very problematic to collaborate and especially exchange ideas with others when one’s body language is a metaphor for a non-disclosure agreement.

Reaching out across disciplines is especially important at an institute for advanced study like Krasnow is. Such exchanges are the crucial catalyst for scientific discovery. And the fuel for such exchanges is collegiality. Without it, one may be successful perhaps to a degree, but one loses the wonderful scientific give-and-take from colleagues who may shy away.

My two cents…


The Institute Advisory Board

Tomorrow the Institute’s Advisory Board will gather for its regular Spring meeting. These individuals play a crucial role in providing me with strategic advice. Even more importantly the board members have, through their gifts, made much of the scientific discovery at Krasnow possible.

And scientific discovery is ultimately the purpose of the Krasnow Institute for Advanced Study. The other day I was tasked with creating a new Institute mission statement for the upcoming re- accreditation process whereby George Mason is reaffirmed as a university. That’s worth thinking very carefully about–because behind the words, there has to be something measurable. To my mind, this measurable thing has to be scientific discovery. That is the creation of new knowledge about the natural world within the context of “mind” research.
Tomorrow I’ll ask the Advisory Board to join me in the work of creating this new mission statement: one that places discovery at the central point of our work.