Let’s not have science become a political football…

One of the great dangers for American science is that it will become increasingly politicized. The partisanship and economic frailty of our current times only exacerbates this risk. A politicized science is one that finds itself, just like any other faction or special interest group, as not credible because of bias and self-interest. And credibility is the fragile currency of science.

Indeed, science’s greatest historical failures, seem to have arisen out self-inflicted politicization. The Eugenics Movement comes to mind. Historically arising from Darwin’s work on biological evolution and natural selection, Eugenics emerged directly from that science, politicized inappropriately to the question of what characteristics constituted a more perfect individual–truly the stuff of political demagogs.

At a recent lunch table here in Washington, I was struck by the dichotomy between Republicans and Democrats over which climate science was to be believed–intelligent lay public members dutifully deferring to scientific research, but only so long as it conformed to their ideological positions.

I have seen the same odd Blue versus Red scientific wars in the areas of embryonic stem cell research, origin of life and more recently economics and it strikes me as damaging, both to scientists and to society, for which good science is so critically important to its welfare.

So as scientists, let’s strive to keep our science at arm’s length from the political wars. Understanding that unprincipled individuals will always be attempting to deploy the latest “finding” to support their own political positions.

Encouraging collaboration…

At our Institute, a major “price of admission” for new faculty is a willingness to collaborate across disciplinary boundaries–the notion being that the loci for many major advances lie at the boundaries of disperate fields. This in itself is challenging because different disciplines operate with different technical languages, commonly called “jargon”. Finding a lingua franca between different disciplines takes time and energy and the pay off, while potentially large, is always fraught with risk (true scientific research is always risky).

Hence, here at Krasnow, the challenge is to encourage such collaboration across disciplinary boundaries, but the even deeper challenge is to encourage collaborations in general. Why?

A major reason is that our current training in science, especially at the doctoral level, emphasizes a solitary rather than team approach. The PhD thesis is, after all, a singularly individual intellectual product–the doctoral advisor’s name doesn’t go on the title page as an author for a reason. While the acquisition of data used in a dissertation may in some cases involve a team approach (think big data physics), at the data analysis level, for the thesis, the work is generally that of the graduate student.

Another reason for the challenge in getting scientists to collaborate is the inherent difficulties, under current systems of sharing data. Until data sharing curation and provenance norms are universal, the “safe” approach is to keep one’s own experimental data under wraps. While large scale data sharing is a desirable end-point, we still aren’t there yet.

Finally, my own sense is that a key ingredient of scientific success involves the ability to think intensely, without distraction, about a problem–and most individuals find it easiest to do this alone. Even if this isn’t the case, the conventional wisdom is that the “ah ha” moment follows such a period of introspective pondering.

So those are some reasons….how might one still encourage collaborations?

The difficulties of the Eurozone…

The current challenges in the Eurozone have the potential to reach far out into global science, certainly beyond Greece and even beyond the EU. The reason is simple: Europe plays a central role in many “big science” initiatives (the obvious ones of course in particle physics and astronomy). But the EU also supports an enormous amount of very high caliber research in the life sciences through its Framework funding initiatives.

Above and beyond the funding of science, there’s also a critical mass of top notch scientists in Europe and the tendrils of their collaborations reach around the globe.

So we wish our colleagues across the Atlantic the best. All of science has a vested interest in the current Eurozone crisis being resolved positively and promptly.

Paul Allen Smackdown of the Singularity

From Technology Review, hat tip Andrew Sullivan: here. Bottom-line, the “complexity brake” will arrest our acceleration towards Kurzweil’s Singularity.

And the argument has as its basis, the complexity problem as far as a general theory of neuroscience is concerned.

Since I don’t share Kurzweil’s rosy vision of his Singularity, I’m pleased. In addition, this should keep us neuroscientists employed well into the future.

Some thoughts on the debt crisis

First, I think the consequences for US science, were the US to default and possibly even if Congress and the President reach a deal, will be negative. In macro terms, I see Federal R&D on a downward glide slope that may well turn into a dive.

Second, I think the combination of the US debt crisis and the European sovereign debt melt down are potentially devastating to the entire global science enterprise. Asia is not yet at the point where the massive western science infrastructure is not needed to push ahead.

Third, with regards to the US, the solutions being put forward by both sides are so constrained by the size of the entitlement problem, there is no scenario that I can see where we don’t eat our seed corn.

To give loyal readers a sense of what the future might look like, we might look to the example of Soviet science after the collapse of the USSR in 1989. Not good.

High performing scientific organizations: the role of foment

One of the characteristics of excellence for a scientific organization is a steady increase over the years in the typical metrics for success (e.g. publications in high impact journals, sponsored research). Another as important characteristic is that excellent scientific organizations build and retain a culture of intense scientific interaction among and between P.I.’s, their trainees and students that at one level manifests as a collegial environment, but more importantly as a place of intense scientific foment. Scientific foment of the type, I’m describing, is to discovery as yeast is to sourdough bread.
So, how to create and sustain that scientific foment?
By experience, it’s become clear to me that first and foremost, there’s the necessary but not sufficient condition: a light-touch management style. Foment is a bottom-up process, and no amount of strategic planning can force it to happen. Deeply entrenched in the scientific DNA is a tendency to question authority along with a healthy skepticism of pronouncements from on high. Hence, simply telling investigators to go forth and foment hasn’t worked (to my knowledge) and is unlikely to be a successful approach.
Secondly, foment doesn’t arise in an environment that is overly burdened with bureaucratic concerns. Take the environment of a driver’s license exam office and you’ll likely not find the seeds of the next advance in cell biology. So an approach by management to actively decrease what is now arcanely termed “paperwork”, is likely to begin to set the initial conditions for success.
Thirdly, there must be a meritocratic culture. Rewards (of all kinds) ought to be meted out by management both for scientific success, but also for the taking of scientific risk–because the greatest scientific successes, always entail some significant amount of scientific risk. In other words, we are against rewarding the minimal publishable unit ramped-up, rather we reward distinct, identifiable discovery that’s made on the basis of experimental (in vivo, in vitro or in silico) research success.
Fourthly, scientific jargon, should be frowned upon–in general. I have lately become of the opinion that such jargon operates in some ways as the secret rituals of fraternities, to exclude those who haven’t been initiated. There are great opportunities for foment at the fracture zones between disciplines, where the important questions often haven’t been posed, much less tested experimentally. To have foment across the disciplinary fracture zones implies checking one’s jargon “heat” at the door.
Finally, none of this can happen if management lacks scientific credibility. Management, need not conduct the experiments, but management certainly needs to be part of the foment, at every step of the way. For an institute like ours, one with frontiers of exploration in domains ranging from molecular to human social behavior, there then must be a scholarly curiosity about many fields (not just one) from the leadership.

Reverse engineering the brain: not to be taken literally

There’s been some angst among fellow scientists about the use of the above term to describe the current attempts to use experimentation and computational neuroscience together particularly in the context of robotics. The worry is that if we can’t reverse engineer the worm C. elegans or the sea snail, Aplysia–which we can’t at present–then we certainly aren’t in a position to reverse engineer the aspects of higher cognition (e.g. spatial navigation) that are interesting about mammalian brains–especially our own.

I agree with the worriers in that, the prospects of building a robot with fully human-like capabilities is not in the near future. Where I disagree is with the notion of setting a scientific agenda that uses the principles of reverse engineering to build up (incrementally) an understanding of how aspects of higher cognition emerge from neuronal activity. An example of very productive work in this field can be seen in the research coming out of Gerry Edelman’s Neuroscience Institute in La Jolla where computational neuroscience models interact with the real noisy environment. Jeff Krichmar’s work there (he’s now at UC Irvine) is an excellent example of this approach.
And so, when the idea of reverse engineering the brain comes up, from my perspective it is as a metaphor. As far as actual reverse engineering of brains, this will happen in the worm or the fly long before it becomes an actual possibility for vertebrate brains. But the term is a useful metaphor for an approach, whereby experimentally determined characteristics of real brains can be applied to real life engineering problems–like creating better autonomous vehicles.