Is Science Really Moving Faster Than Ever?
Entry 2: What Chairman Mao and a malaria drug can teach us about the societal benefits of science.
Photograph by Chip Somodevilla/Getty Images.
I’ve certainly never been accused before of wanting to “quantify outcomes stemming from scientific research before”—slanderous! But yes, I do think we could do a much better job organizing science and the scientific enterprise to contribute to solving problems and addressing a range of social needs.
But let me start by summarizing what I take to be your argument. First, quantifying things like “the pace of technological change” and “the rate of scientific advance” is pretty much fruitless, and claims that we’re in a unique historical era where science and technology are moving faster than ever before, and (most importantly) society is changing faster than ever before, don’t really stand up to close scrutiny. So I basically agree with this. On the one hand, it seems obviously and trivially true that we’re generating more scientific information and technological artifacts than ever before, and at a faster rate, just because a lot more people are in that game than ever before. But whether that really amounts to faster scientific and technological advance in terms of knowledge or technologies that matter for society is a lot harder to get your head around. Railroads and the telegraph totally transformed societies, cultures, economies, and politics within a couple of decades, more or less the timeframe of, say “the information technology revolution,” whatever that is. Same for automobiles, power looms and water wheels, assembly lines, etc.
But then you go on to say that because we don’t have very good aggregate quantifiers of scientific and technological advance, at least as they pertain to things that matter, like solving societal problems, the best we can do for science is to support camaraderie and the pursuit of scientific curiosity. This, of course, is a familiar and powerful argument that’s been used effectively for a half-century or more to shield the scientific community from accountability: Scientists get to promise to make the world a better place as long as they are robustly funded and as long as no one interferes with them. Since the advance of science is said to be unpredictable and serendipitous, anything that’s done to try to steer science in any particular direction is only going to be bad for science, and thus for science’s contributions to society.
The formulation fails on almost every level (except its success as a political tactic). First of all, governments and firms have been successfully steering science toward desired goals for the past 150 years (pretty much for as long as science has been at all relevant to technological advance). Of course some rather small percentage of science is devoted to letting scientists do their own thing, unencumbered by any expectation of useful outcomes, but this has never been a significant part of the public or private investment in research. Not only that, but the idea that scientists pursuing their own curiosity is the best way either to advance fundamental science, or to produce knowledge that will end up being useful, is pretty tough to support, too. Of course there are a standard set of anecdotes about the canonical heroes of pure science, Newton, Faraday, Einstein, and the like, and there will always be (we may hope) the very few true, untethered geniuses who can see things anew, but mostly, to use your analogy, K, scientists are just soldiers in the army, with relatively little freedom to do much beyond put the next brick in the wall that their predecessors, colleagues, funders, and institutions are laboring to construct. Daniel Engber’s Slate piece on mouse models in academic biomedical research compellingly documents this uncomfortable reality, and prompts the question: What if it’s the wrong wall?
The point is not that scientific camaraderie and curiosity are unimportant; it’s that they are exercised in an institutional context, as part of a complex innovation ecosystem, and it’s the dynamics of that ecosystem that are really what matter. We don’t need to quantify the outcomes of science to understand why the Department of Defense was such an incredibly effective incubator of powerful new technological systems during the Cold War. Nor do we need to quantify the outcomes of science to understand why the National Institutes of Health is in many ways failing to deliver on its promise to improve the nation’s health—a fact that NIH Director Francis Collins has explicitly acknowledged in implementing a new “translational” science institute that’s supposed to better connect fundamental science advances to progress in the clinical setting. But from these two examples we cannot conclude anything about the levels of camaraderie and curiosity being pursued at DOD vs. NIH; nor do we need to.
Yes, scientists are, for the most part, like soldiers, “motivated more by the internal logic of the task at hand,” but to suggest that that means we shouldn’t attend to the logic and structure of the larger science and innovation enterprise is like suggesting that we shouldn’t worry about strategy and tactics in military action. Yes, a lot of metrics, like citations and patent counts, do indeed often conceal more than they reveal, and to the extent they reveal that we are going faster than ever, that velocity might be best compared to a hamster wheel. But that doesn’t mean we can’t do a better job designing the institutions and programs that link knowledge advance to societal needs.
In the end, K., it seems to me that your logic can only lead back to the venerated idea that the only variable that matters in thinking about science and technology is how much money we are spending on it. This has basically been the position of the mainstream science community and the organizations that represent it, since the beginning of the Cold War.
There was a wonderful article in the New York Times in January about the malaria drug artemisinin. Derived from a naturally occurring herb whose malaria-fighting qualities had been known for centuries, the compound was identified and studied by Chinese scientists in the 1960s, during the darkness of the Cultural Revolution. This work was carried on the orders of Chairman Mao, had been asked by North Vietnamese leaders to provide medical assistance for their malaria-beset army. Malaria therapies derived from artemisinin have proven to be much more effective than those that U.S. scientists were able to come up with; even so, it was not until the early 2000s that artemisinin began to be used widely in the West.
The point of this abbreviated story, which violates pretty much every myth that we like to tell ourselves about where the benefits of science come from, is that there are many ways to pursue scientific knowledge that can advance social goals, and that what matters is not whether scientists can pursue camaraderie and curiosity, but whether they can do so in settings that are likely to lead to knowledge that is both useful and used. In columns that I’ve written for Nature, I’ve presented a number of examples that help illustrate the crucial importance of institutional setting for linking research to beneficial use in society—in problems as diverse as toxic chemical reduction, AIDS drug development, protection against earthquakes, clean energy innovation, and disposal of nuclear waste. None of these stories are arguments for more quantitative analysis; all of them are arguments for understanding the complex context of science in its social settings, as a basis for making better decisions about how and what science ought to be done.
Daniel Sarewitz co-directs the Consortium for Science, Policy, and Outcomes at Arizona State University. He also writes a monthly column on science and technology policy for Nature. He is based in Washington, D.C.