The best way to understand this type of research is that it’s of high risk with a potential high payoff. It’s the type of blue-sky research that is very unlikely to be pursued in for-profit organizations because it might have no tangible outcome for decades. Since one doesn’t actually know if some research has a high payoff before it’s been done, one should better call it “Potentially Transformative Research.”
Why do we need it?
If you think of science being an incremental slow push on the boundaries of knowledge, then transformative research is a jump across the border in the hope to land on save ground. Most likely, you’ll jump and drown, or be eaten by dragons. But if you’re lucky and, let’s not forget about that, smart, you might discover a whole new field of science and noticeably redefine the boundaries of knowledge.
The difficulty is of course to find out if the potential benefit justifies the risk. So there needs to be an assessment of both, and a weighting of them against each other.
Most of science is not transformative. Science is, by function, conservative. It conserves the accumulated knowledge and defends it. We need some transformative research to overcome this conservatism, otherwise we’ll get stuck. That’s why the NSF and ERC acknowledge the necessity of high-risk, high-payoff research.
But while it is clear that we need some of it, it’s not a priori clear we need more of it than we already have. Not all research should aspire to be transformative. How do we know we’re too conservative?
The only way to reliably know is to take lots of data over a long time and try to understand where the optimal balance lies. Unfortunately, the type of payoff that we’re talking about might take decades to centuries to appear, so that is, at present, not very feasible.
In lack of this the only thing we can do is to find a good argument for how to move towards the optimal balance.
One way you can do this is with measures for scientific success. I think this is the wrong approach. It’s like setting prices in a market economy by calculating them from the product’s properties and future plans. It’s not a good way to aggregate information and there’s no reason to trust whoever comes up with the formula for the success measure knows what they’re doing.
The other way is to enable a natural optimization process, much like the free market prices goods. Just that in science the goal isn’t to price goods but to distribute researchers over research projects. How many people should optimally work on which research so their skills are used efficiently and progress is as fast as possible? Most scientists have the aspiration to make good use of their skills and to contribute to progress, so the only thing we need to do is to let them follow their interests.
Yes, that’s right. I’m saying the best we can do is trust the experts to find out themselves where their skills are of best use. Of course one needs to provide a useful infrastructure for this to work. Note that this does not mean everybody necessarily works on the topic they’re most interested in, because the more people work on a topic the smaller the chances become that there are significant discoveries for each of them to be made.
The tragedy is of course that this is nowhere like science is organized today. Scientists are not free to choose on which problem to use their skills. Instead, they are subject to all sorts of pressures which prevent the optimal distribution of researchers over projects.
The most obvious pressures are financial and time pressure. Short term contracts put a large incentive on short-term thinking. Another problem is the difficulty for researchers to change topics, which has the effect that there is a large (generational) time-lag in the population of research fields. Both of these problems cause a trend towards conservative rather than transformative research. Worse: They cause a trend towards conservative rather than transformative thinking and, by selection, a too small ratio of transformative rather than conservative researchers. This is why we have reason to believe the fraction of transformative research and researchers is presently smaller than optimal.
How can we support potentially transformative research?
The right way to solve this problem is to reduce external pressure on researchers and to ensure the system can self-optimize efficiently. But this is difficult to realize. If that is not possible, one can still try to promote transformative research by other means in the hope of coming closer to the optimal balance. How can one do this?
The first thing that comes to mind is to write transformative research explicitly into the goals of the funding agencies, encourage researchers to propose such projects, and peers to review them favorably. This most likely will not work very well because it doesn’t change anything about the too conservative communities. If you random sample a peer review group for a project, you’re more likely to get conservative opinions just because they’re more common. As a result, transformative research projects are unlikely to be reviewed favorably. It doesn’t matter if you tell people that transformative research is desirable, because they still have to evaluate if the high risk justifies the potential high payoff. And assessment of tolerable risk is subjective.
So what can be done?
One thing that can be done is to take a very small sample of reviewers, because the smaller the sample the larger the chance of a statistical fluctuation. Unfortunately, this also increases the risk that nonsense will go through because the reviewers just weren’t in the mood to actually read the proposal. The other thing you can do is to pre-select researchers so you have a subsample with a higher ratio of transformative to conservative researchers.
This is essentially what FQXi is doing. And, in their research area, they’re doing remarkably well actually. That is to say, if I look at the projects that they fund, I think most of it won’t lead anywhere. And that’s how it should be. On the downside, it’s all short-term projects. The NSF is also trying to exploit preselection in a different form in their new EAGER and CREATIV funding mechanism that are not at all assessed by peers but exclusively by NSF staff. In this case the NSF staff is the preselected group. However, I am afraid that the group might be too small to be able to accurately assess the scientific risk. Time will tell.
Putting a focus on transformative research is very difficult for institutions with a local presence. That’s because when it comes to hire colleagues who you have to get along with, people naturally tend to select those who fit in, both in type of research and in type of personality. This isn’t necessarily a bad thing as it benefits collaborations, but it can promote homogeneity and lead to “more of the same” research. It takes a constant effort to avoid this trend. It also takes courage and a long-term vision to go for the high-risk, high payoff research(er), and not many institutions can afford this courage. So here is again the financial pressure that hinders leaps of progress just because of lacking institutional funding.
It doesn’t help that during the last weeks I had to read that my colleagues in basic research in Canada, the UK and also the USA are looking forward to severe budget cuts:
“Of paramount concern for basic scientists [in Canada] is the elimination of the Can$25-million (US$24.6-million) RTI, administered by the Natural Sciences and Engineering Research Council of Canada (NSERC), which funds equipment purchases of Can$7,000–150,000. An accompanying Can$36-million Major Resources Support Program, which funds operations at dozens of experimental-research facilities, will also be axed.” [Source: Nature]
“Hanging over the effective decrease in support proposed by the House of Representatives last week is the ‘sequester’, a pre-programmed budget cut that research advocates say would starve US science-funding agencies.” [Source: Nature]
“[The] Engineering and Physical Sciences Research Council (EPSRC) [is] the government body that holds the biggest public purse for physics, mathematics and engineering research in the United Kingdom. Facing a growing cash squeeze and pressure from the government to demonstrate the economic benefits of research, in 2009 the council's chief executive, David Delpy, embarked on a series of controversial reforms… The changes incensed many physical scientists, who protested that the policy to blacklist grant applicants was draconian. They complained that the EPSRC's decision to exert more control over the fields it funds risked sidelining peer review and would favour short-term, applied research over curiosity-driven, blue-skies work in a way that would be detrimental to British science.” [Source:Nature]So now more than ever we should make sure that investments in basic research are used efficiently. And one of the most promising ways to do this is presently to enable more potentially transformative research.