Raghuveer Parthasarathy’s big idea for fixing science

Raghuveer Parthasarathy writes:

The U.S. National Science Foundation ran an interesting call for proposals recently called the “Idea Machine,” aiming to gather “Big Ideas” to shape the future of research. It was open not just to scientists, but to anyone interested in potentially identifying grand challenges and new directions.

He continues:

(i) There are non-obvious, or unpopular, ideas that are important. I’ll perhaps discuss this in a later post. (What might you come up with?)

(ii) There is a very big idea, perhaps bigger than all the others, that I’d bet isn’t one of the ~1000 other submissions: fixing science itself.

And then he presents his Big Idea: A Sustainable Scientific Enterprise:

The scientific enterprise has never been larger, or more precarious. Can we reshape publicly funded science, matching trainees to viable careers, fostering reproducibility, and encouraging risk?

Science has transformed civilization. This statement is so obviously true that it can come as a shock to learn of the gloomy view that many scientists have of the institutions, framework, and organizational structure of contemporary scientific research. Issues of reproducibility plague many fields, fueled in part by structural incentives for eye-catching but fragile results. . . . over 2 million scientific papers are published each year . . . representing both a steady increase in our understanding of the universe and a barrage of noise driven by pressures to generate output. All of these issues together limit the ability of scientists and of science to tackle important questions that humanity faces. A grand challenge for science, therefore, is to restructure the scientific enterprise to make it more sustainable, productive, and capable of driving innovation. . . .

Methods of scholarly communication that indicate progress in small communities can easily become simple tick-boxes of activity in large, impersonal systems. Continual training of students as new researchers, who then train more students, is very effective for exponentially expanding a small community, as was the goal in the U.S. after World War II, but is clearly incompatible with a sustainable, stable population. The present configuration is so well-suited to expansion, and so ill-suited to stability . . .

It is hard to understate the impact of science on society: every mobile phone, DNA test, detection of a distant planet, material phase transition, airborne jetliner, radio-tracked wolf, and in-vitro fertilized baby is a testament to the stunning ability of our species to explore, understand, and engineer the natural world. There are many challenges that remain unsolved . . .

In some fields, a lot of what’s published is wrong. More commonly, much of what’s published is correct but minor and unimportant. . . . Of course, most people don’t want to do boring work; the issue is one of structures and incentives. [The paradox is that funding agencies always want proposals to aim high, and journals always want exciting papers, but they typically want a particular sort of ambition, a particular sort of exciting result—the new phenomenon, the cure for cancer, etc., which paradoxically is often associated with boring, mechanistic, simplistic models of the world. — ed.] . . .

Ultimately, the real test of scientific reforms is the progress we make on “big questions.” We will hopefully look back on the post-reform era as the one in which challenges related to health, energy and the environment, materials, and more were tackled with unprecedented success. . . . science thrives by self-criticism and skepticism, which should be applied to the institutions of science as well as its subject matter if we are to maximize our chances of successfully tackling the many complex challenges our society, and our planet, face.

“Radio-tracked wolf” . . . I like that!

In all seriousness, I like this Big Idea a lot. It’s very appropriate for NSF, and I think it should and does have a good chance of being a winner in this competition. I submitted a Big Idea too—Truly Data-Based Decision Making—and I like it, I think it’s great stuff, indeed it’s highly compatible with Parthasarathy’s. He’s tackling the social and institutional side of the problem, while my proposal is more technical. They go together. Whether or not either of our ideas are selected in this particular competition, I hope NSF takes Parthasarathy’s ideas seriously and moves toward implementing some of them.

You are welcome in comments to discuss non-obvious, or unpopular, ideas that are important. (Please do better than this list; thank you.)

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