Point and counterpoint is an appealing construct when it comes to movie reviews, sports predictions, and even politics. But what does it mean when you have two conflicting conclusions about new directions in scholarship? That seems to be the case in recent discussions of the state of interdisciplinary research.
In her book Interdisciplinary Conversations: Challenging Habits of Thought (Stanford University Press, 2010), Myra H. Strober, professor emerita at Stanford, provides a telling, behind-the-scenes look at the difficulties of cultivating cross-disciplinary collaboration among faculty. She finds little evidence of interdisciplinary work.
But a report this year from the Massachusetts Institute of Technology, “The Third Revolution,” attributes advances in medicine and biology over the past five years—like chips to detect cancer in the bloodstream and early prediction of infectious disease—primarily to an interdisciplinary “convergence” of the life sciences, physical science, and engineering. The report describes convergence as going beyond collaborating across the boundaries of fields to the more significant integration of the paradigms of each discipline into the others. It grew out of a previous 2009 report, “A New Biology for the 21st Century,” carried out by the National Research Council and published by the National Academies Press, which described fruitful collaboration among biologists, engineers, and other scientists.
It is easier to see how convergence of nano-info-bio concepts produced rapid DNA sequencing than it is to see how convergence can occur at, for example, the homo-info-econ nexus (i.e., bringing in the human element) to introduce sustainable-energy practices. In the latter case, the communities of scholars and research methods and time frames are often more disparate than in the former.
Nevertheless, many research universities are launching interdisciplinary efforts to attack the latter kinds of problems on a remarkable scale. For example, at my own Duke University, a new Energy and Environment Initiative focuses the efforts of scholars from no fewer than six schools on integrated research to overcome the barriers to adopting selected energy programs. The Department of Defense Data to Decisions project is fostering convergence of computer science and electrical engineering with behavioral economics and business statistics to enable, for example, decisions on what constitutes a security threat from an aggregate of visual (surveillance) and behavioral data. When analyzed by the tools of any single discipline, such security threats would not be apparent. And research to predict and prevent pandemics is leading to a convergence of signal processing and genomics to provide prognostic information on disease in individuals, which can then be coupled with GIS (geographic-information system) mapping to facilitate real-time global-health decision making.
So how do we reconcile these divergent (or might we say nonconvergent) views of what is happening to interdisciplinarity, and what can we learn from each one about how to proceed both in research and in educating a generation of convergence scholars?
The key difference between the conclusions of Strober, on the one hand, and the MIT scholars and National Academies researchers, on the other, is in what these experts tested their hypotheses against. Strober examined groups of faculty who participated in seminars whose purpose, she explained in a Chronicle article, was “to encourage dialogue across the disciplines.” The MIT panel looked at how crucial problems in human health had been solved, and the National Academy of Engineering has defined 14 Grand Challenges in four areas—health, sustainability, security, and joy of living—in which a series of major problems like making solar energy economical, engineering better medicines, and providing universal access to clean water need to be figured out.
Perhaps what we’ve now learned is that pursuing interdisciplinarity for its own sake is a nonstarter. The essence of successful convergence science is that it is driven by clear societally motivated problems, like the Grand Challenges, that no single discipline can resolve.
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That is not all, however. Successful convergence science cannot limit itself to crossing just science and engineering boundaries: It also requires a broad understanding of economics, human behavior, public policy, and more.
Tom Kalil, deputy director for policy for the White House Office of Science and Technology Policy, has suggested that the ideal scientist for convergence is the classic “T-shaped” individual, with the top of the T representing breadth of knowledge and the stem representing depth of knowledge. Faced with problems as complex as the Grand Challenges, even that may not be enough.
I find myself agreeing more with Richard K. Miller, president of Franklin W. Olin College of Engineering. He has observed the similarity between what is needed to solve grand challenges and what is needed generally for innovation (in this sense, meaning bringing an idea into practice for the benefit of some group). The solution lies at the intersection—think of a Venn diagram—of the feasible, viable, and socially desirable. Feasibility encompasses the core technology of the innovation or solution, while viability pertains to the ability to produce or scale the solution cost effectively, and desirability relates to the collective and individual behavior that determines whether the innovation will be embraced and adopted. No innovation succeeds that does not at once satisfy those three requirements.
The three legs of innovation explain why the grand challenges of convergence science must draw on so much more than just science and engineering. And they suggest a different metaphor for the kind of individual needed to work on them—not a T-shaped but an I-shaped individual. The I-shaped—or Innovation-shaped—scholar, to use a term several others have proposed, is prepared to collaborate with disciplinary scholars across the three legs of innovation.
Understand that convergence does not mean the end of disciplinary scholarship. There will always be a need for the core competencies that interdisciplinary scholarship allows us to combine and bring to bear on a complex question. But how can we best communicate across the academic divide to which Strober refers? The three legs also suggest we need to organize and finance our research efforts around grand-challenge problems, in Grand Challenge Research Centers that are broad enough to encompass scholars from all three legs. I have in mind something like the National Science Foundation’s Engineering Research Centers, a group of interdisciplinary centers located at universities around the county, but something that would go beyond engineering.
That still leaves the question: How can students be prepared to participate successfully in convergence science? The latest crop of college students takes to viral communication and collaboration as easily as breathing. A pervasive “there’s an app for that” mentality makes today’s students ripe for the paradigm-shifting problem solving that society needs. Through online role-playing games, some students have logged thousands of hours working with people they don’t know in different times zones, who have different skill levels, to collaboratively tackle a problem within the game. In essence, they come to college not only ready to take on interdisciplinary problems but also exceedingly skilled in collaboration. The next step is to interest them in socially important questions.
Because they are results oriented, students already assume they can make a difference. Leveraging that for the betterment of society makes great sense, and there are so many ways to do so. In late 2010, for example, the U.S. State Department announced it would put some of the money in its Fulbright Program’s premier fellowships into developing creative responses to serious problems like climate change and pandemics. Another effort complements traditional graduate training with additional legs of the I-shape. Anecdotal evidence from programs like Stanford’s Technology Ventures Program suggests that students are clamoring for Ph.D.-plus efforts that add experience in, for instance, entrepreneurship and business skills. In the fall, Duke and Arizona State University will begin similar programs.
Private donors like Cisco’s John Chambers and the photonics entrepreneur Michael J. Fitzpatrick, who want to encourage mentoring beyond the primary disciplines, have begun to offer Ph.D. fellowships that at Duke, for example, are required to include two or more faculty advisers from different disciplines. More intentional use of the outside members of doctoral committees is another opportunity. Imagine a nursing Ph.D. student who is studying in-home hospice care. How much richer would that research be if informed by a mentor from engineering who could foreshadow what remote technologies would be feasible in the future?
But preparing the I-shaped individual shouldn’t begin in graduate school. Opportunities like the National Academy of Engineering’s Grand Challenge Scholars program—which combines curricular and extracurricular experiences designed to prepare college students to solve the big problems of the next century—and the Grand Challenges K-12 Partners program—which promotes hands-on knowledge of how to approach such problems among elementary- and secondary-school students and teachers—can instill the mind-set and much of the skill set at an early stage.
Both Strober and the advocates of convergence science agree that the problems we face in the 21st century don’t abide by disciplinary boundaries, and that solving them is the key to both social benefit and economic growth. MIT and the National Research Council go further to suggest that convergence represents a paradigm shift, not within a discipline, as Thomas Kuhn described it, but in how the disciplines themselves interact. Let’s get our students and ourselves in shape, I-shape.