Last month, the American Academy of Arts and Sciences (AAAS) released the results of a new study, ARISE II: Unleashing America’s Research & Innovation Enterprise. The study examined the current state of US research and innovation; looked at the role of its key players: academia, industry, and government; and proposed a set of recommendations to better address the highly complex challenges we face in the 21st century information economy.
ARISE II notes that all major players in the US research and innovation enterprise are struggling to adapt to new economic realities and societal challenges. Given the intense competitive pressures they face, US companies have reduced their investments in fundamental science and technology research. The payoffs from such investments are now significantly shorter, and financial markets have a low tolerance for the expenses and risks associated with long term research. Thus, even more than in the past, many of the fundamental discoveries driving private sector innovations have to come from long term research conducted in universities and supported by government.But, government is facing its own economic constraints. The US has been going through a prolonged economic downturn, with continuing high levels of unemployment, long term debt and rising healthcare costs. Pressures to decrease government spending make it harder to support long term research.
At the same time, society faces a number of formidable challenges, including the search for clean, low cost energy; adequate food and water to satisfy the requirements of a growing, better-off world population; universally available, affordable healthcare and education; and the rapid urbanization of the planet. Science and technology can be a great help in addressing these problems, but they require a high degree of collaboration involving experts from different disciplines.
ARISE II recommends that the research & innovation enterprise should be reorganized through a comprehensive integration along two axes: across disciplines, - moving from multidisciplinary and interdisciplinary collaboration to transdisciplinary collaboration; and across stakeholders, - promoting more effective ways of working together and new models of interaction among academia, government and business throughout the discovery, development and application process.
The study concluded that neither multidisciplinary innovation, - where experts from multiple disciplines work together toward a common objective, - or interdisciplinary innovation, - where the solution may be found in the spaces between existing disciplines or professions, - go far enough. Rather, a more holistic transdisciplinary approach is required, where the boundaries between disciplines are essentially dismantled.
“In the term transdisciplinary, the committee sees leveraging of existing concepts and approaches from multiple disciplines to derive new concepts and approaches, which in turn enable new ways to achieve and utilize understanding. Hence, transdisciplinary implies an integration-driven emergence of new disciplines, not just ad hoc collaborations.”
This is a pretty far-reaching recommendation. While competitive pressures force companies to adjust to fast changing market realities, change comes slower to academic and government institutions. University research is often conducted in centers involving members from multiple departments. But, academic appointments and promotions are still mostly made by individual departments. Candidates for appointments, promotions, and tenure are generally evaluated by experts in a specific discipline who may not properly take into account the candidate’s contributions to transdiciplinary team-work. Faculty members are often not able to fully engage in such transdiciplinary activities until they have received tenure from their department.
To reach its conclusions, the study examined the two very different research and innovation cultures that prevailed in the physical sciences and in the life sciences over the second half of the 20th century. Throughout this period, research discoveries in the physical sciences were rapidly translated by engineers into innovative products. Science and engineering, as well as basic and applied research were viewed as part of an interwoven continuum, driven to a large extent by the central role played by the federal government.
During World War II, the federal government made substantial investments in research and mission-oriented programs to support the war efforts, including the Manhattan Project, and the development of radar and computers. During the Cold War, government continued investing in major mission-oriented programs like space exploration and the development of atomic energy for military and peaceful application. It also increased its support of basic research in the physical sciences and engineering with the creation of the National Science Foundation.
In addition, a number of large companies set up centrally funded industrial labs which conducted applied as well as open basic research, including ATT, Dupont, GE, IBM and Xerox. From the 1940s through the 1980s, there was a considerable flow of ideas, technologies and people between universities, industry and government labs. This contributed greatly to the postwar growth of the American economy.
But, it all started to change over the past 20 - 25 years. The end of the Cold War had an impact on the funding priorities of government as well as the missions of the national labs. Increased global competition caused companies to re-focus their resources on shorter-term investments. We face a number of grand challenges, but there are few government-driven programs bringing the various players together to work on them. Basic research, applied research, and development are increasingly taking place in separate silos. These changes have affected how research is conducted and funded in the physical sciences and engineering.
In the life sciences and medicine “the situation could hardly have been more different,” said the ARISE II report. “[The] basic and applied life sciences were traditionally pursued as distinct and separate activities: life scientists focused on achieving a fundamental understanding of basic biological processes and until the dawning of biotechnology did not extend those discoveries into practical applications; for example, in medicine. . . Unlike the more integrated concepts in [the physical sciences and engineering], the notion that every fundamental life sciences discovery could advance the practice of medicine was virtually absent. Quite separately, physicians pursued their mandate to care for their patients using procedures established in their clinics.”
Despite their distinct culture and divergent experiences, the ARISE II recommendations apply to the life sciences as well as the physical sciences. They both now face a common set of challenges and opportunities. They each increasingly rely on sophisticated instrumentation, intensive computational resources, and systems approaches. Both “are moving toward a common language: advances in mathematics, information sciences, and computer engineering allow highly diverse kinds of data to be manipulated in digital form, and this capability will help unlock problems across scientific disciplines.”
Not surprisingly given our information-intensive economy, these common capabilities are very much like those we are beginning to associate with data science. The emergence of data science is closely intertwined with the explosive growth of big data over the past several years. Data science is truly transdiciplinary in nature, a mash-up of several different disciplines, incorporating elements, techniques and theories from many fields.
Perhaps the most exciting part of data science is that it can be applied to just about any domain of knowledge, given our newfound ability to gather valuable data on almost any topic. The physical sciences and engineering have long been practicing their own version of data science. But it all now equally applies to the life sciences, medicine and healthcare, as well as to the social sciences and to sociotechnical systems which combine digital technologies with the people and organizations they are transforming.
Data science holds great promise in the pursuit of long-term fundamental science, as well as in near-term applications in medicine, engineering, government and business. Quite possibly, data science can be a catalyst for the reorganization of the research and innovation enterprise proposed by the ARISE II study.
“Revising policy and practice across the U.S. science and technology enterprise is a daunting task,” says the ARISE II report in its conclusion. “Because the system is so interconnected, success will require change in many places simultaneously. . . [and] new levels of cooperation and integration, as well as updating and reinventing policies and practices across academia, industry, and government. The committee hopes that its recommendations will provide a useful roadmap for encouraging and speeding that process of cooperation and integration.”