The Financing of Catastrophe Risk (National Bureau of Economic Research Project Report)
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As a consequence, private-sector norms of flexibility, efficiency, and profitability take their place alongside traditional scholarly ones of reliability, critical scrutiny, and openness. Far more purposeful collaboration across institutions will be required to secure knowledge. Securing knowledge requires substantial financial investment to create the conditions for scientific innovation and to support new research.
For much of the post—World War II era in the United States, the federal government played a central role in funding basic research, most notably with the creation of the National Science Foundation NSF as the principal nonmilitary research funding agency. More recently, the federal share of total research expenditures has declined, while support from the private sector has grown.
In the s, the government accounted for over 70 percent of basic research funding, but that figure has fallen below 50 percent in recent years. How can we preserve the public benefits associated with federal funding on a terrain where the private sector claims increasing prominence? Changes in funding patterns raise deep questions about how social science research can continue to generate benefits for all portions of society, rather than just profit-generating segments.
- National Bureau of Economic Research Project Report.
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Federal funding provides long-term investments in activities whose outcomes cannot be fully identified in advance. These are not typically incentives for making long-term investments in knowledge, including research that might mitigate unanticipated harms.
Today, by contrast, many foundations have shifted priorities to project goals with short-term impact agendas and increased emphasis on observable indicators of impact. Changes in funding patterns raise deep questions about how social science research can continue to generate benefits for all portions of society.
Indeed, the public good has captured the attention of business and corporate enterprises, as demonstrated by the Business Council and the Council on Competitiveness, and by a broader interest in corporate social responsibility CSR practices.
While the data revolution creates exciting possibilities for social science research, it also raises challenges, particularly for data access. Historically, the federal government has played a leading role in gathering and coordinating access to data. Along with state and municipal governments, the federal government maintains complex and largely uncoordinated systems for gathering data on multiple aspects of the lives of US citizens.
Data arises both from administrative processes and systematic surveys, and the ways in which government collaborates with social scientists have changed in recent years. Government-academic partnerships have historically been anchored in the design of survey and sampling techniques and in sharing census and other data. In particular, the census became a model for government-academic social research cooperation see box 1. Short-term political pressures, cost-reduction demands, calls for greater data granularity, and declining response rates to surveys have put pressure on these collaborative arrangements.
Amid these stresses, data sharing between the government and academia, as well as future collaborations that enable independent research using privately held data, must continue to safeguard several key norms, including privacy protections, baselines for measuring trends, academic freedom, and a commitment to improving the collection of social data for public benefit.
The Financing of Catastrophe Risk
The overall framework for government-academy data sharing requires a conscientious re-examination. Such a platform would make data more accessible to researchers and enhance privacy protections. The oldest and most central part of the US social knowledge system has been the decennial census, mandated in the US Constitution.
Indeed, the American Statistical Association ASA was founded on the eve of the census with the express purpose of improving its technical features in order to prevent the manipulation of the census in the service of race science as had occurred in prior decades. Later, the Census Bureau began turning to university experts, professional associations, and, by the end of the twentieth century, think tanks and private contractors.
These relationships have proven mutually beneficial; the influence of the social sciences increased the likelihood that census and other government survey data would be suitable for testing hypotheses about issues ranging from employment mobility to educational reform. They also support the census by advocating for sufficient funding, analytic rigor, and autonomy of the political process in the lead-up to the census. From credit card transactions to internet search patterns to smart phone usage, commercial companies are producing new forms of social data. This data creates exciting possibilities for social science research, but it also introduces new questions about profit motives, intellectual property rights, and other issues stemming from its commercial nature.
Aligning the fundamental motives of the government and academia has created challenges for navigating data-sharing partnerships, but the growing role of the commercial sector poses even greater complexities. The rewards to all parties are clear: the new forms of data greatly enrich the possibilities for social science.
The challenge involves creating the right knowledge infrastructure to generate social benefits from this new data. Several promising pilot programs demonstrate possibilities for private-sector collaboration with government and academic researchers see box 2. The Task Force endorses the creation of a data commons, hosted by a third-party institution, to link public and private data.
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The proposal, outlined by scholars Robert Groves and Adam Neufeld, would make data available temporarily through an intermediary institution, rather than create a permanent data depository. Such ambitious initiatives face significant obstacles, but they are essential to secure knowledge in ways that distribute both benefits and responsibilities across the institutional infrastructure.
Along these lines, the corporate world has already created a model for inculcating public values in the business models of profit-generating firms: corporate social responsibility CSR initiatives.
Box 2: Pilot Programs in Public-Private Collaboration Several projects are taking important steps toward developing collaborative relationships among commercial actors, scholars, and policymakers. For years, a focus of the Alfred P.
Sloan Foundation has been lowering the transaction costs incurred when researchers wish to study government, company, or other administrative data that was not originally collected for research purposes. As part of this effort, the Sloan Foundation has established a number of sector-specific intermediaries called Administrative Data Research Facilities ADRFs , which are being organized into an open network.
These initiatives could provide models for technology companies—and the private sector more broadly—to make their data available for research on issues that address public problems. The Task Force has focused on two particular areas that would benefit from collaboration and the creation of a new compact to guide social knowledge creation: data integrity and ethics governing research protocols.
Securing knowledge requires not only expanding the accessibility of data but also protecting it from corruption, manipulation, and exploitation for partisan, fraudulent, or repressive ends.
Online data hosting facilitates collaboration among a larger range of social scientists, but greater accessibility comes with risks. The more data that accumulates, the more vulnerable it becomes to outside actors with wide-ranging motives, from individual hackers and criminal networks to businesses and national governments.
Even more worrisome, cyber breaches will increasingly seek not just to steal but to alter data. Owing to recent advances in computer technology, we are entering a world in which technology blurs distinctions between images, voices, and videos created in the moment and those altered after the fact. Already, artificial intelligence has enabled the creation of realistic photographs of nonexistent people. Computer scientists can engineer voices that sound exactly like specific, real individuals.