This grant supports the expansion of a popular seminar on computational social science, run by Matthew Salganik of Princeton University and Christopher Bail of Duke University. The instructional program, which takes place over the summer, involves lectures, group problem sets, and participant-led research projects. The seminar also includes outside speakers who conduct computational social science research in academia, industry, and government. Topics covered include text as data, website scraping, digital field experiments, nonprobability sampling, mass collaboration, and ethics. Interest in the program has been robust, with more than 10 times as many applicants as available slots each year. Sloan funds will allow lectures and course content to be broadcast via interactive video to six new satellite locations, including City University of New York; Northwestern; University of Colorado, Boulder; Seattle; Helsinki; and Cape Town. Additional satellite sites may be added in future years.

Harvard econometrician Jose Zubizarreta is developing new statistical methods for the extraction of causal inferences from large datasets. His methods flexibly adjust for covariates in observational studies while also yielding more stable causal estimates. For part of the research, Zubizarreta will investigate formal and theoretical properties of these methods. His team, however, based as it is at a medical school, will also work on specific applications. These require, for example, developing a new framework for the design and analysis of observational studies with discontinuities, or developing new methods that improve the degree of control (covariate balance) and statistical efficiency of randomized experiments that enhance their generalizability. Zubizarreta plans to produce five peer-reviewed papers on these topics. In addition, all software, code, and examples will be produced in an open source programming language and made freely available, together with documentation and sample data, to the academic community and the public.

This grant funds an initiative by the National Academy of Sciences (NAS) to join with peer institutions from around the world to launch international dialogue about policies governing artificial intelligence (AI) and automation. Partners include the National Academy of Engineering, the Canadian National Research Council, the Royal Society, the Royal Academy of Engineering, the Chinese Academy of Sciences, and the Chinese Academy of Engineering. Participants will include government officials, industry leaders, and academic researchers from many different countries in addition to the United States, U.K., China, and Canada. Topics to be addressed include national security, data use and privacy, and legal and intellectual property conundrums related to AI. Grant funds will partially support a workshop and associated webcast, a subsequent workshop report, and the creation and dissemination of supplementary resources for participants and the public.

One of the most far-reaching ambitions of the Deep Carbon Observatory is an omnibus modeling effort to integrate knowledge about the movements and transformations of carbon, an effort spanning the core, mantle, and crust over the four and a half billion years since Earth’s formation. The prospect is daunting, ranging from molecular processes to lava flows, to continent formation, from diamonds, to microbes, to billions of tons of sinking sediments, from temperatures conducive for life to those that melt iron, from pressures allowing delicate films to form to those that crush carbon into diamonds, and from momentary events to those so slow that in comparison the adjective “glacial” describes the blink of an eye. In addition, the temptation to model the evolution of the planet, including the emergence of life and the biosphere, proved irresistible.  Funds from this grant provide continued support to the Deep Carbon Observatory Modeling Forum in its efforts to provide an intellectual framework for the DCO’s modelers and to create key component models to speed and integrate their work. Over the next 21 months, the project team will continue its work developing open access platforms and tools for the modeling and visualization of deep carbon. Funded activities include software development, participation in the wider DCO’s synthesis activities, the holding of a workshop on modeling and visualization, and a series of “immersion” workshops designed to introduce DCO researchers to immersive model visualization.