This grant provides two years of continued support for the Coolidge Corner Theatre Science on Screen series, a grant program that helps independent theaters across the country pair current, classic, cult, and documentary film screenings with thoughtful introductions by notable figures from the fields of science, technology, and medicine. Grant funds will allow Coolidge to make 56 grants to independent theaters over the next two years, which will bring to over 100 the number of independent cinema houses across the country that participate in the program. Each theater in the Science on Screen series receives a grant of between $4,000 and $8,500 to facilitate three screenings a year with expert STEM speakers, at least one of which is a film developed or awarded a prize through the Sloan FoundationХs Film program. Additional grant funds support a National Week of Science on Screen in which all participating theaters hold coordinated screenings, an expanded two-year grant program for cinemas participating for the first time, and an alumni program that provides support at a reduced level for the programХs most committed cinemas. Other funds support marketing, promotion, and social media outreach designed to expand participation to theaters in all 50 U.S. states, and an ongoing presence at Arthouse Convergence, the largest annual gathering of independent cinema operators in the country.

This grant supports an ongoing initiative by Consumer Reports to empower consumer choices of products and services by conducting research, developing tools, and providing accurate, easy-to-understand reporting on how companies and products collect and use consumer data. Led by Justin Brookman, Director of Consumer Privacy and Technology Policy, Consumer Reports will engage researchers and technologists over the next two years to build tools and construct research methodologies to map the collection, manipulation, and sharing of consumer data across three pivotal industries: the Internet of Things (devices in our homes, such as smart thermostats and other internet-connected appliances); automobiles (geolocation data, sensors); and data brokers (second and third parties who collect and sell information about consumers). Grant funds will support a series of dedicated fellowships for technologists and other digital experts who will help create new tools and research methodologies with the goal of creating state-of-the-art testing capacity that Consumer Reports will use to generate insights into how companies and products in these three spaces collect and use data. These insights will then be made public through Consumer ReportsХ impartial, evidence-driven journalism, which will aim both to improve consumersХ ability to choose products effectively and create incentives for market participants in these industries to improve and make more transparent their data collection and use policies. К

Consumer 101 is an educational TV show, launched in 2018 and produced by Consumer Reports, that Тgives viewers a behind-the-scenes look into the science used to test every kind of product, from cars and smart televisions to payment apps and food.У Broadcast on NBC on Saturday morning and targeting 13- to 16-year-olds, the show aims to help teens turn themselves into smart consumers by showing them how things work, revealing tips to get the most out of everyday items, and providing them a window into unexpected career paths in science and technology. The show has reached an audience of over one million viewers. Funds from this grant support the production and broadcast of 10 segments of Consumer 101 focused on digital privacy and security. Possible topics include smartphone security, targeted ads and search protection, smart speakers, password managers, app permissions, online privacy traps, privacy solutions, and deleting old accounts on services one no longer uses. Additional grant funds will support promotion and outreach efforts for the produced segments on traditional and social media.

This grant funds work by Paul Ziemann, professor of chemistry at the University of Colorado, to investigate the sources and processes that influence the composition of organic chemicals in indoor environments and to improve predictions of the chemistry of indoor air. Ziemann and his team will conduct field studies in several locations on and around the University of Colorado campus. Study sites have been chosen to reflect the diversity of indoor environments: a carpeted meeting room in the Sustainability, Energy, and Environment Community building; the Chapel Theatre in Old Main, which is the oldest building on campus and which contains extensive wooden paneling; and the swimming pool at the universityХs recreation center. State-of-the-art instruments and methods will be used to measure organic chemicals and other reactive species at each site. Measurements will include gas (volatile organic compounds and other trace gases), aerosols, surface composition (functional groups and single compounds), and air exchange. Laboratory studies will be conducted to investigate the fundamental interactions of organic chemicals with surfaces composed of common indoor materials, including bare plastics, bare wood, varnished wood, and carpet polymers. Results of the field and laboratory studies will be used to develop models to describe and quantify indoor chemical emissions, deposition, and reactions; and to determine the effects of chemical and physical variables such as organic gases, oxidants, surfaces, humidity, acids, light and temperature, and human occupancy on the composition of indoor air.

Funds from this grant support an ongoing project led by Marina Vance, assistant professor of mechanical and environmental engineering at the University of Colorado, Boulder, and Delphine Farmer, associate professor of chemistry at Colorado State University, to build community and data infrastructure for researchers working in indoor chemistry. Over the course of the grant period, Vance and Farmer will develop a data sharing infrastructure for indoor chemistry studies, merge and synthesize data collected from the HOMEChem field experiment with additional chemical datasets, further analyze that data, plan and host a scientific meeting for researchers in the Chemistry of Indoor Environment program, and continue outreach and community building among indoor chemistry researchers through the IndoorChem website and social media properties.

Drawing causal inferences about the effect of one variable on another is something people do all the time. Machine learning (ML) and artificial intelligence (AI), in contrast, are only able to perform statistical correlations and pattern discovery. Umbrellas are associated with rain, for example, but carrying an umbrella does not make water droplets fall from the clouds. This is obvious to humans, but neither machine learning nor even classical statistics can even pose, let alone investigate, such basic assertions. One of AIХs most distinguished research groups is embarking on a mission to bring causal considerations like these to their work on ML. Founded almost 15 years ago by Geoff Hinton, the Learning in Machines and Brains program (LMB), organized and partially funded by the Canadian Institute for Advanced Research, has made causal inference a top priority for its next phase. Funds from this grant support efforts by LMB to hold a multidisciplinary conference on causal inference in AI, bringing together top experts in economics, econometrics, statistics, neuroeconomics, and logic, to discuss the challenges and opportunities in developing machine learning protocols and platforms that can detect causal relationships in data. Additional grant funds will support a series of six $50,000 ТcatalystУ grants that will spur innovation by funding targeted research projects on these and related issues.

Funds from this grant support work by a team, led by David Cousins at a company called Duality, to develop mathematical tools and techniques that will enable social scientists and other researchers to link and analyze privacy-sensitive financial data without the risk of exposing protected information in the data. Partnering with the Institute for Research on Innovation and Science (IRIS), which collects administrative records from universities with the expectation that no sensitive information about one institutionХs employees, students, or finances will be revealed to any another, Cousins and the Duality team will work on the development of methods that use a type of advanced cryptography known as fully homomorphic encryption (FHE) to develop analysis tools that are powerful and scalable enough to be used in a wide variety of research contexts, yet satisfy very stringent data privacy standards. All developed software and code will be open source and deposited in freely accessible software libraries.

The Summer Institutes in Computational Social Science (SICSS) are annual summer courses that aim to accelerate the growth and strength of computational social science; to seed interdisciplinary research that builds on this field; to create open source teaching materials that support training in the field; to ensure that the new field develops appropriate norms and standards that are in the long-term interests of science and society; and to create a community of scholarsСsupported by partner organizations such as companies and universitiesСthat will help advance computational social science into the mainstream of economics, data science, sociology, political science, and other social science fields.К Founded by Christopher Bail of Duke and Matt Salganik of Princeton, the courses are held each summer on the Duke and Princeton campuses, while simultaneously being broadcast to 11 different educational institutions around the world. Almost 300 graduate students, postdoctoral fellows, and junior faculty participated in 2019 alone, with applications far exceeding the spots available. Funds from this grant support the continued operation, expansion, and development of the SICSS for a period of three years.

This grant provides three years of continued operational support to the Household Finance Working Group (HFWG) at the National Bureau of Economic Research. The group brings together leading economists, econometricians, regulators, and policymakers working on issues broadly related to understanding how households make economic decisions. Specific topics addressed by the working group include household saving, portfolio behavior, borrowing decisions, investment choices, risk management, and bankruptcy.К Over the next three years, the HFWG will continue its work with a focus on how changes in technology are affecting both household decision-making and the opportunities to study it. Topics to be examined include the rise of fintech, big data, and machine learning in the provision of consumer financial services; the impact of electronic payment systems, such as cryptocurrencies, on traditional financial institutions; and both the challenges as well as the opportunities posed by the use of administrative data for research on consumers and their financial decisions.

The Тexternal validityУ of a scientific finding is its robustness in the face of additional observations or alternative model specifications. Statistically significant findings can often be weakened or reversed if either the same analysis had been done with a different sample or if a different model specification had been applied to the same data. Bayesian statistical techniques are particularly well suited to address such issues, but their uptake has been impeded by their awkward, difficult implementation in the standard statistical programs most commonly used by researchers. К This grant provides funds for the continued development and adoption of Stan, an open source, probabilistic programming language developed by Columbia University statistician Andrew Gelman. Stan elegantly implements advanced Bayesian methods for analyzing external validity and for many other issues and has gained increasing popularity in recent years. Grant funds will allow the continued growth of Stan with a specific focus on developments aimed at making the program more useful and useable by economists and other social scientists. Planned grant activities include the development of new modules specifically addressing the complex and multilevel systems that social scientists study, as well as the production of open-access tutorials, research papers, and reproducible case studies.