This grant funds a project by computer scientist Jeannette Wing, Director of the Columbia University Data Science Institute and Professor of Computer Science, to adapt "formal methods” (the representation of computer science systems as mathematical objects) to AI systems.  Once the AI system, the input data, and the desired trust property are formally specified, the AI system can then be analyzed using mathematics, allowing a skilled analyst to rigorously prove or disprove statements about the system being represented. The technique holds obvious appeal for those concerned about the trustworthiness of AI systems, since a formal methods analysis has the potential to reveal how an AI system would or would not behave in novel situations.  Grant funds will support Wing’s attempts to extend formal methods theory to AI systems, including how to formally specify properties of AI systems like fairness, privacy, and robustness.  A particular focus of Wing’s work will be to better formally understand the relationships among such properties, in order to identify and generalize their commonalities and differences.  Wing will also work on trying to use formal methods to characterize, with respect to these trust properties, the relationship between AI systems and the datasets used for training and testing them.

Open and inexpensive hardware has the potential to revolutionize the creation and deployment of sensors and other scientific instruments, expanding access and lowering barriers to innovation in data-driven research methods.  Much of the activity within the open hardware movement has been on expanding the distributed production of hardware, through tools like the open licensing of hardware design and the creation of open 3-D      printing templates for instrument parts.  There has been comparatively less emphasis, however, on how to measure and ensure quality control in a distributed production process.  The widespread availability of inexpensive sensors will only revolutionize science, after all, if the sensors actually work.  This project by University of Washington researcher Nadya Peek will  improve our understanding of quality control in distributed manufacturing processes.  Over the course of the grant, Peek will engage in four streams of activity aimed at filling gaps in current open hardware calibration practices. First, she will develop a generalizable format for documenting the theoretical capabilities of a production machine like a consumer-grade 3D printer.  Second, once this format is created, Peek will use it to develop calibration software capable of verifying that a specific instance of that machine is performing to expectations and within acceptable error parameters.  Third, Peek will develop new software to monitor such machines in real time, ensuring that they are maintaining precision and calibration through the production process.  Fourth, she will develop low-barrier procedures for testing the precision and quality of the final output. In addition, Peek will also field a survey questioning how researchers in the open hardware community are adapting their distributed production processes in response to the shutdowns caused by the COVID-19 pandemic.  

The Internet Age is quickly giving way to the Age of the Algorithm.  Decision-makers of all kinds are increasingly turning to complex algorithmic methods to help them allocate resources, set policies, and assign risk.  Banks use algorithms to figure out how likely someone is to default on a loan. Online retailers use algorithms to decide which ads to display on your phone.  Pollsters use algorithms to determine who is and who is not likely to vote. Increasing reliance on algorithmic verdicts comes with risks of its own, however.  The worry is not so much that the algorithms might get things wrong—human judgement, after all, is hardly error free--but they might get things systematically wrong, disfavoring one group of people over another for arbitrary or irrelevant reasons.  The worry is that we might build algorithms, in other words, that are unfair. This grant funds efforts by a team led by Harvard computer scientist Cynthia Dwork that aim to address this issue. Dwork’s plans involve constructing new theoretical frameworks—based on rigorous mathematical notions called pseduorandomenss, latitude, and multicalibration--that can be used to define and evaluate whether an algorithm is fair or not.  Grant funds will allow Dwork to fully develop her theory, build some algorithms that meet that those characteristics described, and test them to see if they indeed perform as theory predicts.  If successful, the effort would constitute a significant stride forward in our understanding of an increasingly essential cog in the machinery of modern life. 

Virtual assistants like Amazon’s Alexa are quickly becoming the gateway to all other digital products and services. The convenience and power of these assistants has led more than 50 million American households to adopt a virtual assistant over the past two years, an astonishing pace. Yet the marketplace for virtual assistants is dominated by just two firms, with Amazon and Google controlling 95% of the market. Because virtual assistants usefully connect to other digitally enabled devices and services, and because they need to constantly listen for voice prompts from their owners, they are poised to collect unprecedented amounts of personal information about consumers, from listening in on all the Internet of Things devices in our houses, to our communications on social media, from email to Facebook, and from our search history and purchasing records to our finances and health. In addition, unlike browser-enabled searches that return a full page of search results, queries of a virtual assistant yield only one answer, giving them a unique ability to shape (and manipulate) what we encounter and what we know via the World Wide Web. Since virtual assistants are powerful intermediaries between consumers and the wider world, it would benefit all consumers if the market for these assistants was robust, giving consumers many options to choose from.       This grant funds a project by Monica Lam, professor of computer science and director of the Open Virtual Assistant Lab at Stanford University, to build and pilot the first prototype of an open source, privacy preserving virtual assistant. The project, if successful, promises to expand the options available to consumers and offer the ease and convenience of a first-class virtual assistant without the sacrifice of personal privacy or transparency.

Funds from this grant support the production and dissemination of a special series by Annual Reviews’s online publication Knowable Magazine that aims to provide fresh, science-based, and publicly accessible perspectives issues related to the COVID-19 pandemic. Called Reset: The Science of Crisis and Recovery, the 9-month series will feature articles, essays, profiles, interviews, infographics, video, and comics exploring the scholarly work that informs the best response to the coronavirus pandemic. Content will include reporting and expert commentary in the digital publication Knowable Magazine and republished content in diverse media outlets. In addition, the team at Knowable will launch a series of online events featuring renowned scholars from an array of fields discussing timely topics around COVID-19 and providing reliable, evidence-based information and guidance. Content will be informed by Annual Review’s roster of 51 journals and 1,000 scholars, scientists, and journalists. Additional grant funds will support efforts to reach new audiences, including potential content distribution partnerships with Yahoo! News, local radio stations, the Smithsonian, the Aspen Institute, and the Huffington Post, among others.

The National Action Council on Minorities in Engineering (NACME) administers the Foundation’s graduate scholarship programs, including the Minority PhD program (MPHD) and the Sloan Indigenous Graduate Partnership (SIGP).  In this role, NACME maintains records on MPHD and SIGP graduate students and tracks and manages the disbursement of Sloan scholarship and other funding commitments.   NACME also plays an essential role both in the analysis of supported graduate students performance and outcomes, and in managing the community of campus participants in Sloan programs. Funds from this grant will support these activities for years. In addition to continued execution of this role, NACME will pursue three additional objectives over the course of the three-year grant period.  First it will expand its analysis of student records to discover trends impacting the performance of Sloan scholars in the MPHD and SIGP programs.  Second, it will expand and assess efforts to build community among UCEMs with the implementation and management of a new online platform, SloanConnect, and other associated strategies.  Third it will test potential new surveys and program elements to assess their value for implementation.

BetaNYC is a local civic technology nonprofit whose mission is to improve New York City governance through the more effective use of data and software inside municipal government. BetaNYC’s primary strategy is to engage at the most grassroots level of city government through a program that embeds tech-savvy City University of New York (CUNY) students inside local community boards and the offices of NYC borough presidents. These technology fellows help government officials assess internal technology needs and design and execute technology projects aimed at improving constituent services.  Funds from this grant support the continuation of the fellowship program as well as other capacity-building services to community boards and city agencies.  Grant funds are being administered by the Fund for the City of New York, acting as the fiscal agent for BetaNYC.

This grant provides funding to Film Independent (FIND) to organize, publicize and host the next Sloan Film Summit, a major convening of all grantees in the Foundation’s Film program, held every three years pre-COVID. FIND will continue to include public-facing events that go beyond the Sloan attendees. FIND’s own membership has grown by 25% since the last summit and includes over 7,500 filmmakers, who will be among the target audience. The three-day summit, which will feature some 150 attendees, offers a rare opportunity for mingling and interacting among students, faculty, and administrators from the six long-established Sloan film schools; filmmakers and leaders from the five Sloan screenplay development and film festival partners; and the Museum of the Moving Image, Coolidge Corner Theatre, and the Science and Entertainment Exchange. The 2021 Summit will also include representatives from new entrants to the Sloan Film program, including the six new film schools in the Discovery Awards program and the Athena Film Festival and North Fork TV Festival. Planned activities at the festival include an opening night film screening and dinner, updates on Sloan award recipients, case studies of successful filmmaker-scientists collaborations, a networking lunch that connects filmmakers with scientists, staged screenplay readings, a panel where leading scientists discuss underappreciated scientific discoveries, and an industry connection event that will allow 100 filmmakers to meet one-on-one with agents, casting directors, distributors, and other industry executives.

This grant funds an innovative awards program at New York University’s Tisch School of the Arts (NYU) that aims to promote the production of a science- or technology-themed full length feature film by students at the nation’s premier film school. The process begins with NYU film student submissions of one-page pitches of science films they propose to make. A dozen quarter-finalists are selected to move forward, and write step-by-step breakdowns of their films. Six semifinalists are then chosen and given a month to meet with scientists and film faculty to improve the science content, narrative, and design of their films before submitting revised treatments. Three winners are then selected and each is awarded $5,000 to develop their treatments into full-scale feature screenplays. Once screenplays are submitted, one winner is selected, who receives a $100,000 production award to make their first feature film. Grant funds support the continuation of this awards program for the next three years.

This grant funds an awards program by Film Independent (FIND), producer of the Independent Spirit Awards, that aims to help produce and distribute feature films with scientific or technological themes, or those that feature scientists, engineers, technologists, inventors, or mathematicians as major characters.   FIND makes several grants a year to achieve its aims: one producer a year selected to develop a science-themed script in FIND’s Producing Lab, with a $30,000 Producer’s grant and a reception and promotion around this project; one producer or producing team a year awarded a Sloan Fast Track Fellowship, which is a $20,000 cash grant and invitation to the Fast Track film financing market; one outstanding episodic television writer a year supported with a $15,000 grant to develop science-themed series in FIND’s new Episodic Lab; and an average of one exceptional science-themed film every 18 months for a total of two distribution grants of $50,000 each to incentivize buyers to acquire an eligible film for distribution. To date, FIND’s program has been a success. Every project supported has either been completed and released theatrically, is currently in preproduction, or remains at the script development stage. In addition, the program has an admirable record of promoting diverse voices, with women and people of color representing over 60% of their filmmakers.