An important under-explored issue within energy systems literature is understanding the challenges that arise when two energy and environment goals conflict with one another. In particular, there is a desire to install more large-scale renewable energy generation resources to decarbonize the electricity sector, yet the siting of these power sources is increasingly occurring on sensitive and vulnerable lands that often serve as critical habitats for endangered species. This grant led by Rebecca Hernandez at the University of California, Davis will explore the challenges that arise when these two energy and environment goals conflict. Grant funds will allow Hernandez to explore this “renewable energy vs. conservation” tradeoff, exploring the West and Southwest regions of the United States to map and model the overlap between current and future conservation needs and renewable energy installation locations. The team will also engage a range of stakeholders to identify community preferences associated with these tradeoffs, with a particular focus on Indigenous nations and tribal communities. Funds will allow Hernandez to produce at least 4 peer-reviewed articles examining the conflict associated with species threatened by climate change and renewable energy development; produce detailed maps of range shift patterns for current and future renewable energy impacts on endangered species; undertake 2 stakeholder workshops; train 1 graduate student and 1 postdoctoral fellow; and produce a publicly accessible Climate-Smart Siting Guide for public distributions.

Recent evidence and trends have been undermining some predictions that robots are about to steal all our jobs. Researchers have evolved from believing that automation must lead to substantial unemployment. Many now argue that automation may actually increase employment. This can happen because Artificial Intellignece (AI) raises firm productivity and also because, in some situations, AI acts as a complement to human expertise. Rather than having nothing to do, it looks like we may instead learn to work alongside our new robotic friends. This grant supports Nikhil Agarwal and Tobias Salz at MIT who are investigating the collaborative nature of interactions between people and AI in knowledge-intensive environments. Their goal is to understand better how human decision-makers combine their own contextual information or intuition with machine generated predictions.   Grant funds will allow Agarwal and Salz to develop theoretical models of human decision-making with and without AI assistance, then test these models by running experiments on how human experts actually make use of AI tools in practice. The team will initially test their models through observing how radiologists interpret patients’ chest X-rays, varying the availability and timing of AI predictions and the presence or absence of contextual data such as the patients’ clinical histories. This will allow the team to explore, to take one example, the weight that radiologists give to AI predictions under different circumstances. The findings of this project, however, will have implications that go far beyond the practice of radiology, including potential further applications concerning the use of AI in financial transactions, corporate operations, and risk assessments.

Regional Transmission Organizations (RTOs) and Independent System Operators (ISOs) have a substantial, critical impact on the function of the energy system. Each RTO and ISO is structured and governed differently, yet there is little research on how each of these entities operate. This grant builds on previous Sloan-funded research and provides ongoing support to an interdisciplinary research network, called the RTOGov network, that has is filling this knowledge gap, bringing together scholars from multiple disciplines and institutions. Now led by Seth Blumsack at Pennsylvania State University and Stephanie Lenhart at Boise State University, RTOGov will study how these entities operate and function, how each compares or contrasts with one another, and how differences in organizational structure and governance impact the service they provide to energy systems and customers. This phase will allow scholars in the network to undertake more comparative regional governance studies across institutions as well as examine broader policy issues associated with federal requirements for RTO governance. Building on practitioner collaborations established during the first phase of the project, RTOGov scholars will focus on sharing lessons learned to contribute to the formation of emerging RTO-like entities that are actively being designed in regions like the Southeast, Mountain West, and Alaska. Grant funds will allow RTOGov to produce at least 12-15 papers for academic journals in multiple fields and associated policy briefs or white papers; engage a diverse range of 25-30 additional contributing scholars; support the training of at least 8-10 students; and continue to provide guidance to practitioners. RTOGov also plans to organize and host 6 semi-annual research workshops that will gather participating researchers, contributors, and advisory committee members.

Researchers have developed a new generation of energy system models representing U.S. electricity generation, transmission, and demand that promises to help decisionmakers understand how different policies will speed or inhibit the decarbonization of the U.S. energy system. Yet these models differ in various respects, and there is a need to gain insight about how these individual energy system models compare to one another. To fully unlock the decision-making usefulness of these powerful next generation energy system models, a nuanced understanding is needed to determine how the evaluations produced by these models vary and what features of the models explain such variance. This grant supports research by a multi-institution team led by Oleg Lugovoy at the Environmental Defense Fund to compare a set of cutting-edge, open-source electricity system planning models across a range of different decarbonization scenarios. Lugovoy’s team will compare four models (known as GenX, Switch, Temoa, and USENSYS) using the PowerGenome platform to conduct their comparisons and analyze the results. The models will be compared across two decarbonization scenarios, a business-as-usual scenario and a high-renewables scenario, all drawing on the same input data. Grant funds will allow the team to produce 4-6 publications, train 2 postdoctoral researchers in energy system modeling intercomparison, produce a GitHub data repository, and disseminate model comparison results to practitioner stakeholders. Finally, the team will convene 2-4 public workshops to train those interested in learning how to use the open-source models and the results of the model intercomparison project.

The Sloan Digital Sky Survey (SDSS) is one of the Sloan Foundation’s longest running basic science programs, with a nearly 25-year period of continuous observation shedding light on some of the most important questions in astronomy and astrophysics. The fifth phase of the Sloan Digital Sky Survey (SDSS-V) consists of an all-sky, multi-epoch spectroscopic survey observing the universe in both the visible and the infrared portion of the spectrum. SDSS-V will observe the entire sky using two complementary telescopes—one at Apache Point Observatory in New Mexico and a second at Las Campanas Observatory in Chile—allowing it to map the night sky more fully, with the Chilean telescope able to observe core parts of the Milky Way not visible in the Northern Hemisphere. Grant funds will allow SDSS-V to conduct its originally planned, full five-year observation program and observe multiple objects, at multiple distances, across three constituent sub-surveys: the Milky Way Mapper, which will study the history of our own galaxy; the Black Hole Mapper, which will observe the behavior of supermassive blackholes that sit at the center of galaxies; and the Local Volume Mapper, which will examine the interstellar medium in key regions of the Milky Way and other galaxies. This grant will allow SDSS-V to complete the upgrade to a new robotic focal plane observation system, complete the construction of the Local Volume Mapper instrumentation hardware, and extend the SDSS-V observation period to 2026-2027.

Determining how to advance deep decarbonization efforts in the United States is a big picture issue that requires research and analysis on many fronts. Early in 2021, the National Academies of Sciences, Engineering, and Medicine (NASEM) released a Sloan-funded consensus study report, titled Accelerating Decarbonization of the U.S. Energy System,which identifies both key technical and socioeconomic goals to help the U.S. achieve net-zero emissions by 2050 and the near-term federal policies that would set the U.S. on a path to meet those goals. This grant will expand the work of the NASEM committee to further explore the implementation of deep decarbonization interventions in the United States energy system. The first component of this next phase of work is producing a second consensus study on aspects of deep decarbonization not covered in the first report, focusing on issues like environmental justice, the impacts on jobs, and the role of sub-national policies. Second, this grant will help to establish an ongoing Deep Decarbonization Forum to address current and future deep decarbonization issues with a wide range of stakeholders.

This grant provides ongoing support for Stefano DellaVigna at the University of California, Berkeley, and Eva Vivalt at the University of Toronto, who are scaling up their Social Science Prediction Platform (SSPP), an online platform for collecting and cataloguing forecasts about the results of social science experiments. Documenting such forecasts is an increasingly used and useful way to help evaluate the importance of social scientific studies. Among other reasons, it creates a baseline from which to measure the novelty or unexpectedness of a social scientific result or finding. It can also serve as a useful measure of scientific consensus around important or contested issues in a field. Grant funds will allow DellaVigna and Vivalt to include more research projects in the platform, to include more than 5,000 new forecasts, and to include new applications for predictions such as measuring the effectiveness of policy interventions. Funds will enable the team to run conferences and workshops; to produce training materials and outreach activities; to recruit a large and diverse sample of forecasters; and to develop new methodologies and platform capabilities.

This grant supports Sanjay Patnaik, director at the Brookings Center on Regulation and Markets (CRM), which promotes independent, unbiased, and non-partisan research on regulatory economics. Grant funds will allow CRM to conduct research on topics including artificial intelligence and emerging technologies, financial market regulation and fintech, and consumer protection and antitrust in the digital age. Through its research, CRM seeks to explore how novel technologies can best be regulated without stifling innovation; how the regulatory process could be adapted to quickly respond to changing market conditions; and how regulation can deal with new approaches to data privacy. In addition to producing high-quality and policy-relevant research on regulatory economics, CRM will disseminate this work through academic papers, policy briefs, and events that connect researchers with practitioners.