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    Study finds health risks in switching ships from diesel to ammonia fuel

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    As container ships the size of city blocks cross the oceans to deliver cargo, their huge diesel engines emit large quantities of air pollutants that drive climate change and have human health impacts. It has been estimated that maritime shipping accounts for almost 3 percent of global carbon dioxide emissions and the industry’s negative impacts on air quality cause about 100,000 premature deaths each year.Decarbonizing shipping to reduce these detrimental effects is a goal of the International Maritime Organization, a U.N. agency that regulates maritime transport. One potential solution is switching the global fleet from fossil fuels to sustainable fuels such as ammonia, which could be nearly carbon-free when considering its production and use.But in a new study, an interdisciplinary team of researchers from MIT and elsewhere caution that burning ammonia for maritime fuel could worsen air quality further and lead to devastating public health impacts, unless it is adopted alongside strengthened emissions regulations.Ammonia combustion generates nitrous oxide (N2O), a greenhouse gas that is about 300 times more potent than carbon dioxide. It also emits nitrogen in the form of nitrogen oxides (NO and NO2, referred to as NOx), and unburnt ammonia may slip out, which eventually forms fine particulate matter in the atmosphere. These tiny particles can be inhaled deep into the lungs, causing health problems like heart attacks, strokes, and asthma.The new study indicates that, under current legislation, switching the global fleet to ammonia fuel could cause up to about 600,000 additional premature deaths each year. However, with stronger regulations and cleaner engine technology, the switch could lead to about 66,000 fewer premature deaths than currently caused by maritime shipping emissions, with far less impact on global warming.“Not all climate solutions are created equal. There is almost always some price to pay. We have to take a more holistic approach and consider all the costs and benefits of different climate solutions, rather than just their potential to decarbonize,” says Anthony Wong, a postdoc in the MIT Center for Global Change Science and lead author of the study.His co-authors include Noelle Selin, an MIT professor in the Institute for Data, Systems, and Society and the Department of Earth, Atmospheric and Planetary Sciences (EAPS); Sebastian Eastham, a former principal research scientist who is now a senior lecturer at Imperial College London; Christine Mounaïm-Rouselle, a professor at the University of Orléans in France; Yiqi Zhang, a researcher at the Hong Kong University of Science and Technology; and Florian Allroggen, a research scientist in the MIT Department of Aeronautics and Astronautics. The research appears this week in Environmental Research Letters.Greener, cleaner ammoniaTraditionally, ammonia is made by stripping hydrogen from natural gas and then combining it with nitrogen at extremely high temperatures. This process is often associated with a large carbon footprint. The maritime shipping industry is betting on the development of “green ammonia,” which is produced by using renewable energy to make hydrogen via electrolysis and to generate heat.“In theory, if you are burning green ammonia in a ship engine, the carbon emissions are almost zero,” Wong says.But even the greenest ammonia generates nitrous oxide (N2O), nitrogen oxides (NOx) when combusted, and some of the ammonia may slip out, unburnt. This nitrous oxide would escape into the atmosphere, where the greenhouse gas would remain for more than 100 years. At the same time, the nitrogen emitted as NOx and ammonia would fall to Earth, damaging fragile ecosystems. As these emissions are digested by bacteria, additional N2O  is produced.NOx and ammonia also mix with gases in the air to form fine particulate matter. A primary contributor to air pollution, fine particulate matter kills an estimated 4 million people each year.“Saying that ammonia is a ‘clean’ fuel is a bit of an overstretch. Just because it is carbon-free doesn’t necessarily mean it is clean and good for public health,” Wong says.A multifaceted modelThe researchers wanted to paint the whole picture, capturing the environmental and public health impacts of switching the global fleet to ammonia fuel. To do so, they designed scenarios to measure how pollutant impacts change under certain technology and policy assumptions.From a technological point of view, they considered two ship engines. The first burns pure ammonia, which generates higher levels of unburnt ammonia but emits fewer nitrogen oxides. The second engine technology involves mixing ammonia with hydrogen to improve combustion and optimize the performance of a catalytic converter, which controls both nitrogen oxides and unburnt ammonia pollution.They also considered three policy scenarios: current regulations, which only limit NOx emissions in some parts of the world; a scenario that adds ammonia emission limits over North America and Western Europe; and a scenario that adds global limits on ammonia and NOx emissions.The researchers used a ship track model to calculate how pollutant emissions change under each scenario and then fed the results into an air quality model. The air quality model calculates the impact of ship emissions on particulate matter and ozone pollution. Finally, they estimated the effects on global public health.One of the biggest challenges came from a lack of real-world data, since no ammonia-powered ships are yet sailing the seas. Instead, the researchers relied on experimental ammonia combustion data from collaborators to build their model.“We had to come up with some clever ways to make that data useful and informative to both the technology and regulatory situations,” he says.A range of outcomesIn the end, they found that with no new regulations and ship engines that burn pure ammonia, switching the entire fleet would cause 681,000 additional premature deaths each year.“While a scenario with no new regulations is not very realistic, it serves as a good warning of how dangerous ammonia emissions could be. And unlike NOx, ammonia emissions from shipping are currently unregulated,” Wong says.However, even without new regulations, using cleaner engine technology would cut the number of premature deaths down to about 80,000, which is about 20,000 fewer than are currently attributed to maritime shipping emissions. With stronger global regulations and cleaner engine technology, the number of people killed by air pollution from shipping could be reduced by about 66,000.“The results of this study show the importance of developing policies alongside new technologies,” Selin says. “There is a potential for ammonia in shipping to be beneficial for both climate and air quality, but that requires that regulations be designed to address the entire range of potential impacts, including both climate and air quality.”Ammonia’s air quality impacts would not be felt uniformly across the globe, and addressing them fully would require coordinated strategies across very different contexts. Most premature deaths would occur in East Asia, since air quality regulations are less stringent in this region. Higher levels of existing air pollution cause the formation of more particulate matter from ammonia emissions. In addition, shipping volume over East Asia is far greater than elsewhere on Earth, compounding these negative effects.In the future, the researchers want to continue refining their analysis. They hope to use these findings as a starting point to urge the marine industry to share engine data they can use to better evaluate air quality and climate impacts. They also hope to inform policymakers about the importance and urgency of updating shipping emission regulations.This research was funded by the MIT Climate and Sustainability Consortium. More

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      Fotini Christia named director of the Institute for Data, Systems, and Society

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      Fotini Christia, the Ford International Professor of Social Sciences in the Department of Political Science, has been named the new director of the Institute for Data, Systems, and Society (IDSS), effective July 1.“Fotini is well-positioned to guide IDSS into the next chapter. With her tenure as the director of the Sociotechnical Systems Research Center and as an associate director of IDSS since 2020, she has actively forged connections between the social sciences, data science, and computation,” says Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing and the Henry Ellis Warren Professor of Electrical Engineering and Computer Science. “I eagerly anticipate the ways in which she will advance and champion IDSS in alignment with the spirit and mission of the Schwarzman College of Computing.”“Fotini’s profound expertise as a social scientist and her adept use of data science, computational tools, and novel methodologies to grasp the dynamics of societal evolution across diverse fields, makes her a natural fit to lead IDSS,” says Asu Ozdaglar, deputy dean of the MIT Schwarzman College of Computing and head of the Department of Electrical Engineering and Computer Science.Christia’s research has focused on issues of conflict and cooperation in the Muslim world, for which she has conducted fieldwork in Afghanistan, Bosnia, Iraq, the Palestinian Territories, and Yemen, among others. More recently, her research has been directed at examining how to effectively integrate artificial intelligence tools in public policy.She was appointed the director of the Sociotechnical Systems Research Center (SSRC) and an associate director of IDSS in October 2020. SSRC, an interdisciplinary center housed within IDSS in the MIT Schwarzman College of Computing, focuses on the study of high-impact, complex societal challenges that shape our world.As part of IDSS, she is co-organizer of a cross-disciplinary research effort, the Initiative on Combatting Systemic Racism. Bringing together faculty and researchers from all of MIT’s five schools and the college, the initiative builds on extensive social science literature on systemic racism and uses big data to develop and harness computational tools that can help effect structural and normative change toward racial equity across housing, health care, policing, and social media. Christia is also chair of IDSS’s doctoral program in Social and Engineering Systems.Christia is the author of “Alliance Formation in Civil War” (Cambridge University Press, 2012), which was awarded the Luebbert Award for Best Book in Comparative Politics, the Lepgold Prize for Best Book in International Relations, and a Distinguished Book Award from the International Studies Association. She is co-editor with Graeme Blair (University of California, Los Angeles) and Jeremy Weinstein (incoming dean at Harvard Kennedy School) of “Crime, Insecurity, and Community Policing: Experiments on Building Trust,” forthcoming in August 2024 with Cambridge University Press.Her research has also appeared in Science, Nature Human Behavior, Review of Economic Studies, American Economic Journal: Applied Economics, NeurIPs, Communications Medicine, IEEE Transactions on Network Science and Engineering, American Political Science Review, and Annual Review of Political Science, among other journals. Her opinion pieces have been published in Foreign Affairs, The New York Times, The Washington Post, and The Boston Globe, among other outlets.A native of Greece, where she grew up in the port city of Salonika, Christia moved to the United States to attend college at Columbia University. She graduated magna cum laude in 2001 with a joint BA in economics–operations research and an MA in international affairs. She joined the MIT faculty in 2008 after receiving her PhD in public policy from Harvard University.Christia succeeds Noelle Selin, a professor in IDSS and the Department of Earth, Atmospheric, and Planetary Sciences. Selin has led IDSS as interim director for the 2023-24 academic year since July 2023, following Professor Martin Wainwright.“I am incredibly grateful to Noelle for serving as interim director this year. Her contributions in this role, as well as her time leading the Technology and Policy Program, have been invaluable. I’m delighted she will remain part of the IDSS community as a faculty member,” says Huttenlocher. More

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      A data-driven approach to making better choices

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      Imagine a world in which some important decision — a judge’s sentencing recommendation, a child’s treatment protocol, which person or business should receive a loan — was made more reliable because a well-designed algorithm helped a key decision-maker arrive at a better choice. A new MIT economics course is investigating these interesting possibilities.Class 14.163 (Algorithms and Behavioral Science) is a new cross-disciplinary course focused on behavioral economics, which studies the cognitive capacities and limitations of human beings. The course was co-taught this past spring by assistant professor of economics Ashesh Rambachan and visiting lecturer Sendhil Mullainathan.Rambachan studies the economic applications of machine learning, focusing on algorithmic tools that drive decision-making in the criminal justice system and consumer lending markets. He also develops methods for determining causation using cross-sectional and dynamic data.Mullainathan will soon join the MIT departments of Electrical Engineering and Computer Science and Economics as a professor. His research uses machine learning to understand complex problems in human behavior, social policy, and medicine. Mullainathan co-founded the Abdul Latif Jameel Poverty Action Lab (J-PAL) in 2003.The new course’s goals are both scientific (to understand people) and policy-driven (to improve society by improving decisions). Rambachan believes that machine-learning algorithms provide new tools for both the scientific and applied goals of behavioral economics.“The course investigates the deployment of computer science, artificial intelligence (AI), economics, and machine learning in service of improved outcomes and reduced instances of bias in decision-making,” Rambachan says.There are opportunities, Rambachan believes, for constantly evolving digital tools like AI, machine learning, and large language models (LLMs) to help reshape everything from discriminatory practices in criminal sentencing to health-care outcomes among underserved populations.Students learn how to use machine learning tools with three main objectives: to understand what they do and how they do it, to formalize behavioral economics insights so they compose well within machine learning tools, and to understand areas and topics where the integration of behavioral economics and algorithmic tools might be most fruitful.Students also produce ideas, develop associated research, and see the bigger picture. They’re led to understand where an insight fits and see where the broader research agenda is leading. Participants can think critically about what supervised LLMs can (and cannot) do, to understand how to integrate those capacities with the models and insights of behavioral economics, and to recognize the most fruitful areas for the application of what investigations uncover.The dangers of subjectivity and biasAccording to Rambachan, behavioral economics acknowledges that biases and mistakes exist throughout our choices, even absent algorithms. “The data used by our algorithms exist outside computer science and machine learning, and instead are often produced by people,” he continues. “Understanding behavioral economics is therefore essential to understanding the effects of algorithms and how to better build them.”Rambachan sought to make the course accessible regardless of attendees’ academic backgrounds. The class included advanced degree students from a variety of disciplines.By offering students a cross-disciplinary, data-driven approach to investigating and discovering ways in which algorithms might improve problem-solving and decision-making, Rambachan hopes to build a foundation on which to redesign existing systems of jurisprudence, health care, consumer lending, and industry, to name a few areas.“Understanding how data are generated can help us understand bias,” Rambachan says. “We can ask questions about producing a better outcome than what currently exists.”Useful tools for re-imagining social operationsEconomics doctoral student Jimmy Lin was skeptical about the claims Rambachan and Mullainathan made when the class began, but changed his mind as the course continued.“Ashesh and Sendhil started with two provocative claims: The future of behavioral science research will not exist without AI, and the future of AI research will not exist without behavioral science,” Lin says. “Over the course of the semester, they deepened my understanding of both fields and walked us through numerous examples of how economics informed AI research and vice versa.”Lin, who’d previously done research in computational biology, praised the instructors’ emphasis on the importance of a “producer mindset,” thinking about the next decade of research rather than the previous decade. “That’s especially important in an area as interdisciplinary and fast-moving as the intersection of AI and economics — there isn’t an old established literature, so you’re forced to ask new questions, invent new methods, and create new bridges,” he says.The speed of change to which Lin alludes is a draw for him, too. “We’re seeing black-box AI methods facilitate breakthroughs in math, biology, physics, and other scientific disciplines,” Lin  says. “AI can change the way we approach intellectual discovery as researchers.”An interdisciplinary future for economics and social systemsStudying traditional economic tools and enhancing their value with AI may yield game-changing shifts in how institutions and organizations teach and empower leaders to make choices.“We’re learning to track shifts, to adjust frameworks and better understand how to deploy tools in service of a common language,” Rambachan says. “We must continually interrogate the intersection of human judgment, algorithms, AI, machine learning, and LLMs.”Lin enthusiastically recommended the course regardless of students’ backgrounds. “Anyone broadly interested in algorithms in society, applications of AI across academic disciplines, or AI as a paradigm for scientific discovery should take this class,” he says. “Every lecture felt like a goldmine of perspectives on research, novel application areas, and inspiration on how to produce new, exciting ideas.”The course, Rambachan says, argues that better-built algorithms can improve decision-making across disciplines. “By building connections between economics, computer science, and machine learning, perhaps we can automate the best of human choices to improve outcomes while minimizing or eliminating the worst,” he says.Lin remains excited about the course’s as-yet unexplored possibilities. “It’s a class that makes you excited about the future of research and your own role in it,” he says. 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      Q&A: How refusal can be an act of design

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      This month in the ACM Journal on Responsible Computing, MIT graduate student Jonathan Zong SM ’20 and co-author J. Nathan Matias SM ’13, PhD ’17 of the Cornell Citizens and Technology Lab examine how the notion of refusal can open new avenues in the field of data ethics. In their open-access report, “Data Refusal From Below: A Framework for Understanding, Evaluating, and Envisioning Refusal as Design,” the pair proposes a framework in four dimensions to map how individuals can say “no” to technology misuses. At the same time, the researchers argue that just like design, refusal is generative, and has the potential to create alternate futures.

      Zong, a PhD candidate in electrical engineering and computer science, 2022-23 MIT Morningside Academy for Design Design Fellow, and member of the MIT Visualization Group, describes his latest work in this Q&A.

      Q: How do you define the concept of “refusal,” and where does it come from?

      A: Refusal was developed in feminist and Indigenous studies. It’s this idea of saying “no,” without being given permission to say “no.” Scholars like Ruha Benjamin write about refusal in the context of surveillance, race, and bioethics, and talk about it as a necessary counterpart to consent. Others, like the authors of the “Feminist Data Manifest-No,” think of refusal as something that can help us commit to building better futures.

      Benjamin illustrates cases where the choice to refuse is not equally possible for everyone, citing examples involving genetic data and refugee screenings in the U.K. The imbalance of power in these situations underscores the broader concept of refusal, extending beyond rejecting specific options to challenging the entire set of choices presented.

      Q: What inspired you to work on the notion of refusal as an act of design?

      A: In my work on data ethics, I’ve been thinking about how to incorporate processes into research data collection, particularly around consent and opt-out, with a focus on individual autonomy and the idea of giving people choices about the way that their data is used. But when it comes to data privacy, simply making choices available is not enough. Choices can be unequally available, or create no-win situations where all options are bad. This led me to the concept of refusal: questioning the authority of data collectors and challenging their legitimacy.

      The key idea of my work is that refusal is an act of design. I think of refusal as deliberate actions to redesign our socio-technical landscape by exerting some sort of influence. Like design, refusal is generative. Like design, it’s oriented towards creating alternate possibilities and alternate futures. Design is a process of exploring or traversing a space of possibility. Applying a design framework to cases of refusal drawn from scholarly and journalistic sources allowed me to establish a common language for talking about refusal and to imagine refusals that haven’t been explored yet.

      Q: What are the stakes around data privacy and data collection?

      A: The use of data for facial recognition surveillance in the U.S. is a big example we use in the paper. When people do everyday things like post on social media or walk past cameras in public spaces, they might be contributing their data to training facial recognition systems. For instance, a tech company may take photos from a social media site and build facial recognition that they then sell to the government. In the U.S., these systems are disproportionately used by police to surveil communities of color. It is difficult to apply concepts like consent and opt out of these processes, because they happen over time and involve multiple kinds of institutions. It’s also not clear that individual opt-out would do anything to change the overall situation. Refusal then becomes a crucial avenue, at both individual and community levels, to think more broadly of how affected people still exert some kind of voice or agency, without necessarily having an official channel to do so.

      Q: Why do you think these issues are more particularly affecting disempowered communities?

      A: People who are affected by technologies are not always included in the design process for those technologies. Refusal then becomes a meaningful expression of values and priorities for those who were not part of the early design conversations. Actions taken against technologies like face surveillance — be it legal battles against companies, advocacy for stricter regulations, or even direct action like disabling security cameras — may not fit the conventional notion of participating in a design process. And yet, these are the actions available to refusers who may be excluded from other forms of participation.

      I’m particularly inspired by the movement around Indigenous data sovereignty. Organizations like the First Nations Information Governance Centre work towards prioritizing Indigenous communities’ perspectives in data collection, and refuse inadequate representation in official health data from the Canadian government. I think this is a movement that exemplifies the potential of refusal, not only as a way to reject what’s being offered, but also as a means to propose a constructive alternative, very much like design. Refusal is not merely a negation, but a pathway to different futures.

      Q: Can you elaborate on the design framework you propose?

      A: Refusals vary widely across contexts and scales. Developing a framework for refusal is about helping people see actions that are seemingly very different as instances of the same broader idea. Our framework consists of four facets: autonomy, time, power, and cost.

      Consider the case of IBM creating a facial recognition dataset using people’s photos without consent. We saw multiple forms of refusal emerge in response. IBM allowed individuals to opt out by withdrawing their photos. People collectively refused by creating a class-action lawsuit against IBM. Around the same time, many U.S. cities started passing local legislation banning the government use of facial recognition. Evaluating these cases through the framework highlights commonalities and differences. The framework highlights varied approaches to autonomy, like individual opt-out and collective action. Regarding time, opt-outs and lawsuits react to past harm, while legislation might proactively prevent future harm. Power dynamics differ; withdrawing individual photos minimally influences IBM, while legislation could potentially cause longer-term change. And as for cost, individual opt-out seems less demanding, while other approaches require more time and effort, balanced against potential benefits.

      The framework facilitates case description and comparison across these dimensions. I think its generative nature encourages exploration of novel forms of refusal as well. By identifying the characteristics we want to see in future refusal strategies — collective, proactive, powerful, low-cost… — we can aspire to shape future approaches and change the behavior of data collectors. We may not always be able to combine all these criteria, but the framework provides a means to articulate our aspirational goals in this context.

      Q: What impact do you hope this research will have?

      A: I hope to expand the notion of who can participate in design, and whose actions are seen as legitimate expressions of design input. I think a lot of work so far in the conversation around data ethics prioritizes the perspective of computer scientists who are trying to design better systems, at the expense of the perspective of people for whom the systems are not currently working. So, I hope designers and computer scientists can embrace the concept of refusal as a legitimate form of design, and a source of inspiration. There’s a vital conversation happening, one that should influence the design of future systems, even if expressed through unconventional means.

      One of the things I want to underscore in the paper is that design extends beyond software. Taking a socio-technical perspective, the act of designing encompasses software, institutions, relationships, and governance structures surrounding data use. I want people who aren’t software engineers, like policymakers or activists, to view themselves as integral to the technology design process. More

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      Study: Global deforestation leads to more mercury pollution

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      About 10 percent of human-made mercury emissions into the atmosphere each year are the result of global deforestation, according to a new MIT study.

      The world’s vegetation, from the Amazon rainforest to the savannahs of sub-Saharan Africa, acts as a sink that removes the toxic pollutant from the air. However, if the current rate of deforestation remains unchanged or accelerates, the researchers estimate that net mercury emissions will keep increasing.

      “We’ve been overlooking a significant source of mercury, especially in tropical regions,” says Ari Feinberg, a former postdoc in the Institute for Data, Systems, and Society (IDSS) and lead author of the study.

      The researchers’ model shows that the Amazon rainforest plays a particularly important role as a mercury sink, contributing about 30 percent of the global land sink. Curbing Amazon deforestation could thus have a substantial impact on reducing mercury pollution.

      The team also estimates that global reforestation efforts could increase annual mercury uptake by about 5 percent. While this is significant, the researchers emphasize that reforestation alone should not be a substitute for worldwide pollution control efforts.

      “Countries have put a lot of effort into reducing mercury emissions, especially northern industrialized countries, and for very good reason. But 10 percent of the global anthropogenic source is substantial, and there is a potential for that to be even greater in the future. [Addressing these deforestation-related emissions] needs to be part of the solution,” says senior author Noelle Selin, a professor in IDSS and MIT’s Department of Earth, Atmospheric and Planetary Sciences.

      Feinberg and Selin are joined on the paper by co-authors Martin Jiskra, a former Swiss National Science Foundation Ambizione Fellow at the University of Basel; Pasquale Borrelli, a professor at Roma Tre University in Italy; and Jagannath Biswakarma, a postdoc at the Swiss Federal Institute of Aquatic Science and Technology. The paper appears today in Environmental Science and Technology.

      Modeling mercury

      Over the past few decades, scientists have generally focused on studying deforestation as a source of global carbon dioxide emissions. Mercury, a trace element, hasn’t received the same attention, partly because the terrestrial biosphere’s role in the global mercury cycle has only recently been better quantified.

      Plant leaves take up mercury from the atmosphere, in a similar way as they take up carbon dioxide. But unlike carbon dioxide, mercury doesn’t play an essential biological function for plants. Mercury largely stays within a leaf until it falls to the forest floor, where the mercury is absorbed by the soil.

      Mercury becomes a serious concern for humans if it ends up in water bodies, where it can become methylated by microorganisms. Methylmercury, a potent neurotoxin, can be taken up by fish and bioaccumulated through the food chain. This can lead to risky levels of methylmercury in the fish humans eat.

      “In soils, mercury is much more tightly bound than it would be if it were deposited in the ocean. The forests are doing a sort of ecosystem service, in that they are sequestering mercury for longer timescales,” says Feinberg, who is now a postdoc in the Blas Cabrera Institute of Physical Chemistry in Spain.

      In this way, forests reduce the amount of toxic methylmercury in oceans.

      Many studies of mercury focus on industrial sources, like burning fossil fuels, small-scale gold mining, and metal smelting. A global treaty, the 2013 Minamata Convention, calls on nations to reduce human-made emissions. However, it doesn’t directly consider impacts of deforestation.

      The researchers launched their study to fill in that missing piece.

      In past work, they had built a model to probe the role vegetation plays in mercury uptake. Using a series of land use change scenarios, they adjusted the model to quantify the role of deforestation.

      Evaluating emissions

      This chemical transport model tracks mercury from its emissions sources to where it is chemically transformed in the atmosphere and then ultimately to where it is deposited, mainly through rainfall or uptake into forest ecosystems.

      They divided the Earth into eight regions and performed simulations to calculate deforestation emissions factors for each, considering elements like type and density of vegetation, mercury content in soils, and historical land use.

      However, good data for some regions were hard to come by.

      They lacked measurements from tropical Africa or Southeast Asia — two areas that experience heavy deforestation. To get around this gap, they used simpler, offline models to simulate hundreds of scenarios, which helped them improve their estimations of potential uncertainties.

      They also developed a new formulation for mercury emissions from soil. This formulation captures the fact that deforestation reduces leaf area, which increases the amount of sunlight that hits the ground and accelerates the outgassing of mercury from soils.

      The model divides the world into grid squares, each of which is a few hundred square kilometers. By changing land surface and vegetation parameters in certain squares to represent deforestation and reforestation scenarios, the researchers can capture impacts on the mercury cycle.

      Overall, they found that about 200 tons of mercury are emitted to the atmosphere as the result of deforestation, or about 10 percent of total human-made emissions. But in tropical and sub-tropical countries, deforestation emissions represent a higher percentage of total emissions. For example, in Brazil deforestation emissions are 40 percent of total human-made emissions.

      In addition, people often light fires to prepare tropical forested areas for agricultural activities, which causes more emissions by releasing mercury stored by vegetation.

      “If deforestation was a country, it would be the second highest emitting country, after China, which emits around 500 tons of mercury a year,” Feinberg adds.

      And since the Minamata Convention is now addressing primary mercury emissions, scientists can expect deforestation to become a larger fraction of human-made emissions in the future.

      “Policies to protect forests or cut them down have unintended effects beyond their target. It is important to consider the fact that these are systems, and they involve human activities, and we need to understand them better in order to actually solve the problems that we know are out there,” Selin says.

      By providing this first estimate, the team hopes to inspire more research in this area.

      In the future, they want to incorporate more dynamic Earth system models into their analysis, which would enable them to interactively track mercury uptake and better model the timescale of vegetation regrowth.

      “This paper represents an important advance in our understanding of global mercury cycling by quantifying a pathway that has long been suggested but not yet quantified. Much of our research to date has focused on primary anthropogenic emissions — those directly resulting from human activity via coal combustion or mercury-gold amalgam burning in artisanal and small-scale gold mining,” says Jackie Gerson, an assistant professor in the Department of Earth and Environmental Sciences at Michigan State University, who was not involved with this research. “This research shows that deforestation can also result in substantial mercury emissions and needs to be considered both in terms of global mercury models and land management policies. It therefore has the potential to advance our field scientifically as well as to promote policies that reduce mercury emissions via deforestation.

      This work was funded, in part, by the U.S. National Science Foundation, the Swiss National Science Foundation, and Swiss Federal Institute of Aquatic Science and Technology. More

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      Generating the policy of tomorrow

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      As first-year students in the Social and Engineering Systems (SES) doctoral program within the MIT Institute for Data, Systems, and Society (IDSS), Eric Liu and Ashely Peake share an interest in investigating housing inequality issues.

      They also share a desire to dive head-first into their research.

      “In the first year of your PhD, you’re taking classes and still getting adjusted, but we came in very eager to start doing research,” Liu says.

      Liu, Peake, and many others found an opportunity to do hands-on research on real-world problems at the MIT Policy Hackathon, an initiative organized by students in IDSS, including the Technology and Policy Program (TPP). The weekend-long, interdisciplinary event — now in its sixth year — continues to gather hundreds of participants from around the globe to explore potential solutions to some of society’s greatest challenges.

      This year’s theme, “Hack-GPT: Generating the Policy of Tomorrow,” sought to capitalize on the popularity of generative AI (like the chatbot ChatGPT) and the ways it is changing how we think about technical and policy-based challenges, according to Dansil Green, a second-year TPP master’s student and co-chair of the event.

      “We encouraged our teams to utilize and cite these tools, thinking about the implications that generative AI tools have on their different challenge categories,” Green says.

      After 2022’s hybrid event, this year’s organizers pivoted back to a virtual-only approach, allowing them to increase the overall number of participants in addition to increasing the number of teams per challenge by 20 percent.

      “Virtual allows you to reach more people — we had a high number of international participants this year — and it helps reduce some of the costs,” Green says. “I think going forward we are going to try and switch back and forth between virtual and in-person because there are different benefits to each.”

      “When the magic hits”

      Liu and Peake competed in the housing challenge category, where they could gain research experience in their actual field of study. 

      “While I am doing housing research, I haven’t necessarily had a lot of opportunities to work with actual housing data before,” says Peake, who recently joined the SES doctoral program after completing an undergraduate degree in applied math last year. “It was a really good experience to get involved with an actual data problem, working closer with Eric, who’s also in my lab group, in addition to meeting people from MIT and around the world who are interested in tackling similar questions and seeing how they think about things differently.”

      Joined by Adrian Butterton, a Boston-based paralegal, as well as Hudson Yuen and Ian Chan, two software engineers from Canada, Liu and Peake formed what would end up being the winning team in their category: “Team Ctrl+Alt+Defeat.” They quickly began organizing a plan to address the eviction crisis in the United States.

      “I think we were kind of surprised by the scope of the question,” Peake laughs. “In the end, I think having such a large scope motivated us to think about it in a more realistic kind of way — how could we come up with a solution that was adaptable and therefore could be replicated to tackle different kinds of problems.”

      Watching the challenge on the livestream together on campus, Liu says they immediately went to work, and could not believe how quickly things came together.

      “We got our challenge description in the evening, came out to the purple common area in the IDSS building and literally it took maybe an hour and we drafted up the entire project from start to finish,” Liu says. “Then our software engineer partners had a dashboard built by 1 a.m. — I feel like the hackathon really promotes that really fast dynamic work stream.”

      “People always talk about the grind or applying for funding — but when that magic hits, it just reminds you of the part of research that people don’t talk about, and it was really a great experience to have,” Liu adds.

      A fresh perspective

      “We’ve organized hackathons internally at our company and they are great for fostering innovation and creativity,” says Letizia Bordoli, senior AI product manager at Veridos, a German-based identity solutions company that provided this year’s challenge in Data Systems for Human Rights. “It is a great opportunity to connect with talented individuals and explore new ideas and solutions that we might not have thought about.”

      The challenge provided by Veridos was focused on finding innovative solutions to universal birth registration, something Bordoli says only benefited from the fact that the hackathon participants were from all over the world.

      “Many had local and firsthand knowledge about certain realities and challenges [posed by the lack of] birth registration,” Bordoli says. “It brings fresh perspectives to existing challenges, and it gave us an energy boost to try to bring innovative solutions that we may not have considered before.”

      New frontiers

      Alongside the housing and data systems for human rights challenges was a challenge in health, as well as a first-time opportunity to tackle an aerospace challenge in the area of space for environmental justice.

      “Space can be a very hard challenge category to do data-wise since a lot of data is proprietary, so this really developed over the last few months with us having to think about how we could do more with open-source data,” Green explains. “But I am glad we went the environmental route because it opened the challenge up to not only space enthusiasts, but also environment and climate people.”

      One of the participants to tackle this new challenge category was Yassine Elhallaoui, a system test engineer from Norway who specializes in AI solutions and has 16 years of experience working in the oil and gas fields. Elhallaoui was a member of Team EcoEquity, which proposed an increase in policies supporting the use of satellite data to ensure proper evaluation and increase water resiliency for vulnerable communities.

      “The hackathons I have participated in in the past were more technical,” Elhallaoui says. “Starting with [MIT Science and Technology Policy Institute Director Kristen Kulinowski’s] workshop about policy writers and the solutions they came up with, and the analysis they had to do … it really changed my perspective on what a hackathon can do.”

      “A policy hackathon is something that can make real changes in the world,” she adds. More

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      Forging climate connections across the Institute

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      Climate change is the ultimate cross-cutting issue: Not limited to any one discipline, it ranges across science, technology, policy, culture, human behavior, and well beyond. The response to it likewise requires an all-of-MIT effort.

      Now, to strengthen such an effort, a new grant program spearheaded by the Climate Nucleus, the faculty committee charged with the oversight and implementation of Fast Forward: MIT’s Climate Action Plan for the Decade, aims to build up MIT’s climate leadership capacity while also supporting innovative scholarship on diverse climate-related topics and forging new connections across the Institute.

      Called the Fast Forward Faculty Fund (F^4 for short), the program has named its first cohort of six faculty members after issuing its inaugural call for proposals in April 2023. The cohort will come together throughout the year for climate leadership development programming and networking. The program provides financial support for graduate students who will work with the faculty members on the projects — the students will also participate in leadership-building activities — as well as $50,000 in flexible, discretionary funding to be used to support related activities. 

      “Climate change is a crisis that truly touches every single person on the planet,” says Noelle Selin, co-chair of the nucleus and interim director of the Institute for Data, Systems, and Society. “It’s therefore essential that we build capacity for every member of the MIT community to make sense of the problem and help address it. Through the Fast Forward Faculty Fund, our aim is to have a cohort of climate ambassadors who can embed climate everywhere at the Institute.”

      F^4 supports both faculty who would like to begin doing climate-related work, as well as faculty members who are interested in deepening their work on climate. The program has the core goal of developing cohorts of F^4 faculty and graduate students who, in addition to conducting their own research, will become climate leaders at MIT, proactively looking for ways to forge new climate connections across schools, departments, and disciplines.

      One of the projects, “Climate Crisis and Real Estate: Science-based Mitigation and Adaptation Strategies,” led by Professor Siqi Zheng of the MIT Center for Real Estate in collaboration with colleagues from the MIT Sloan School of Management, focuses on the roughly 40 percent of carbon dioxide emissions that come from the buildings and real estate sector. Zheng notes that this sector has been slow to respond to climate change, but says that is starting to change, thanks in part to the rising awareness of climate risks and new local regulations aimed at reducing emissions from buildings.

      Using a data-driven approach, the project seeks to understand the efficient and equitable market incentives, technology solutions, and public policies that are most effective at transforming the real estate industry. Johnattan Ontiveros, a graduate student in the Technology and Policy Program, is working with Zheng on the project.

      “We were thrilled at the incredible response we received from the MIT faculty to our call for proposals, which speaks volumes about the depth and breadth of interest in climate at MIT,” says Anne White, nucleus co-chair and vice provost and associate vice president for research. “This program makes good on key commitments of the Fast Forward plan, supporting cutting-edge new work by faculty and graduate students while helping to deepen the bench of climate leaders at MIT.”

      During the 2023-24 academic year, the F^4 faculty and graduate student cohorts will come together to discuss their projects, explore opportunities for collaboration, participate in climate leadership development, and think proactively about how to deepen interdisciplinary connections among MIT community members interested in climate change.

      The six inaugural F^4 awardees are:

      Professor Tristan Brown, History Section: Humanistic Approaches to the Climate Crisis  

      With this project, Brown aims to create a new community of practice around narrative-centric approaches to environmental and climate issues. Part of a broader humanities initiative at MIT, it brings together a global working group of interdisciplinary scholars, including Serguei Saavedra (Department of Civil and Environmental Engineering) and Or Porath (Tel Aviv University; Religion), collectively focused on examining the historical and present links between sacred places and biodiversity for the purposes of helping governments and nongovernmental organizations formulate better sustainability goals. Boyd Ruamcharoen, a PhD student in the History, Anthropology, and Science, Technology, and Society (HASTS) program, will work with Brown on this project.

      Professor Kerri Cahoy, departments of Aeronautics and Astronautics and Earth, Atmospheric, and Planetary Sciences (AeroAstro): Onboard Autonomous AI-driven Satellite Sensor Fusion for Coastal Region Monitoring

      The motivation for this project is the need for much better data collection from satellites, where technology can be “20 years behind,” says Cahoy. As part of this project, Cahoy will pursue research in the area of autonomous artificial intelligence-enabled rapid sensor fusion (which combines data from different sensors, such as radar and cameras) onboard satellites to improve understanding of the impacts of climate change, specifically sea-level rise and hurricanes and flooding in coastal regions. Graduate students Madeline Anderson, a PhD student in electrical engineering and computer science (EECS), and Mary Dahl, a PhD student in AeroAstro, will work with Cahoy on this project.

      Professor Priya Donti, Department of Electrical Engineering and Computer Science: Robust Reinforcement Learning for High-Renewables Power Grids 

      With renewables like wind and solar making up a growing share of electricity generation on power grids, Donti’s project focuses on improving control methods for these distributed sources of electricity. The research will aim to create a realistic representation of the characteristics of power grid operations, and eventually inform scalable operational improvements in power systems. It will “give power systems operators faith that, OK, this conceptually is good, but it also actually works on this grid,” says Donti. PhD candidate Ana Rivera from EECS is the F^4 graduate student on the project.

      Professor Jason Jackson, Department of Urban Studies and Planning (DUSP): Political Economy of the Climate Crisis: Institutions, Power and Global Governance

      This project takes a political economy approach to the climate crisis, offering a distinct lens to examine, first, the political governance challenge of mobilizing climate action and designing new institutional mechanisms to address the global and intergenerational distributional aspects of climate change; second, the economic challenge of devising new institutional approaches to equitably finance climate action; and third, the cultural challenge — and opportunity — of empowering an adaptive socio-cultural ecology through traditional knowledge and local-level social networks to achieve environmental resilience. Graduate students Chen Chu and Mrinalini Penumaka, both PhD students in DUSP, are working with Jackson on the project.

      Professor Haruko Wainwright, departments of Nuclear Science and Engineering (NSE) and Civil and Environmental Engineering: Low-cost Environmental Monitoring Network Technologies in Rural Communities for Addressing Climate Justice 

      This project will establish a community-based climate and environmental monitoring network in addition to a data visualization and analysis infrastructure in rural marginalized communities to better understand and address climate justice issues. The project team plans to work with rural communities in Alaska to install low-cost air and water quality, weather, and soil sensors. Graduate students Kay Whiteaker, an MS candidate in NSE, and Amandeep Singh, and MS candidate in System Design and Management at Sloan, are working with Wainwright on the project, as is David McGee, professor in earth, atmospheric, and planetary sciences.

      Professor Siqi Zheng, MIT Center for Real Estate and DUSP: Climate Crisis and Real Estate: Science-based Mitigation and Adaptation Strategies 

      See the text above for the details on this project. More

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      Improving US air quality, equitably

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      Decarbonization of national economies will be key to achieving global net-zero emissions by 2050, a major stepping stone to the Paris Agreement’s long-term goal of keeping global warming well below 2 degrees Celsius (and ideally 1.5 C), and thereby averting the worst consequences of climate change. Toward that end, the United States has pledged to reduce its greenhouse gas emissions by 50-52 percent from 2005 levels by 2030, backed by its implementation of the 2022 Inflation Reduction Act. This strategy is consistent with a 50-percent reduction in carbon dioxide (CO2) by the end of the decade.

      If U.S. federal carbon policy is successful, the nation’s overall air quality will also improve. Cutting CO2 emissions reduces atmospheric concentrations of air pollutants that lead to the formation of fine particulate matter (PM2.5), which causes more than 200,000 premature deaths in the United States each year. But an average nationwide improvement in air quality will not be felt equally; air pollution exposure disproportionately harms people of color and lower-income populations.

      How effective are current federal decarbonization policies in reducing U.S. racial and economic disparities in PM2.5 exposure, and what changes will be needed to improve their performance? To answer that question, researchers at MIT and Stanford University recently evaluated a range of policies which, like current U.S. federal carbon policies, reduce economy-wide CO2 emissions by 40-60 percent from 2005 levels by 2030. Their findings appear in an open-access article in the journal Nature Communications.

      First, they show that a carbon-pricing policy, while effective in reducing PM2.5 exposure for all racial/ethnic groups, does not significantly mitigate relative disparities in exposure. On average, the white population undergoes far less exposure than Black, Hispanic, and Asian populations. This policy does little to reduce exposure disparities because the CO2 emissions reductions that it achieves primarily occur in the coal-fired electricity sector. Other sectors, such as industry and heavy-duty diesel transportation, contribute far more PM2.5-related emissions.

      The researchers then examine thousands of different reduction options through an optimization approach to identify whether any possible combination of carbon dioxide reductions in the range of 40-60 percent can mitigate disparities. They find that that no policy scenario aligned with current U.S. carbon dioxide emissions targets is likely to significantly reduce current PM2.5 exposure disparities.

      “Policies that address only about 50 percent of CO2 emissions leave many polluting sources in place, and those that prioritize reductions for minorities tend to benefit the entire population,” says Noelle Selin, supervising author of the study and a professor at MIT’s Institute for Data, Systems and Society and Department of Earth, Atmospheric and Planetary Sciences. “This means that a large range of policies that reduce CO2 can improve air quality overall, but can’t address long-standing inequities in air pollution exposure.”

      So if climate policy alone cannot adequately achieve equitable air quality results, what viable options remain? The researchers suggest that more ambitious carbon policies could narrow racial and economic PM2.5 exposure disparities in the long term, but not within the next decade. To make a near-term difference, they recommend interventions designed to reduce PM2.5 emissions resulting from non-CO2 sources, ideally at the economic sector or community level.

      “Achieving improved PM2.5 exposure for populations that are disproportionately exposed across the United States will require thinking that goes beyond current CO2 policy strategies, most likely involving large-scale structural changes,” says Selin. “This could involve changes in local and regional transportation and housing planning, together with accelerated efforts towards decarbonization.” More

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      Day of AI curriculum meets the moment

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      MIT Responsible AI for Social Empowerment and Education (RAISE) recently celebrated the second annual Day of AI with two flagship local events. The Edward M. Kennedy Institute for the U.S. Senate in Boston hosted a human rights and data policy-focused event that was streamed worldwide. Dearborn STEM Academy in Roxbury, Massachusetts, hosted a student workshop in collaboration with Amazon Future Engineer. With over 8,000 registrations across all 50 U.S. states and 108 countries in 2023, participation in Day of AI has more than doubled since its inaugural year.

      Day of AI is a free curriculum of lessons and hands-on activities designed to teach kids of all ages and backgrounds the basics and responsible use of artificial intelligence, designed by researchers at MIT RAISE. This year, resources were available for educators to run at any time and in any increments they chose. The curriculum included five new modules to address timely topics like ChatGPT in School, Teachable Machines, AI and Social Media, Data Science and Me, and more. A collaboration with the International Society for Technology in Education also introduced modules for early elementary students. Educators across the world shared photos, videos, and stories of their students’ engagement, expressing excitement and even relief over the accessible lessons.

      Professor Cynthia Breazeal, director of RAISE, dean for digital learning at MIT, and head of the MIT Media Lab’s Personal Robots research group, said, “It’s been a year of extraordinary advancements in AI, and with that comes necessary conversations and concerns about who and what this technology is for. With our Day of AI events, we want to celebrate the teachers and students who are putting in the work to make sure that AI is for everyone.”

      Reflecting community values and protecting digital citizens

      Play video

      On May 18, 2023, MIT RAISE hosted a global Day of AI celebration featuring a flagship local event focused on human rights and data policy at the Edward M. Kennedy Institute for the U.S. Senate. Students from the Warren Prescott Middle School and New Mission High School heard from speakers the City of Boston, Liberty Mutual, and MIT to discuss the many benefits and challenges of artificial intelligence education. Video: MIT Open Learning

      MIT President Sally Kornbluth welcomed students from Warren Prescott Middle School and New Mission High School to the Day of AI program at the Edward M. Kennedy Institute. Kornbluth reflected on the exciting potential of AI, along with the ethical considerations society needs to be responsible for.

      “AI has the potential to do all kinds of fantastic things, including driving a car, helping us with the climate crisis, improving health care, and designing apps that we can’t even imagine yet. But what we have to make sure it doesn’t do is cause harm to individuals, to communities, to us — society as a whole,” she said.

      This theme resonated with each of the event speakers, whose jobs spanned the sectors of education, government, and business. Yo Deshpande, technologist for the public realm, and Michael Lawrence Evans, program director of new urban mechanics from the Boston Mayor’s Office, shared how Boston thinks about using AI to improve city life in ways that are “equitable, accessible, and delightful.” Deshpande said, “We have the opportunity to explore not only how AI works, but how using AI can line up with our values, the way we want to be in the world, and the way we want to be in our community.”

      Adam L’Italien, chief innovation officer at Liberty Mutual Insurance (one of Day of AI’s founding sponsors), compared our present moment with AI technologies to the early days of personal computers and internet connection. “Exposure to emerging technologies can accelerate progress in the world and in your own lives,” L’Italien said, while recognizing that the AI development process needs to be inclusive and mitigate biases.

      Human policies for artificial intelligence

      So how does society address these human rights concerns about AI? Marc Aidinoff ’21, former White House Office of Science and Technology Policy chief of staff, led a discussion on how government policy can influence the parameters of how technology is developed and used, like the Blueprint for an AI Bill of Rights. Aidinoff said, “The work of building the world you want to see is far harder than building the technical AI system … How do you work with other people and create a collective vision for what we want to do?” Warren Prescott Middle School students described how AI could be used to solve problems that humans couldn’t. But they also shared their concerns that AI could affect data privacy, learning deficits, social media addiction, job displacement, and propaganda.

      In a mock U.S. Senate trial activity designed by Daniella DiPaola, PhD student at the MIT Media Lab, the middle schoolers investigated what rights might be undermined by AI in schools, hospitals, law enforcement, and corporations. Meanwhile, New Mission High School students workshopped the ideas behind bill S.2314, the Social Media Addiction Reduction Technology (SMART) Act, in an activity designed by Raechel Walker, graduate research assistant in the Personal Robots Group, and Matt Taylor, research assistant at the Media Lab. They discussed what level of control could or should be introduced at the parental, educational, and governmental levels to reduce the risks of internet addiction.

      “Alexa, how do I program AI?”

      Play video

      The 2023 Day of AI celebration featured a flagship local event at the Dearborn STEM Academy in Roxbury in collaboration with Amazon Future Engineer. Students participated in a hands-on activity using MIT App Inventor as part of Day of AI’s Alexa lesson. Video: MIT Open Learning

      At Dearborn STEM Academy, Amazon Future Engineer helped students work through the Intro to Voice AI curriculum module in real-time. Students used MIT App Inventor to code basic commands for Alexa. In an interview with WCVB, Principal Darlene Marcano said, “It’s important that we expose our students to as many different experiences as possible. The students that are participating are on track to be future computer scientists and engineers.”

      Breazeal told Dearborn students, “We want you to have an informed voice about how you want AI to be used in society. We want you to feel empowered that you can shape the world. You can make things with AI to help make a better world and a better community.”

      Rohit Prasad ’08, senior vice president and head scientist for Alexa at Amazon, and Victor Reinoso ’97, global director of philanthropic education initiatives at Amazon, also joined the event. “Amazon and MIT share a commitment to helping students discover a world of possibilities through STEM and AI education,” said Reinoso. “There’s a lot of current excitement around the technological revolution with generative AI and large language models, so we’re excited to help students explore careers of the future and navigate the pathways available to them.” To highlight their continued investment in the local community and the school program, Amazon donated a $25,000 Innovation and Early College Pathways Program Grant to the Boston Public School system.

      Day of AI down under

      Not only was the Day of AI program widely adopted across the globe, Australian educators were inspired to adapt their own regionally specific curriculum. An estimated 161,000 AI professionals will be needed in Australia by 2030, according to the National Artificial Intelligence Center in the Commonwealth Scientific and Industrial Research Organization (CSIRO), an Australian government agency and Day of AI Australia project partner. CSIRO worked with the University of New South Wales to develop supplementary educational resources on AI ethics and machine learning. Day of AI Australia reached 85,000 students at 400-plus secondary schools this year, sparking curiosity in the next generation of AI experts.

      The interest in AI is accelerating as fast as the technology is being developed. Day of AI offers a unique opportunity for K-12 students to shape our world’s digital future and their own.

      “I hope that some of you will decide to be part of this bigger effort to help us figure out the best possible answers to questions that are raised by AI,” Kornbluth told students at the Edward M. Kennedy Institute. “We’re counting on you, the next generation, to learn how AI works and help make sure it’s for everyone.” More