Transistors, the building blocks of modern electronics, are typically made of silicon. Because it’s a semiconductor, this material can control the flow of electricity in a circuit. But silicon has fundamental physical limits that restrict how compact and energy-efficient a transistor can be.

MIT researchers have now replaced silicon with a magnetic semiconductor, creating a magnetic transistor that could enable smaller, faster, and more energy-efficient circuits. The material’s magnetism strongly influences its electronic behavior, leading to more efficient control of the flow of electricity. 

The team used a novel magnetic material and an optimization process that reduces the material’s defects, which boosts the transistor’s performance.

The material’s unique magnetic properties also allow for transistors with built-in memory, which would simplify circuit design and unlock new applications for high-performance electronics.

“People have known about magnets for thousands of years, but there are very limited ways to incorporate magnetism into electronics. We have shown a new way to efficiently utilize magnetism that opens up a lot of possibilities for future applications and research,” says Chung-Tao Chou, an MIT graduate student in the departments of Electrical Engineering and Computer Science (EECS) and Physics, and co-lead author of a paper on this advance.

Chou is joined on the paper by co-lead author Eugene Park, a graduate student in the Department of Materials Science and Engineering (DMSE); Julian Klein, a DMSE research scientist; Josep Ingla-Aynes, a postdoc in the MIT Plasma Science and Fusion Center; Jagadeesh S. Moodera, a senior research scientist in the Department of Physics; and senior authors Frances Ross, TDK Professor in DMSE; and Luqiao Liu, an associate professor in EECS, and a member of the Research Laboratory of Electronics; as well as others at the University of Chemistry and Technology in Prague. The paper appears today in Physical Review Letters.

Overcoming the limits

In an electronic device, silicon semiconductor transistors act like tiny light switches that turn a circuit on and off, or amplify weak signals in a communication system. They do this using a small input voltage.

But a fundamental physical limit of silicon semiconductors prevents a transistor from operating below a certain voltage, which hinders its energy efficiency.

To make more efficient electronics, researchers have spent decades working toward magnetic transistors that utilize electron spin to control the flow of electricity. Electron spin is a fundamental property that enables electrons to behave like tiny magnets.

So far, scientists have mostly been limited to using certain magnetic materials. These lack the favorable electronic properties of semiconductors, constraining device performance.

“In this work, we combine magnetism and semiconductor physics to realize useful spintronic devices,” Liu says.

The researchers replace the silicon in the surface layer of a transistor with chromium sulfur bromide, a two-dimensional material that acts as a magnetic semiconductor.

Due to the material’s structure, researchers can switch between two magnetic states very cleanly. This makes it ideal for use in a transistor that smoothly switches between “on” and “off.”

“One of the biggest challenges we faced was finding the right material. We tried many other materials that didn’t work,” Chou says.

They discovered that changing these magnetic states modifies the material’s electronic properties, enabling low-energy operation. And unlike many other 2D materials, chromium sulfur bromide remains stable in air.

To make a transistor, the researchers pattern electrodes onto a silicon substrate, then carefully align and transfer the 2D material on top. They use tape to pick up a tiny piece of material, only a few tens of nanometers thick, and place it onto the substrate.

“A lot of researchers will use solvents or glue to do the transfer, but transistors require a very clean surface. We eliminate all those risks by simplifying this step,” Chou says.

Leveraging magnetism

This lack of contamination enables their device to outperform existing magnetic transistors. Most others can only create a weak magnetic effect, changing the flow of current by a few percent or less. Their new transistor can switch or amplify the electric current by a factor of 10.

They use an external magnetic field to change the magnetic state of the material, switching the transistor using significantly less energy than would usually be required.

The material also allows them to control the magnetic states with electric current. This is important because engineers cannot apply magnetic fields to individual transistors in an electronic device. They need to control each one electrically.

The material’s magnetic properties could also enable transistors with built-in memory, simplifying the design of logic or memory circuits.

A typical memory device has a magnetic cell to store information and a transistor to read it out. Their method can combine both into one magnetic transistor.

“Now, not only are transistors turning on and off, they are also remembering information. And because we can switch the transistor with greater magnitude, the signal is much stronger so we can read out the information faster, and in a much more reliable way,” Liu says.

Building on this demonstration, the researchers plan to further study the use of electrical current to control the device. They are also working to make their method scalable so they can fabricate arrays of transistors.

This research was supported, in part, by the Semiconductor Research Corporation, the U.S. Defense Advanced Research Projects Agency (DARPA), the U.S. National Science Foundation (NSF), the U.S. Department of Energy, the U.S. Army Research Office, and the Czech Ministry of Education, Youth, and Sports. The work was partially carried out at the MIT.nano facilities.

Nature Climate Change, Published online: 14 October 2026; doi:10.1038/s41558-026-02764-0

Climate citizens’ assemblies are gaining traction worldwide as a way to involve the public in climate governance. Now a study demonstrates that although these assemblies propose more ambitious recommendations than existing climate policy, these recommendations vary across contexts and have limited impact on policy decisions.

Nature Climate Change, Published online: 14 October 2026; doi:10.1038/s41558-026-02777-9

As the Rio Conventions mature from negotiating commitments towards delivering them, strengthening implementation has become an urgent priority. We argue for greater cross-convention learning within the context of institutional architecture to accelerate progress on climate, biodiversity and land degradation.

Nature Climate Change, Published online: 14 October 2026; doi:10.1038/s41558-026-02780-0

Species hybridization belongs on the climate change agenda

Nature Climate Change, Published online: 14 October 2026; doi:10.1038/s41558-026-02755-1

Deliberative citizen participation, such as climate assemblies, has been promoted in climate governance. This study finds that, although assemblies proposed more ambitious recommendations than existing climate policy, these recommendations rarely translated into actual policy decisions.

In an extremely disappointing ruling, a California trial court dismissed SIREN v. San Jose, our case challenging the city of San Jose’s warrantless searches of its vast stores of automated license plate reader (ALPR) data. EFF and the ACLU of Northern California represent SIREN and CAIR California, two non-profits that serve San Jose residents, in this case.

Make no mistake: We believe this ruling is wrong on the law, and we will appeal. The ruling ignores the importance of landmark rulings from the U.S. Supreme Court regarding the invasiveness of aggregating collected data on an individual over time, including one issued just months ago. It also severely underestimates the harm that ALPRs cause, in San Jose and around the country. 

San Jose’s ALPR surveillance system is inescapable. It blankets the city’s streets in nearly five hundred cameras that continuously photograph every car that passes by and retains the collected data for a month or longer. In our briefs, we argued that law enforcement officers who warrantlessly search the resulting ALPR database are violating the California Constitution’s ban on unreasonable searches and its guarantee of privacy. The court disagreed, explaining that based on one California appeals court case involving individual streetlight cameras, people do not have a reasonable expectation of privacy when driving on a public road. This is wrong. Networked ALPRs are not individual streetlight cameras. Their net effect of tracking and mapping cars as they travel reveals patterns of life, intimate relationships, and much more.

Fortunately, there are signs that the tide is turning against ALPRs in the courts. Just a day before the ruling in our case, a federal district court in Oklahoma called ALPRs “a type of indiscriminate mass surveillance” and decided that a law enforcement officer’s warrantless search of ALPR data violated the Fourth Amendment. The officer was observing traffic on an Oklahoma highway when he saw a woman driving a car with California plates. According to the court order, the officer began following the woman “for no apparent reason” other than her out of state plates. While following her, the officer decided to run the woman’s license plate number through Flock’s ALPR system – again, with no apparent reason other than her California plates. The Flock search returned at least 30 days of data, allowing the officer to track the car across at least three states, over the span of a month, from a single search.

The facts of this case demonstrate how ALPRs allow law enforcement to grab a breathtakingly vast sweep of information about a car (and the driver within) with no more effort than a Google search. It’s true that when a person drives on public roads, they can be observed, including by police. But as the Supreme Court has explained, we don’t expect law enforcement to be able to secretly track and store every movement our cars while we’re driving. The federal court in the Oklahoma case aptly illustrated this difference in societal expectations:

We might reasonably expect our friends and family to tell us something like: “Hey, I saw you out driving by the store last week.” But we do not expect people we know—let alone strangers, and especially not law enforcement—to randomly approach us to say: “Hey, I have been following your car for the last 30 days, and here is a detailed log of every place your vehicle has been with supporting photographic evidence. I am also going to share this information with law enforcement throughout the country so they know your whereabouts, too.

This decision is the first of its kind, and EFF will continue working to ensure that it is the first of many. Outside the courts, we’ve seen people across the country step up to reject ALPRs at the state and local level. EFF will continue challenging this technology on every front as well.

Related Cases: SIREN and CAIR-CA v. San Jose

When we communicate online today – from your personal emails and DMs to secure international commerce – we usually do so with encryption. Encryption converts readable data into unreadable gibberish to protect our privacy and security. This didn’t just happen organically. Three decades ago, the U.S government treated encryption like a weapon, and it took some unlikely heroes to set it free: a grad student, a junior lawyer, and a fledgling digital rights group who sued the federal government. 

The ruling in Bernstein v. Department of Justice held that code is speech and so is protected by the First Amendment – a precedent that underpins the internet as we know it today. This landmark case was led by Cindy Cohn, then a young pro bono lawyer working on behalf of EFF, who went on to become EFF’s legal director and then executive director. 

Welcome to the second episode of “Privacy’s Defenders,” a podcast about the people – lawyers, journalists, hackers, and others – who’ve fought to secure your digital liberties since before most people even knew what the internet was. 

%3Ciframe%20height%3D%2252px%22%20width%3D%22100%25%22%20frameborder%3D%22no%22%20scrolling%3D%22no%22%20seamless%3D%22%22%20src%3D%22https%3A%2F%2Fplayer.simplecast.com%2F91542147-6839-46fe-a813-73eb7a5c683c%3Fdark%3Dtrue%26amp%3Bcolor%3D000000%22%20allow%3D%22autoplay%22%3E%3C%2Fiframe%3E Privacy info. This embed will serve content from simplecast.com

   

(You can also find this episode on the Internet Archive and on YouTube.)

In this episode, Cindy – who left EFF in June – speaks with Dan Bernstein, who was a Cal Berkeley grad student when he developed a simple encryption algorithm called “Snuffle.” Because federal law classified encryption as a war munition, publishing Snuffle meant submitting it to the government for review, getting a license as an arms dealer, and being granted a license the government had no intention of granting. Bernstein felt this violated his free-speech rights and in 1995 he sued, represented by Cindy working with EFF. 

Cindy also talks with Tony Coppolino, the Justice Department lawyer she battled in court – who admits she intimidated him from their very first phone call, and who offers a surprising perspective on the case all these years later. 

The “Privacy’s Defenders” podcast (new episodes drop every other Tuesday!) is a follow-up to Cindy’s book, “Privacy’s Defender: My Thirty-Year Fight Against Digital Surveillance,” bringing to life pivotal moments in the voices of those who fought for your rights. Sales of “Privacy’s Defender” benefit EFF, so pick up your copy today!

Joanne Elgart Jennings co-produced and created this podcast.   

Jarod Sport co-produced, mixed, and mastered it.   

Corinne Ruff is our story editor. 

We had additional help from Rachel Estabrook and Alison Broverman. 

The original music was composed and performed by Nat Keefe of Hot Buttered Rum with Ben Andrews on the fiddle.

MIT engineers have developed a new way to program natural killer (NK) immune cells to target cancerous T cells or T cells that have become autoreactive, leading to diseases such as lymphoma and autoimmune hepatitis. 

Using their new technique, the researchers can reprogram NK cells to target diseased T cells without ever removing the NK cells from the patient’s body. Instead, they use lipid nanoparticles to deliver messenger RNA directly to NK cells. These mRNA molecules encode proteins that allow the NK cells to seek and destroy the dysfunctional T cells.

Known as CAR NK cells, these cells could be deployed against a variety of diseases. The MIT team’s new approach could bypass one of the major obstacles to using these cells, which is the time and expense of manufacturing them outside the body.

“The manufacturing challenges with CAR NK cells are significant. The idea here is you can deliver a nanoparticle that will modify your own NK cells with a CAR construct and teach them to attack tumor cells,” says Daniel Anderson, a professor in MIT’s Department of Chemical Engineering and a member of MIT’s Koch Institute for Integrative Cancer Research and Institute for Medical Engineering and Science.

Anderson is the senior author of the study, which appears today in Nature Biotechnology. The paper’s lead authors are MIT postdoc Yuang Chen and MIT graduate students Julia Monkovic and Haseeb Mughal. Robert Langer, the David H. Koch Institute Professor at MIT, is also an author.

Easier reprogramming

Over the past decade, the U.S. Food and Drug Administration has approved seven new cancer treatments based on engineered T cells called chimeric antigen receptor (CAR) T cells. Chimeric antigen receptors are proteins that can be embedded into T cells, allowing them to detect a target antigen, such as a cancer protein. When the target is detected, the T cell becomes activated and destroys the target cell.

This approach has had great success in treating blood cancers, primarily those that originate from B cells, including several types of leukemia, lymphoma, and multiple myeloma. 

To make CAR T cells, doctors take a blood sample from the patient. The sample is sent to a lab where the T cells are isolated and then engineered to express the CAR protein. When enough CAR T cells have been generated, they are shipped back to the hospital and infused into the patient. 

In recent years, scientists have begun using a similar strategy to create CAR NK cells. One potential advantage of CAR NK cells over CAR T cells is that they could be used to kill diseased T cells. Using CAR T cells to treat T cell diseases often doesn’t work well because T cells that are engineered to target T cell proteins may end up killing each other, in addition to the diseased T cells. That issue doesn’t arise when using NK cells to target T cells.

“NK cells can treat these T cell malignancies — not only T cell cancer, but also T cell autoimmune diseases,” Chen says.

However, manufacturing large quantities of CAR NK cells poses many of the same difficulties as generating CAR T cells. To simplify the process, the MIT team wanted to come up with a way to generate CAR NK cells “in vivo” — that is, in the patient’s own body, without having to remove any cells.

“If a patient can just get an infusion of nanoparticles, it would dramatically simplify the process and reduce costs,” Anderson says.

Currently, there are no FDA-approved CAR NK cell therapies, but many researchers are working on developing them to treat cancer or autoimmune disorders. 

To generate these cells, the MIT team designed lipid nanoparticles (LNPs) that can deliver an mRNA payload. These strands of mRNA encode a CAR that can be targeted to specific cell types. For example, they could deliver a CAR that targets CD19, a protein found on B cells, or CD3, a protein found on autoreactive T cells. 

The particles are coated with antibody fragments that bind to receptors found on the surface of NK cells, to ensure they reach the correct targets.

Targeting dysfunctional T cells

After these particles were infused into mice, the researchers found that they could successfully reprogram about 80 percent of the targeted NK cells. The researchers then tested the particles’ potential to treat cancer and autoimmune hepatitis, which is caused by autoreactive T cells. 

In a mouse model of an aggressive form of melanoma, three of the five mice that received LNPs that reprogrammed their NK cells to target the cancer cells went into complete remission.

The researchers also saw significant tumor destruction when they used the LNPs to treat T cell lymphoma in a humanized mouse model, created when mice receive transfusions of human blood cells, allowing them to transiently generate a human-like immune system.

In these mice, tumors were eradicated after five injections of the reprogramming LNPs. This result was similar to what the researchers saw when they treated mice with CAR NK cells that were generated using the conventional approach — removing NK cells, reprogramming them, and returning them to the mice.

Lastly, the researchers demonstrated that their LNPs could generate CAR NK cells that target autoreactive T cells. For this application, they studied mice with autoimmune hepatitis, in which T cells attack hepatocytes in the liver. They found that in the treated mice, the autoreactive T cells were destroyed, and liver damage healed. These effects were seen after just one injection of the LNPs.

“This study is an excellent example of the power of nano delivery systems and their ability to potentially treat cancer and other diseases,” Langer says. 

The researchers hope that these kinds of engineered NK cells could be used to treat a variety of autoimmune disorders caused by dysfunctional T cells, including multiple sclerosis and rheumatoid arthritis. 

The research was funded by Sanofi, the Marble Center for Cancer Nanomedicine, and a Koch Institute Support (core) Grant from the National Cancer Institute.

When government officials craft policies, there is often a comment period for public feedback. Lawmakers have long had to sort through fake feedback that is mass-produced in an effort to sway policy, but they’ve generally gotten used to detecting it. With, artificial intelligence, however, people can submit realistic-seeming comments, which are harder to dismiss as being fabrications with no person behind them. That’s just one way AI can be used to generate text and statements, in civic conversations, for which no one can be found to be answerable.

This issue, among others, has caught the attention of Deb Roy, professor of media arts and sciences at MIT and director of the MIT Center for Constructive Communication (CCC). In a new essay published in the Bulletin of the Atomic Scientists, titled, “Who stands behind the words?,” Roy calls for a renewed emphasis on responsibility in communication, asserting that even when AI is used to craft text, there needs to be accountability and “answerability.”

Building better group dialogues to produce more public trust is a core part of the work of CCC. The group, along with Cortico, the closely affiliated nonprofit Roy co-founded, has helped facilitate group discussions on important issues in many situations — including civic meetings, schools, deliberative assemblies, and private organizations — and used tech tools, including AI, to help find themes among comments, and more. But the center also designs this process so that participants can check and override the tech-based output at each key step. Ultimately, a person is responsible for every public comment. MIT News spoke to Roy about the essay and the work of the center. 

Q: You’ve identified this problem about the lack of accountability behind words that are generated by AI. When did you really first notice this?

A: It came into focus when Chat-GPT [which is powered by a large language model, or LLM] launched. As for my own history with language models, my PhD work explored what we might now call PLMs — Puny Language Models — so I’m quite familiar with language models and have tracked the field’s rapid evolution. But Chat-GPT turned a corner. Two things changed at the same time: the depth of the model and its knowledge, and the way you could interact with it. 

I became obsessed with trying to find the limits of what it could do. And I felt that no matter how hard I tried to stretch my arms around it, I couldn’t. I built my tenure case at MIT on language grounding — the idea that it’s not enough for an AI system to just process lots of words and other symbols. I believed that to understand what words mean, you actually need a physical body and life experiences as part of the process. So I revisited the philosophy-of-AI literature I had once been steeped in, which asks what fundamentally distinguishes the kind of system that large language models exemplify, in extraordinarily advanced form, from the kind of processing we humans engage in. I gave several presentations to my own graduate students trying to make the case that, even though AI seems so intelligent, it’s actually different in kind — and I could not convince them. 

And I thought, I know the difference, but I’m having trouble convincing even myself of what it is. And that led me to ask, “Wait a minute: Is there someone or something that stands behind the words, a human responsible for what is being said?” That’s the thing this extraordinary new language machine doesn’t have. 

Whether these systems genuinely understand language is actively debated. But even if you grant them all the comprehension you like, they still lack standing. The buck can’t stop at a thing, a software system, with nothing to lose.

Q: The Bulletin piece has these interesting examples of civic feedback forums where it looks like there are real people saying things, and instead you have a barrage of comments from AI. How did you find some of these other examples in society where things go off the rails in this way? 

A: After the release of ChatGPT, I started hearing a concern from people inside government who review public comments on proposed rules: a suspicion that not all of the comments were written by humans.

My reaction was: That’s going to delegitimize this channel for public feedback. That was several years ago, but everyone now knows this is happening. Public comment is a pillar of democracy. You don’t just put a new rule in place. People need to have a voice and feel like they’ve been heard before a rule is imposed on them. If you skip that step, people don’t accept rules as legitimate. That’s why that process is baked into how America works. And that pillar just cracked, and by now, in my mind, it’s fallen over. Has anyone noticed? My sense is the people on the receiving end of these comments have quietly adjusted the weight they give to public comments. It was never perfect, but boy, now much of its value is being swept away. 

I open my essay with this example: In 2017, the Federal Communications Commission received more than 22 million public comments on its proposal to repeal net neutrality rules, and the New York attorney general later found that nearly 18 million of them were fake. As I write in the essay, “That fraud was caught because it left fingerprints: templated text, duplicated phrasing.” But large language models erase the fingerprints. Now every comment can be fluent and different, and reviewers can no longer tell which ones express views that real people formed and stand behind.

If you have enough of the stuff that’s fake — words that no one with a stake actually stands behind — it desensitizes you to what’s real. That filters back to the public, and people realize: If I take the time to express myself, they’re not even listening any more.

Q: Could you say a little bit more about your point that we need people with “standing,” who will take “accountability” for all pieces of text, even when those bits of text are generated by AI? 

A: In the legal system, standing is a formal idea: sometimes a case isn’t heard because the people bringing it don’t have standing. But informally we use that term all the time. I’m not trying to formalize standing in everyday life. Instead I’m asking:  What is the informal sense of the term, borrowed from the legal one, that we need to pay more attention to now? Here in New England, consider the open town meeting: The person who stands up to speak is generally expected to have standing, as someone from that town with a stake in what gets decided. And if it’s a stranger who drove from across the state, or from out of state, everyone’s like: Wait a minute, who is that? They’re not from around here. In general, there’s just enough friction and it’s costly enough to show up somewhere you don’t actually have standing, that it doesn’t happen much.

Now LLMs and the current digital networked environment collapse those boundaries. We always took for granted that if someone has a voice, it’s because they have standing. They have some basis to be heard. We need to pay attention to this, and really consider how to design systems so that the people with standing are the ones who get heard. 

The other idea I tried to develop is “answerability.” It isn’t formalized in law, but it’s baked into the legal process. If you have standing to give testimony, there you are, ready for cross-examination. You have to be able to answer for what you’re saying. And if you’re making a specific accusation about someone, you have to be willing to back it with facts. Standing and answerability have to travel together: The right to be heard comes with the obligation to answer for what you say.

That doesn’t mean everyone has to attach their name to everything. I write in the Bulletin essay, “Privacy and answerability aren’t opposites. … An institution can verify a person and stand behind their words without exposing them.” To voice a view, you only need to show that a distinct, eligible person is speaking. An accusation asks more: Someone trusted, like a reporter, has to be able to know who is speaking. As I say: “Disclosure obligations should scale with power, and identity protections with vulnerability.”

None of this means AI can’t help. AI can do a lot of the work inside the chain of accountability — drafting, summarizing, finding patterns. If someone with a stake in a rule uses AI to draft a comment, adopts it as their own, and is ready to answer for it, that’s legitimate, in this context. What AI can’t do is anchor the chain. There has to be a person at the end who stands behind the words.

In the essay I lay out four design principles for building that in: “attributable authorship,” a “decomposed and inspectable process,” the use of “provenance as infrastructure,” and the need to “widen standing rather than concentrating it.” As I write, the “animating rule is that autonomy is permitted while unaccountability is not.” And the metric that matters most isn’t the efficiency gained by removing humans, but the number of people AI places into roles where they can answer for what they do.

Q: There is a phrase in the documents of the Center for Constructive Communication, that we need things to move “at the speed of trust,” not at the “speed of tech.” And that implies really thinking about building up these systems. Could you just say a little more about what that phrase means to you?

A: I learned that phrase when I was in Appleton, Wisconsin, with Katherine Cramer [of the University of Wisconsin], a longtime collaborator, talking with community organizers who were running “Dialogue across Divides” conversations there. They had hundreds of people involved. I thought I was developing technology tools with exactly that same purpose, and was so excited to see it. And I asked one of the people who ran that organization, “How fast did you scale this?” And he paused, and then he said, “At the speed of trust.” 

And I took that to mean “slow.” Then I realized he was saying: For you, slow, because you haven’t yet earned our trust. And I’ve since learned that when you do have trust, things can move fast. So bringing in technology is really a process of engagement. It doesn’t work to say, “Trust us, we’re doing this because we think it’s for your own good.” People will turn to someone they already trust and ask, “Is this good for us?” And if that person says “Yes,” things can move fast.

Look at what’s happening at the intersection of AI and society: The speed of AI and the speed of democracy are running on different clocks. Talk to people who work in democratic practice and they say, “AI must slow down, because democracy can’t move that fast.” Talk to people in AI and they say, “AI cannot slow down, democracy needs to speed up.” If we can’t get these two time scales in sync, we’re headed for a breakway situation, where AI gets deployed faster than democratic processes can respond, and decisions get made without the public. That’s starting to happen right now. 

Q: We need people actively doing things to build dialogue and figure out how tech tools can interact with that. At the Center for Constructive Communication, you’ve done a few iterations of the center’s Real Talk initiatives to build civic dialogues, as well as the Youth Voices Initiative in school settings, and currently you’re working on the New Social Forms project. Could you say a few words about them? 

A: The Real Talk effort represents the longest-standing thread in this work. A huge emphasis of our work has been developing better ways to listen to one another. We create a context that is always small — small is beautiful here — where people are willing to share authentically. And we have the consent architecture and the technology to reveal the larger patterns, and then share them. We’ve done this with hundreds of communities around the country. And closer to home, we’ve brought the same approach to our campus here at MIT through the realtalk@MIT program, with support from the Office of the President and the Office of the Provost, to help our community build a culture around dialogue and listening. 

The second thing I’d emphasize is that we’ve been doing more and more work on deliberative processes and citizen assemblies, and on how to make them more accessible. What if a group of high schoolers says, “We have a real problem with our cellphone policy?” Suppose you want to have an assembly that brings students, teachers, and administrators together, not just to listen to people’s concerns but to make policy recommendations. So we did that. The center worked with a high school in New York City, where technology helped people reveal their preferences and differences and listen to each other.

We’re also building answerability into the technology. A prototype called VoiceTrace, developed by PhD student Cassandra Overney in our group, links every output statement — a summary of what was heard in a listening process, or a recommendation coming out of a deliberation — to the specific voices behind it, so any claim can be traced back to the conversations it came from.

The New Social Forms project pertains to a very interesting pattern emerging in workplaces around the world, certainly the ones we’re connected to. AI is an extraordinary tool for individual empowerment, but in the words of one of our collaborators at the Google Experience Institute, people are tunneling. They go deep, using AI to develop refined ideas, but when they surface, their ideas have diverged from their teammates’. So groups and teams trying to work together with AI, there’s a human coordination problem.

We’re going to expand the initial work we’ve started with Google because there’s a lot of interest in collective communication, trust, and interaction among people trying to work together. 

So is that a civic context? It’s a workplace, but workplaces are civic spaces, too. They govern people’s daily lives, they’re where many of us build civic skills and learn to cooperate across difference, and there’s a long tradition of civic life rooted in shared work. We’re all humans trying to interact with each other. These are the same issues. Justice Louis Brandeis once used the phrase “industrial democracy” to capture this. When workplaces lacked certain kinds of civic processes and civility — two interestingly related terms — labor disputes used to turn violent. Procedural justice, mediators, and people hearing one another are just as necessary in the workplace. In the end, it’s all about human beings. Hearing the humanity in one another is what democracy depends on, and it’s just as necessary for communities and organizations to function.

The Sierra Nevada mountain range in California is as stunning as it is diverse, with storms from the Pacific Ocean dumping rain and snow on the range’s western slopes while arid conditions mark much of its eastern face. David Des Marais, MIT’s Amgen Career Development Associate Professor, knows the mountains well. His childhood in San Francisco was filled with hiking and camping excursions throughout the range.

At some point during those trips, he started wondering about one of the few constants of the landscape: the presence of plants. How were plants able to thrive in all those conditions? He turned the question into a career.

Des Marais, who directs the Parsons Laboratory in the Department of Civil and Environmental Engineering, studies how plants interact with their environment. The research spans molecules and mountain ranges, exploring everything from how individual genes change a plant’s ability to grow to how climate change will impact populations of red oak trees across the eastern U.S. His work also considers how evolutionary forces act on plants to change populations over time.

Plants are central to his lab, but Des Marais sees them as a window into all living things. He’s even quick to credit the health of his houseplants and garden to his wife, an evolutionary biologist at Harvard University.

“Understanding why life is so diverse is fascinating to me,” Des Marais says. “Understanding how different organisms, from bacteria to dinosaurs, have figured out how to interact with their challenging environment and optimize their fitness is inherently interesting. Why plants in particular? As a geneticist and a physiologist, plants are compelling experimental systems. If I have a theory about gene X causing function Y, I can go into the lab and delete gene X from this species and put it into that species and test function directly. It’s a powerful approach.”

Des Marais does not spend all his days in a lab. In addition to directing the Parsons Laboratory, he teaches four classes at MIT and has two sons who are active in baseball and theater. He welcomes these responsibilities.

At MIT especially, he embraces service.

“The only reason MIT works is because there are people willing to sacrifice some of their research to keep the place running,” Des Marais says. “One of the things I like about academia is that there’s sort of an institutional memory, and you try to honor the legacy of where you’ve been while you shape the future.”

From California to MIT

Des Marais grew up near Stanford University as well as near facilities for NASA and the U.S. Geological Survey, which meant there were always plenty of scientists and engineers around. His mother was a teacher, and his father was a geochemist with a knack for pointing out that the landscape around them was the result of geological processes dating back millions of years — a habit Des Marais admits he didn’t like at the time but that, in hindsight, influenced his thinking.

“I’m pretty sure that got into my brain, especially the idea that what looks static often comes about because of processes, and we can study those processes,” he says.

Des Marais studied integrative biology as an undergraduate at the University of California at Berkeley. He completed his PhD at Duke University around plant genetics.

“There’s a whole series of outdoor events, from the Boy Scouts through college, that made me start to think about the challenges that plants face living in these stressful environments,” he says. “That drove me to plant science and environmental science.”

In a long postdoc at the University of Texas at Austin, Des Marais learned to conduct experiments teasing out the effect of specific genes as he studied how they changed a model plant’s relationship with water.

Des Marais came to Boston primarily for personal reasons: He and his wife, who was also a postdoc at UT Austin, entered the job market at the same time. After some awkward moments competing for the same jobs, his wife landed a tenure-track position at Harvard University. Shortly after, he joined Harvard as a staff scientist.

In 2017, Des Marais discovered MIT’s Department of Civil and Environmental Engineering was hiring a plant ecologist.

“I don’t even think of myself as a plant ecologist, but I applied on a whim and they were interested,” Des Marais says. “I do a lot around plant water relations, and I joke that there are all these hydrologists in the department who study how water moves through the soil and into the atmosphere through these magical pipes. The magical pipes are plants, which play an important role in the water cycle. I realized a ton of people at MIT were studying that phenomenon at regional or global scales, but no one really studied how or why plants move water in the first place.”

Today Des Marais’ lab work can be broken into two broad categories. The first is centered around how plants function, including their relationship with environmental factors like water, temperature, and nutrients. Des Marais says some of his most impactful studies link specific molecules to how a plant functions in a given ecosystem.

The second centers around fundamental questions in plant evolution, what Des Marais describes as how plants “make decisions” about when to grow, reproduce, germinate, and more.

One current research project looks at how climate change will impact red oak trees, an important species and carbon sink. He is also examining climate change’s impact on plants that are important for food systems.

“We know that climate change is impacting plant function, and it’s impacting plant nutrition, and that impacts human nutrition,” Des Marais says. “Climate change is going to affect where we can grow which plants efficiently and how we can get them where they need to be eaten. All that stuff is critically important for humans.”

Understanding plants for the planet

Des Marais says it’s been fascinating working with experts in environmental chemistry and fluid mechanics as part of the Parsons Laboratory. He sees his role as director as being primarily about fostering community.

“The students are great,” Des Marais says. “It’s a funky old building, but we all work well together. We try to make sure everyone feels comfortable and welcome in the space.”

Even if he can’t take credit for his houseplants, Des Marais appreciates the vital role plants play for the planet.

“Plants are the foundation of the food chain, and there’s no way to get around that,” Des Marais says. “The efficiency of plant photosynthesis directly impacts our nutrition, and it impacts what we can feed the animals that we eat. It affects carbon cycling and water cycling — put simply, plant biology matters.”

Nature Climate Change, Published online: 13 October 2026; doi:10.1038/s41558-026-02751-5

Achieving climate neutrality requires policies perceived as fair, with equity both between and within income groups. Here researchers evaluate the equity implications of different European Union climate policy packages and show how a mixed policy design can balance trade-offs between two equity dimensions.

In September, hackers from a group called ShinyHunters announced that they stole a trove of FBI data about its own agents. It was an intelligence disaster.

Last week, the FBI arrested (alternate link) someone associated with that crime.

Robert Hall PhD ’67 and Michael Woodford PhD ’83, scholars who both earned their doctorates at MIT, have been awarded the 2026 Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel.

Hall, a professor at Stanford University, and Woodford, a professor at Columbia University, were recognized for work that helped revitalize ideas about how government policy can spur growth to help end economic downturns. The Nobel citation describes their research as contributing to “new macroeconomic models that have significantly improved our ability to implement effective stabilisation policy.”

Both scholars helped integrate microeconomic analysis into macroeconomic models. In Hall’s case, the Nobel committee particularly cited research he conducted in the late 1970s shedding new light on economic expectations and household consumption. The committee also spotlighted Woodford’s construction of a comprehensive and influential macroeconomic model that was built on microeconomic foundations and introduced in his 2003 book, “Interest and Prices: Foundations of a Theory of Monetary Policy.” 

The work of both scholars helped update models for intervention during economic crises, based on the ideas of John Maynard Keynes, which had worked many times in the 20th century but encountered newfound difficulties adapting to the conditions of the 1970s. So-called New Keynesian models used for economic stabilization today are a result of both economists’ research, the citation noted. 

Hall is the Robert and Carole McNeil Joint Senior Fellow at the Hoover Institution and Professor in the Department of Economics at Stanford University. He received his BA in economics from the University of California at Berkeley before earning his PhD from MIT.

Woodford is the the John Bates Clark Professor of  Political Economy at Columbia University. He received a BA from the University of Chicago and a JD from Yale University Law School prior to receiving his PhD from MIT. 

Remarkably, Hall becomes the fifth former doctoral student principally advised by MIT economist Robert M. Solow to earn the Nobel Prize in economics. The others are George Akerlof PhD ’66, Peter Diamond PhD ’63, William Nordhaus PhD ’67, and Joseph Stiglitz PhD ’67, all of whom had Solow as their principal advisor in MIT’s graduate program. Additionally, MIT professor of biology H. Robert Horvitz ’68, a Nobel laureate in 2002 in the category of physiology or medicine, wrote his undergraduate thesis in economics under the direction of Solow. In 1987, Solow received the Nobel Prize himself. 

Woodford did his doctoral work under the primary supervision of Timothy Kehoe, now of the University of Minnesota — although Woodford does thank Solow in the first paragraph of his doctoral thesis, for helping him “distinguish important problems from exercises of merely technical interest.”

There are now 17 MIT alumni who have won the Nobel Prize in economics. Previously, 10 people have won the award while serving on the MIT faculty, and eight former faculty have also been named recipients.

Nature Climate Change, Published online: 12 October 2026; doi:10.1038/s41558-026-02771-1

Selecting climate solutions creates new institutional authority

In the past two years, the federal government has unlawfully consolidated data exposing our private information. 

This consolidation has been chaotic but generally came in three rolling waves: It started with DOGE, moved to agency-to-agency data sharing with ICE, and then attempted data-driven purges of state voter rolls.

We all deserve to live in a world where the data we use to pay our taxes, receive benefits, and vote is not combined and weaponized against us. The amalgamation of data leads to mistakes, abuses, and a lack of trust in institutions meant to protect us. Overall, it can chill our participation in society. This is particularly true for groups disfavored by this administration—especially immigrants and protesters.

Congress highlighted similar abuses—including the creation of enemies lists and snooping on activists and federal employees—following the McCarthy and Watergate eras. And the increasing use of computers to magnify those harms led Congress to pass a slate of protections like the federal Privacy Act of 1974.

The good news is that many people have stepped forward to resist the federal government’s unprecedented and unlawful data consolidations. Many groups, including EFF, have filed lawsuits to enforce our data privacy laws, and many states have, too. Legislators at the federal and state levels have worked to expose and oppose these surveillance programs. And many people have protested for their right to data privacy.

Existing data privacy protections have been essential in the past two years, but they can be improved. This should include: narrowing loopholes and increasing enforcement in existing laws, limiting the government’s purchase of data on the commercial market, and passing a comprehensive consumer privacy law.

Data Consolidation by DOGE

Starting on January 20, 2025, President Trump created DOGE—essentially renaming an existing agency originally meant to modernize government technology. Rather than engage in modernization, DOGE quickly obtained high-level access to sensitive databases across the government that store millions of people’s personal records—including at the Office of Personnel Management (OPM), the Social Security Administration, and the Treasury Department.

DOGE was staffed with people with little government or cybersecurity knowledge and who often had conflicts of interest. DOGE’s early aim was not always clear, aside from gaining “prompt access to all unclassified agency records” and the “sharing and consolidation” of those records.

The result? The indiscriminate firing of government employees and the decimation of important agencies that focused on consumer protection and foreign aid. It also resulted in clear misuses of data. For example, while working with DOGE at the Social Security Administration, one individual signed an outside agreement with an advocacy group with the aim of using SSA data to find evidence of alleged voter fraud and “overturn election results in certain States.”

DOGE’s data access and consolidation violated the federal Privacy Act, which limits the sharing and consolidation of government databases. Many groups stepped in to sue. For example, EFF and our co-counsel at Lex Lumina LLC and Democracy Defenders Fund, on behalf of two public employee unions (AFGE and AALJ), sued the OPM for unlawfully disclosing federal workers’ information to DOGE. After EFF and others secured early victories, the government sought to end the lawsuits by firing many DOGE agents and removing their access to records. A great deal of damage remains in need of a judicial remedy.

Data Consolidation by the Department of Homeland Security (DHS)

Even as DOGE’s influence diminished, federal agencies have attempted to share, compare, and seize large databases, in order to target immigrants. In some cases, they have succeeded. This happened with tax records at the IRS, Medicaid data from the Department of Health and Human Services (HHS), and public housing data from the Department of Housing and Urban Development. The Department of Agriculture also sought to collect databases regarding Supplemental Nutrition Assistance Programs (SNAP) from states.

Many groups have filed lawsuits to block this anti-immigrant-motivated data consolidation, alleging it violates privacy protection laws. EFF filed amicus briefs in support of two of these lawsuits: Centro de Trabajadores v. Bessent, which concerns IRS data; and California v. HHS, which concerns Medicaid data (and where we teamed up with EPIC and Protect Democracy). Most recently, states have stepped up to challenge the federal government’s attempted seizure, for immigration enforcement purposes, of state commercial driver’s license data held by the American Association of Motor Vehicle Administrators, a non-profit organization.

This data consolidation for immigration enforcement has also included government purchase of commercial products. This includes ICE’s purchase of commercial location data without a warrant, and its interest in “Big Data and Ad Tech providers.” ICE also has contracts with companies like Palantir, which help organize all the datasets the agency collects.

Data Consolidation for Voter Purges

The right to vote is fundamental to every democracy. That’s why EFF has long advocated for cybersecurity in voting systems, to make sure every vote is properly counted.

Voter purges are a longstanding threat to the right to vote. State and local officials regularly delete people from the voter registration rolls, often for bad reasons and without adequate notice. This has a disparate impact against people of color.

Now the federal government is trying to purge voters, too. To do so, it has consolidated our data in three ways. First, it is using an old data system called SAVE for a new purpose: checking voter eligibility. Second, it has seized voter information from states. Third, it has created a federal list of eligible voters.

As a direct result, people with a right to vote will be purged from voter rolls because of erroneous data. Others will be intimidated from voting or registering. And all registered voters suffer a violation of their data privacy rights: information collected for one purpose is being used against them for another purpose.

Expansion of SAVE

Since 1986, the federal government has operated SAVE, which stands for Systematic Alien Verification for Entitlements. It is not a database, but it facilitates easy access to databases. It is used to determine whether immigrants and naturalized citizens are eligible for various government benefits, such as food stamps.

In 2025, the federal government started using SAVE for a new purpose: checking voters’ eligibility. Further, SAVE now provides access to new databases and allows bulk searches. More than 60 million voters have been run through SAVE, and 21,000 were flagged as potential noncitizens who are ineligible to vote. Erroneous flags have caused purges of lawful voters – such as Anthony Nell.

A case called League of Women Voters v. DHS challenges this expansion of SAVE. The plaintiffs are represented by CREW, Democracy Forward, the Fair Elections Center, and EPIC. A federal judge held this program unlawful and set it aside. DHS appealed and asked for a stay of this order, and a federal appellate court denied the stay. Unfortunately, the U.S. Supreme Court granted the stay, exercising its controversial “shadow docket” authority by a six-to-three vote.

Federal employees in DHS’s “Fraud Detection and National Security Unit,” which ordinarily investigates alleged immigration fraud, have been re-assigned to examine voter eligibility. A whistleblower alleges that employees have been directed to go to state election agency websites, enter some of a voter’s personal information, and thereby access more of it. This may violate state laws requiring a person, before accessing a voter’s information, to attest they are that voter or have that voter’s authorization.

Federal Seizure of States’ Voter Information

Since 2025, the federal government has demanded that at least 48 states hand over their voter information. At least 16 states have complied. The federal government is running this information through SAVE, searching for voters to purge.

The federal government has sued 30 states for refusing to comply. So far, courts have dismissed 25 of these suits. There’s also a lawsuit against this data grab, titled Common Cause v. DOJ, brought by CREW, Protect Democracy, and the ACLU.

The New Federal Voter Eligibility List

In March 2026, President Trump issued an executive order requiring DHS to create a list of people who are U.S. citizens, aged 18 or older, and residents of the state. The order also requires DOJ to prosecute anyone, including state and local officials, who provides a ballot to a person who is not eligible to vote in federal elections.

In California v. Trump, 24 states allege that this executive order violates the Constitution’s separation of powers. A federal judge enjoined this program, and an appellate court denied a stay. But the U.S. Supreme Court by a six-to-three vote granted a stay, which allows the program to move forward. (By a seven-to-two vote, the Court denied a stay of an injunction against a different part of the same executive order, which concerned mail-in ballots.) Another legal challenge, titled EPIC v. USCIS, alleges that the new federal voter eligibility list violates the Privacy Act as well as the separation of powers.

Next Steps

It is encouraging to see so many people, groups, and states step forward to protect our data privacy from these unlawful waves of federal data consolidations. Still, more work remains. For example:

• The Privacy Act of 1974 has proven a critical bulwark. But after a half century, it could use a refresh. For example, Congress should close its loopholes and expand its enforceability.
• Law enforcement agencies must be prohibited from avoiding the Constitution’s warrant requirement by buying our personal data from brokers. For example, Congress should pass the “Fourth Amendment Is Not For Sale Act.”
• We need a comprehensive consumer data privacy law, among other reasons to reduce the flood of our personal data that corporations provide to law enforcement agencies. Legislators should check out EFF’s “privacy first” framework.

In the meantime, there’s no time like the present to practice surveillance self-defense, like using strong passwords and disabling your phone’s ad identification.

 

Related Cases: American Federation of Government Employees v. U.S. Office of Personnel Management

On Wednesday I spent a day fishing, on a small boat out of Gloucester, MA. We caught many cod (none of which we could keep), and a bunch of hake and mackerel (all of which we could keep). And…I caught a squid! Near as I can tell, it’s a longfin squid, sometimes called a Boston squid (Doryteuthis (Amerigo) pealeii).

That night I cooked it over a barbecue grill—hot and fast. Delicious.

EFF was thrilled to join organizers, advocates, and activists in the East Bay for the second annual Oakland Tech Week last week. We are grateful to our friends at MediaJustice and Upturn for inviting us co-present this all-day event, “Building Beyond Big Tech: Organizing Oakland’s Future”, on Sept. 30.  The event, hosted by the Kapor Center in downtown Oakland, offered a unique chance to spend time with people across The Town and the Bay Area working to create a better future for everyone.

“We’re at this truly consequential moment,” said EFF executive director Nicole Ozer, in her speech kicking off the day’s events. “We know that in this community’s work—and communities across the country—our ability to ensure that technology empowers rather than oppresses is fundamental to the future of countries, our livelihoods, and, literally, our lives.”

We also participated in a panel on the state of play in California, moderated by MediaJustice executive director Steven Renderos. Director of State Affairs Hayley Tsukayama joined reporter Khari Johnson of CalMatters and Crystal Zemero of People Over Billionaires to talk about the landscape at the state level. The day also included smaller conversations focused on building better tech and fine-tuning messaging, facilitated by our colleagues at MediaJustice.

Seeing the people—our neighbors—who are fighting back against surveillance in their communities was inspiring. They’re casting doubt on the claims large technology companies make about what’s happening in their neighborhoods. They’re speaking up at council meetings and rallies. They’re seeking changes that would give their workplaces and neighborhoods a better, safer relationship with technology. It was so important to come together in solidarity to compare notes, spend time together, find opportunities to support each other, and scheme together.

We can work together to build a future that works for everyday people. A better world is possible—and Oakland Tech Week was a great reminder that, all around us, folks are working together to tackle huge challenges.

“There are formidable forces,” Ozer said.  “But we can pierce the other side’s narrative of inevitability with our power of indignation. The future of AI and other technology is not written and we can work together to get it right.”

Whether you’re in Oakland or Aukland, consider this a renewed invitation to join us.

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EFF strongly condemns Turkey’s state-led discriminatory, oppressive attacks on feminist and LGBTQ+ organisations, media platforms, student groups, and rights defenders and activists within the country.

Since mid-September, access to the websites and social media accounts of a dozen organizations have been blocked by court order, while over 60 members and activists have been detained, their offices and homes raided, mobile phones, laptops and other digital devices seized, and judicial proceedings launched against them. 

These actions threaten the very existence of the LGBTQ+ organizations targeted, limiting their ability to carry out legitimate human rights work, deterring participation and support, and chilling the free speech rights of not just these groups, but any organization that even reports on LGBTQ+ oppression.

A little over a week ago, an Istanbul court shut down the website and social media accounts of T24, Turkey’s longest running independent digital news organization—which has covered government-backed campaigns against and earlier crackdowns on gay rights groups—alleging it had aired “LGBT propaganda” over the past year. 

It’s all part of Turkey’s efforts to portray LGBTQ+ groups and support networks for those living with HIV as criminal organizations that must be suppressed, purportedly to protect family values. Homosexuality is not illegal in Turkey (unlike Uganda, Nigeria, and Egypt, where it is criminalized), but LGBTQ+ organizations and activists have in recent years faced increased government oppression, including criminal proceedings on allegations related to obscenity and violations of Turkey’s Law on Associations, which regulates the activities of nonprofits.

In its new crackdown, the government is targeting LGBTQ+ groups’ websites and social media channels for alleged obscene posts accessible to children. Kaos GL, Turkey’s oldest gay rights organization, said investigations are being led by the Cyber Crimes Bureau of the Ankara Chief Public Prosecutor’s Office, which took members of its Board of Directors into custody, raided their homes, and searched the organization’s offices, where electronic devices were seized. 

According to Human Rights Watch, prosecutors in Istanbul said those targeted were suspected of “founding, leading, or being a member of a criminal organization,” as well as sex work and drug-related offenses. Publicly available law enforcement and judicial documents about the investigation reportedly don’t say which publications or posts are alleged to be obscene.

The prosecutor’s office launched an investigation of the organization and others under Article 226 of the Turkish Penal Code, which regulates the offense of “obscenity” (without clearly defining it), while the overall operation, dubbed “My Family is Safe” and launched as part of President Recep Tayyip Erdoğan’s “Decade of the Family” program, is being brought under Article 220 of the code. Justifying the crackdown by invoking family values and child safety suggests that the government is trying to enforce a moral code on society based on intolerance of and discrimination against LGBTQ+ people.

New Low for Turkey

Framing the activities of LGBTQ+ rights organizations as violations of organized crime provisions is a new low for Turkey, where free speech and press freedoms have long been under attack. The implication from these raids and investigations is that the organizations’ legitimate civil society work advocating for the rights of queer people—monitoring human rights violations, offering legal aid, running news portals, sponsoring cultural events such as symposiums and film screenings, publishing an online magazine and supporting LGBTQ+ refugees—is suspected of being criminal threatens the basic human rights of the LGBTQ+ community in Turkey.

These actions send a dangerous message to people and organizations exercising freedom of speech and association in support of queer people. Under the penal code, directing a criminal organization is punishable by five to ten years in prison, while merely being a member carries a sentence of two to five years. 

EFF joins hundreds of human, civil, LGBTQ+, and digital rights organizations around the world in calling for the immediate release of all those detained for exercising their rights to freedom of expression, association and legitimate human rights work, and the unblocking of all websites and social media accounts of affected organizations. 

For many LGBTQ+ individuals the world over, the internet can be a safer space for exploring identity, finding community, and seeking support. The anti-LGBTQ+ crackdown in Turkey is not happening in a vacuum—unfortunately we are seeing anti-LGBTQ+ bills restricting free expression and privacy, content moderation decisions that disproportionately impact LGBTQ+ users, and other forms of intolerance around the world. 

We urge international civil society and diplomatic partners to raise awareness of and to speak out against the crackdown, and to publicly show support for the legitimacy of Turkey’s LGBTQ+ organizations and the important work they do to ensure that queer people are safe and free.

Nature Climate Change, Published online: 09 October 2026; doi:10.1038/s41558-026-02773-z

The authors developed simulations to examine the role of topographic variation in mediating species response to climate change. They show that topographic variation can reduce energy expenditure by up to 20.8% and increase buffering benefits of elevation shifts by 82.1% for a diurnal ectotherm.

With artificial intelligence capabilities continuing to expand, universities now face complex, urgent questions about how to navigate increasing challenges, as well as new opportunities. Much attention is now directed toward this, including an MIT report on AI and education published this summer. 

A new essay from MIT Statistics and Data Science Center Director Sasha Rakhlin, the Distinguished Professor in Data, Systems, and Society, IDSS and Brain and Cognitive Sciences, synthesizes recent discussions and readings about how AI is changing academia — particularly mathematics, statistics, machine learning, and engineering. Here, focusing primarily on graduate research and education, he describes key questions that departments and universities need to think about, and how they can best work with AI going forward.

Q: What is changing in research, and why is it happening so quickly?

A: Mathematics illustrates how quickly AI capabilities are advancing. Last year, a model reached gold-medal level at the International Mathematical Olympiad. Only a year later, models are producing new research results, including a recently proposed solution to one of the Millennium Prize Problems. Tasks that once demonstrated advanced mathematical ability can increasingly be performed by AI.

A central factor determining the pace of AI progress in a particular discipline is the speed and reliability of verification. Formalized proofs can be checked automatically; programs can be run and tested. Where evaluation is fast and reliable, systems can generate candidates, learn from outcomes, and improve. This also applies to AI research itself: improving models, training procedures, and their supporting tools. Better models can contribute to the next round of development, creating a compounding process that accelerates progress.

For experienced researchers, this creates opportunities to pursue questions whose technical demands previously put them out of reach. It also sharpens the distinction between obtaining a solution and understanding why it works, what generalizes, and what to ask next. However, we should not assume that abstraction, judgment, or problem formulation will remain beyond AI. Universities should prepare for a near future in which AI is smarter than all of us in many, perhaps most, aspects of our intellectual work.

Q: How should departments rethink academic credit and graduate training?

A: In a growing number of fields, a polished paper is becoming a weaker signal of individual expertise. Departments must begin now to reconsider what they reward, without simply defining valuable work as whatever AI cannot yet do. Asking good questions, replication, synthesis of ideas, informative negative results, and shared datasets may deserve greater recognition. More broadly, evaluation should establish what a researcher contributed and takes intellectual responsibility for, including when substantial parts of the work were performed by AI. These expectations should guide hiring, promotion, and funding — and be made explicit for current and incoming PhD students.

Training poses a harder problem. Intellectual muscles develop through exercise. Routine calculations, coding, failed approaches, and small discoveries have long helped students acquire intuition and judgment. Delegating this work can remove formative experiences, even as AI allows students to attempt more ambitious projects. We need to distinguish unnecessary friction from work through which expertise develops. Students should learn to formulate problems, audit model outputs, reproduce results, and defend their choices. Fundamentals may become more valuable as the basis for using these tools well.

Q: What should MIT and other universities build now?

A: This is where I see a real opportunity for universities. Let's first be clear about the goal: Universities should be able to pursue questions over long horizons, share results openly, and evaluate claims independently. Partnerships with industry will be essential, but we should not assume that commercial priorities will cover the breadth of science or remain aligned with it over time. Some degree of technological independence will therefore be necessary.

Academia's most important strategic asset may be the accumulated knowledge and experience within its laboratories. Published papers present a selective record: Failed experiments, abandoned directions, and the reasons an approach did not work often remain unpublished. Scientists and engineers hold tacit knowledge, acquired through experience, about which interventions are likely to fail and why. This missing context may help explain why models currently struggle in some domains, especially the empirical sciences, to anticipate consequences that are clear to an expert. These limitations may be temporary, and capturing negative results and scientists' interpretations could make models much better at scientific exploration.

We can imagine a future in which MIT's laboratories function more like a single, living, scientific organism, connected through shared AI research infrastructure. For example, suppose a neuroscience laboratory needs better methods for segmenting neurons in microscopy images. An AI agent could recognize a relevant advance from a computer vision group, connect the researchers, propose benchmarks, and help them iterate. It could surface unresolved questions to students and faculty, and make lessons from one laboratory available to others. To make this possible, we should build workflows that capture hypotheses, interventions, outcomes, failures, and interpretations. Shared systems should connect these workflows, allowing agents to use tools and information across laboratories with appropriate permissions. This will require substantial public and institutional investment now in compute, secure data systems, and expertise in adapting and post-training AI models.

Tracing this process could also preserve the lineage of ideas and make contributions, including those of graduate students, easier to recognize. With agreed rules for consent and credit, researchers could collaborate more openly, with greater confidence that their work would be acknowledged. This could also help answer the earlier question of how to recognize and reward intellectual contributions.

AI systems can already synthesize and reason about information from more sources than any individual researcher could absorb, and their ability to make useful connections will continue to improve. We should use this capacity to bring us together around hard scientific and engineering problems, helping us build on one another's strengths and insights. To me, this is a promising path forward, but universities need to invest now to make it possible.