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.

In today’s digital world, the internet is an essential resource for young people to access information, explore community, and find themselves. But we know that this often comes alongside fears of experiencing online harms like doxxing, grooming, or bullying.

Trying to protect your family from everything all the time is impractical and exhausting, but some thoughtful planning can help families devise a workable plan that meets their needs and addresses their concerns.

That’s why this Digital Parent Week, we’re sharing easy tips on how parents and their children can work together to co-curate a digital safety plan that helps all members of the family enjoy the benefits of technology while protecting their online privacy and safety. 

Start with Open Conversations

Online safety begins with communication, not just restrictions. Talk with a young person about how they use the internet: their favourite apps, games, and social media platforms for example. Creating a supportive environment helps young people feel comfortable asking for help if something goes wrong online.

Together, you can think about:

1. What do we want to protect? e.g., I want to protect a young person’s privacy and mental health when they’re playing Roblox. They love Roblox and use it to communicate and hang out with their best friend, so we’d like to find a way to make it as safe as possible.
2. Who do we want to protect it from? e.g., messages from strangers, staying up too late playing, wasting money on pointless digital junk in games.
3. How bad are the consequences if we fail? e.g, losing some money on a scam or having creepy conversations with strangers that could escalate into something more nefarious or dangerous.
4. How likely is it that we will need to protect it? e.g., I don’t know the likelihood of a stranger messaging you on Roblox because I’m not sure how communication works on the platform, but I’ve heard from their friends that strangers message them all the time in some games.
5. How much trouble are we willing to go through to try to prevent potential consequences? e.g., I’m willing to learn from my child how the game works, play the game with my child, and learn how to work the parental controls. 
6. Who are our allies? e.g., my partner, our parents, as well as a young person’s best friends and their parents.

It's easy to think of a young person's experience on the internet as being totally disconnected and different from your own. But now is a great time to also interrogate your own internet habits, like the sorts of sites you engage with, tools you use, and privacy settings you've set. These questions are as valuable to help you as a parent as they are just an internet user.

Sometimes even just figuring out what conversations are worth having can take some effort, we've put together some ideas to get you started in our guide.

Make Privacy a Family Priority

Digital security training can feel overwhelming but this is why a community-oriented approach helps. In speaking with your family and friends, you can build out digital security practices that work for you. This makes it more likely that your privacy practices will become second nature to you and your loved ones.

Use secure messaging services for every communication: Choosing a secure service ensures that your privacy is protected from government and corporate surveillance. If you can convince your family to get on board, options like Signal provide the most extensive privacy protections out of the box through its use of end-to-end encryption and limited data collection. But we understand that sometimes it's easier to stick with whatever the family already uses for a group chat, like WhatsApp, Apple's iMessage, or Google Messages, so take the time to familiarize yourself with the limits of WhatsApp and RCS encryption.

Consider the content posted online: It's easy to accidentally share personal information through photos, messages, and other content. Children and adults may unknowingly share personal information through photos, messages, location settings and app permissions. Take time together to review privacy settings, check which apps can access the camera or location, and discuss why personal details should be shared carefully. Make sure you have family agreement about when and where to post photos of each other or your home.

Create incident response plans: Developing a plan for if or when something bad happens is a good practice for anyone, but especially with younger people. It’s important to strategize with your family around what to do in the event of such things happening, and doing so before an incident occurs is much easier than when you’re presently facing a crisis.

Alongside this, simple steps like using strong and unique passwords on all devices, including those that are shared in the family, can make a real difference. Regardless of age, there’s no time like the present to get started on good security hygiene, and for many that starts with a password manager and two-factor authentication.

How to Think About Parental Controls

Many sites permit parents to control features such as personalization, algorithmic feed, autoplay, endless scroll, reactions, notifications, and time limits. Talk as a family about which features are important and useful and which are problematic. The conversations above around boundaries and digital literacy are a more effective way to prepare youth for accessing the internet. To develop true autonomy, young people need the privacy to discover the world for themselves without their parents monitoring the contents of every conversation they have.

Explore new apps together and revisit family rules as they grow. These decision points where you’re exploring with a young person what you’re both comfortable with can be good moments to “find your way to a yes” for whatever feature or tool or game they’re asking about. The questions they ask, along with your responses, provide a road map for what to look for in privacy controls that can get you to a place where everyone is comfortable engaging with that technology. 

Small Steps = Big Difference

There is no one size fits all to the tech questions and concerns a parent will face, and keeping young people safe online is not about removing every risk and monitoring every click. This Digital Parenting Week, you can start to focus on what’s important for your family and how to best achieve those goals. 

If you're still not sure where to start, installing EFF’s Privacy Badger on every computer in your household is a great starting point to protecting everyone's privacy.

For more detailed information on all these tips and more, visit EFF’s Online Privacy Guide for Parents and Youth.

A user who is frustrated with changes a social media company made to their favorite messaging platform, like the introduction of an annoying AI chatbot, can’t do much to address the situation, short of leaving the platform.

Now, MIT researchers are offering an alternative path.

They’ve created Social.Wiki, a system that allows users to easily edit any social application made within Social.Wiki, and choose which of the edits made by others they want to see. 

For example, a user could change a messaging site on Social.Wiki to remove an AI chatbot and instead add a restaurant voting feature so their group chat can finally decide where they are going out for dinner.

“The infrastructure that we are all dependent on online is very rigid. It is based on these one-size-fits-all applications that we don’t have a lot of power to change. This project is about trying to imagine what a different web would look like where anyone can participate,” says Theia Henderson, an electrical engineering and computer science (EECS) graduate student, and lead author of a new paper on Social.Wiki.

The researchers envision a world in which, if a user is unhappy with their social app, they can edit it to change it however they like — without getting cut off from their social connections.

The platform enables users with no coding expertise to create a range of websites, including social sites like photo sharing networks, discussion forums, and dating apps. It handles all back-end work, eliminating the need for creators to set up servers or arrange databases.

Social.Wiki employs a decentralized infrastructure that allows users to retain ownership of their data as they create, edit, and navigate social websites within the platform. It also includes a “data guard” that protects user data from malicious or buggy applications. 

Through case studies and user tests, the researchers demonstrated the breadth of applications people can create with Social.Wiki, including a rideshare app where riders propose the prices they are willing to pay and a collaborative canvas for creating art together.

While Social.Wiki is still in its early days, the researchers plan to continue refining the platform as they deploy it to a wider audience. 

“We want to empower the creation of far more social applications that meet the needs of unusual small groups. Each group is unusual, but everyone is in unusual groups. Everybody has their own needs for social applications that we want to be able to address,” says David Karger, professor of EECS, a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL), and senior author of the paper.

Henderson and Karger are joined on the paper by EECS graduate students Carmel Schare and Ana Dodik; Clemens Klokmose, a professor of computer science at Aarhus University in Denmark; Ziv Epstein, a postdoc in the MIT Media Lab; and David D. Clark, an MIT research scientist. The paper will be presented at the ACM Symposium on User Interface Software and Technology in November.

Letting users choose

Social.Wiki is a Wikipedia-like system in which users can navigate to different web applications or create their own web application within the Social.Wiki ecosystem. Each website has an “edit” button that allows any user to change the content of the site, from the text color on a message board to the pricing algorithm in a ride-sharing app.

Clicking the “edit” button in Social.Wiki opens a page that lets users view and edit the source code manually or prompt an AI assistant to make changes to the site. 

This platform builds on the researchers’ prior work on Graffiti, a web framework with a decentralized infrastructure that makes building personalized applications easier. 

With Social.Wiki, the researchers sought a collaboratively editable system that would allow anyone to revise web applications to be ideally suited for their needs and the needs of groups they belong to. 

To enable this structure, Social.Wiki relies on a strategy the researchers call “plural governance.” Instead of a central moderator deciding which content users will see, each Social.Wiki user can choose the rules that determine which edits they will see on Social.Wiki webpages.

Users can also identify “trusted editors,” so they will see edits from individuals or organizations they consider reliable.

For instance, a user could customize their rules, or “governance policy,” so they only see edits to a site that have been endorsed by at least two of their friends. When the Social.Wiki browser loads a site for a user, it applies the governance policy that user selected to decide which version of the site to present.

For example, based on each user’s choices and edits, the system might show one user a ride-sharing app with a uniform pricing algorithm while another user might see the same app with a dynamic pricing algorithm.

“No website is tied to a particular machine. This means we have no centralized ownership over the websites or the underlying infrastructure,” Henderson explains.

Security and creativity

In this decentralized infrastructure, user data are stored separately from the websites that access it, which helps keep data secure.

Social.Wiki also employs a data guard, which prompts a user to review each request from a website that is attempting to access their data.

“In Social.Wiki, these websites are held in common and anybody can edit them, but the data guard makes sure that each user stays in control of what happens to their data,” Karger adds.

The researchers evaluated Social.Wiki through several case studies. For one, they developed a messaging platform that allows participants to modify the chat’s styling and interface without affecting the experience of others. In another, they built a collaborative ride-sharing app that enables riders to adjust the fare they want to pay using a transparent “living wage” calculator.

They also sponsored a hackathon in which users built Social.Wiki applications.

Participants developed a range of creative sites, including a housing co-op communication tool that organizes chats on a map of the co-op, as well as a garden-themed microblogging site where posts are “planted” as flowers.

“Even the little bit that has been done so far with Social.Wiki demonstrates that there is so much more that could be done with social apps if users could specialize them to meet a particular group’s needs,” Karger says.

Moving forward, the researchers are working to deploy Social.Wiki to a broader audience and gather feedback from more diverse user groups. They also want to make technical upgrades to enable end-to-end encryption on private message data and provide better developer tools.

This work was funded, in part, by Schmidt Sciences and the National Science Foundation (NSF). 

For decades, scientists have been able to look at individual moments in the development of an embryo: a snapshot of a developing brain, a picture of how the heart takes shape, or a glimpse of cells beginning to form the nervous system.

But what if instead of taking snapshots, they could watch the entire process unfold?

A new study out of the lab of MIT Professor Jonathan Weissman, a member of the Whitehead Institute for Biomedical Research and a Howard Hughes Medical Institute investigator, offers one of the most detailed views yet of how a mammal is built, cell by cell.

By following the family history of over a million cells as a mouse embryo develops, the researchers have created a kind of developmental blueprint, or movie, showing how cells divide and ultimately become the tissues and organs in the body.

This open-access work, published Oct. 8 in the journal Cell, in collaboration with Zachary Smith’s group at Yale University and the Max Planck Institute for Molecular Genetics, provides a comprehensive view of a process that has long been studied in pieces: how a single fertilized egg gives rise to hundreds of different kinds of cells, arranged in the right places and at the right times to build an animal.

“This is really a view of how the information in the genome plays out over space and time to go from linear DNA to a three-dimensional animal,” Weissman says.

The map could have broad implications for understanding birth defects and cancer. Many birth defects arise when cells change course as tissues and organs are being assembled. A detailed map of typical development could help researchers pinpoint where and when those processes go awry. In cancer, the same approach could help scientists trace when cells acquire traits such as the ability to spread or resist treatment. 

The map could also inform stem cell research by revealing the sequence of cell states that leads to mature, functional cell types.

In the 1980s, scientists ventured into similar territory by painstakingly following the development of Caenorhabditis elegans, a tiny worm whose transparent body contains only about 1,000 cells. Using microscopy, they could trace how individual cells divided and where their descendants ended up.

But achieving something similar in a mammal was a challenge on a vastly different scale. Mammalian embryos contain far more cells, develop inside the uterus — out of sight — and do not follow a completely predetermined script.

The new study tackles this challenge using a technology developed in the Weissman Lab called PEtracer. The system acts somewhat like a flight recorder inside a cell. PEtracer makes small, heritable changes to DNA that are passed down as cells divide. By reading those changes later, scientists can work backward to reconstruct which cells came from which ancestors, essentially building a family tree for the cells in the developing embryo.

In this work, the researchers combined these family trees with information about what genes were turned on in each cell and where these cells were located in the embryo. They analyzed over a million cells from mouse embryos collected at multiple points during development, allowing them to follow not just where cells ended up, but when they began heading toward particular fates.

A new study from Jay Shendure’s group at the University of Washington, published concurrently in the journal Science, uses a related approach called DNA Typewriter to track cell divisions in developing mouse embryos and build a record of their cellular history. 

Both studies provide a much more comprehensive look at mammalian development than existed previously. The Weissman team, however, studied embryos at closely spaced stages of development, looking at multiple embryos at each stage. This gave them a more detailed picture of how development unfolds and allowed them to ask how consistently cells follow the same paths from one embryo to another. 

With this detailed timeline, the researchers could also determine when cells commit to particular fates, how many early cells go on to form a tissue, and how they ultimately contribute to the developing organ.

While earlier studies might focus on one cell population, this approach puts those individual stories into the context of the entire developing animal — a perspective that is particularly useful for understanding disease. 

Cancer, for example, is not a single event, but a process in which cells acquire new characteristics over time, including the ability to spread or resist treatment. A lineage map could allow researchers to trace when those characteristics emerge and how cells change as they acquire them.

“Development and cancer both depend on decisions cells make about what they will become,” says Luke Koblan, a postdoc in the Weissman Lab and co-first author of the paper. “By tracing how cells develop in mouse embryos, we hope to better understand how cancer cells change in ways that help them spread or resist treatment.”

The work could also provide a new guide for stem cell research. Scientists have spent decades trying to coax stem cells into becoming mature, functional versions of particular cell types for research or potential therapies. But reproducing the precise conditions in an embryo is difficult.

“If we could have a step-by-step recipe for how to create every cell type in the body,” says graduate student and co-first author William Colgan, “that would be incredibly powerful for stem cell biology.”

Weissman compares the work to the Human Genome Project: knowing the sequence of the human genome gave scientists the ingredients — but not the instructions for how those ingredients are used — to build an organism.

“The genome is like the ingredient list for a four-course meal,” he says. “It tells you what the ingredients are, but it doesn’t tell you which ones you use when, how much you use, or where you put them. Without the recipe, it’s impossible to know how those ingredients can become the meal.”

This new map begins to fill in the details of that missing recipe. The result is a resource that researchers can use to explore mammalian development in a fundamentally new way. Rather than studying development as a collection of separate processes, scientists can now begin to see how those processes fit together into one unfolding story. 

In the most recent update to Apple’s devices, iOS 27.2, the company has introduced a new setting to “Exclude Apps” from Siri AI, fulfilling one of our asks from our Encrypt It Already campaign earlier this year.

One of our main concerns with new AI features on devices is how those features interact with end-to-end encrypted content, particularly with secure messaging apps. Many AI features require cloud processing, and despite privacy protections engineered into these systems, the content of secure messaging apps may leave a user’s device without their knowledge. That changes the privacy concerns around using those tools. In a perfect world, users would be able to put a barrier up to ensure data from certain apps doesn’t leave the device. Here was our initial ask:

You should be able to tell the operating system’s AI to not access an app, even if that comes at the “cost” of missing out on some features. The setting should be straightforward and easy to understand in ways the Gemini and Apple Intelligence controls currently are not.

At launch, we found the settings to control Siri AI’s app access behavior pretty confusing. You had to toggle several options to block Siri AI off from accessing an app, or disable Siri AI entirely. Turning off Siri AI and reverting to Siri Classic is, for now, still a good option if you’d prefer to use the older version.

The most recent update is far more clear and does more to protect your data. And, just as expected, it comes at the cost of some features. That’s a good thing, actually. The features not working shows that the new setting is effective. 

Here’s how to add apps to the exclusion list, once you’ve updated to 27.2:

• Open Settings > Siri > Excluded Apps
• Tap “Add Apps” and select any apps you’d like to add to the exclusion list

Now Siri AI cannot access the contents of the app. Excluding an app also means you may lose some features. For example, if you exclude the Apple Messages app, you will no longer be able to have Siri AI read or respond to messages for you. Even the “onscreen awareness” feature, where you invoke Siri and ask it for information about what you’re currently looking at, will not work anymore. For example, if you exclude Signal, you cannot invoke Siri and ask it to discern any information in the Signal app. You’ll just get these messages:

What’s the State of This on Android?

This update from Apple is also a good excuse to check in on the process on Android. It has improved a little, but is not as straightforward as Apple’s new settings, and lacks the ability to set the screen context feature per-app. But you do have some control over what Gemini can access: 

• Open up the Gemini app
• Tap your user photo, then Settings > Personal Intelligence > Connected Apps
• Revoke access to any apps you do not want Gemini to have access to

This process seems to work well enough for some data and we like that it’s opt in, but it’s not exactly intuitive. For example, Signal doesn’t appear there because Signal doesn’t support Gemini’s app access feature at all. That means Gemini can’t access the content of Signal directly, which is good. 

But Gemini can read notifications if you’ve enabled the “Device Assistance” Connected App (which you likely have, since that also enables basic features, like setting a timer—check under Settings > Personal Intelligence > Connected Apps), and it can use screen context unless you’ve disabled the Device controls > Screen context > “Use screen and app data” option in the Gemini Settings. These two features may access the contents of the Signal app or notifications, if you choose to use them. We’d prefer a more hard-lined approach that reduces the chances of user error here: Google should give users the ability to turn these features off per app.

Apple clearly understands that some users want stronger controls over what Siri AI can and cannot access. But we think they should go further and offer the option to only use “on device” AI features, similar to what Samsung offered with its Galaxy AI. We’re happy to see this change and think all operating systems need to consider similar controls moving forward.

A federal appeals court should curb the government’s abuse of grand jury subpoenas to unmask social media users who criticize lawless immigration enforcement.

That is the message from the ACLU, EFF, and other civil liberties and trade groups who filed a friend-of-the-court brief in a sealed case in the U.S. Court of Appeals for the District of Columbia.

The case involves the government’s investigation of an anonymous Reddit user who commented on a post about an immigration officer in Minnesota. The Department of Homeland Security (DHS) first issued an administrative subpoena to Reddit to unmask the user. When the user challenged the subpoena in court on free speech and statutory grounds (as many others have), DHS withdrew it. But then the government obtained a separate grand jury subpoena—a subpoena issued by a prosecutor to gather evidence to present to a grand jury before any criminal charges are filed—for much of the same information. The user then challenged the grand jury subpoena too, and the case is currently being appealed.

The right to speak anonymously is essential. It preserves privacy and shields critics from government retaliation. In the past year, the Department of Justice (DOJ) has issued grand jury subpoenas to social media companies for their users’ personal data. This is frequently done for improper purposes and without really showing that social media users have committed any crime. These subpoenas have the effect of intimidating and chilling critics, as immigration authorities have engaged in invasive, unconstitutional, and sometimes violent conduct.

As the amicus brief makes clear, courts should not defer to the government’s claims regarding the legitimacy of using grand jury subpoenas to unmask internet users. Instead, the subpoenas must receive proper First Amendment scrutiny. Like many other types of legal processes, grand jury subpoenas are issued by federal officials without prior court approval. And they too can be abused to harass or retaliate against people critical of the government.

The amicus brief was filed in early September and recently unsealed. The brief was signed by the American Civil Liberties Union of DC, EFF, the Center for Individual Rights, the Foundation for Individual Rights and Expression, the Cato Institute, and NetChoice.

It is notable that NetChoice signed the amicus brief. It is a trade group that represents many companies who have received similar subpoenas including Reddit, Google, Meta, PayPal, among others. EFF has called on these companies to do more to defend their users’ speech and privacy rights in the face of these subpoenas.

During its annual meeting on Oct. 19, the National Academy of Medicine (NAM) announced election of 100 new members, including MIT faculty member Michael Yaffe and six MIT alumni: Steven Allen Abrams ’79; Susan L. Ettner PhD ’91; Diane Medved Harper ’80, SM ’82; Albert Icksang Ko ’81; Jennifer Lewis ScD ’91; and Alexander Marson PhD ’08.

Election to the academy is considered one of the highest honors in the fields of health and medicine and recognizes individuals who have demonstrated outstanding professional achievement and commitment to service.

Michael Yaffe, David H. Koch (1962) Professor of Science, is the founding director of the MIT Center for Precision Cancer Medicine, as well as a professor in the MIT departments of Biology and Biological Engineering and a member of the MIT Koch Institute for Integrative Cancer Research. He is also an attending surgeon and intensivist at the Beth Israel Deaconess Medical Center, where he specializes in injury and surgical oncology, and was recently appointed as senior advisor to the director of the National Cancer Institute (NCI) for the NCI Intramural Research Program. 

The NAM recognized Yaffe for “the discovery of phospho Ser/Thr-binding domains in proteins and how they regulate signaling pathways controlling the cell cycle or in response to stress.” His contributions in this area were pivotal to “the emergence of systems biology and bioinformatic approaches to map motifs across the kinome and characterize biochemical principles that determine kinase-substrate selectivity.” 

Yaffe’s work in cell signaling more broadly seeks to understand how signaling pathways that control DNA damage responses, survival, cell cycle progression, and immune activation are integrated at the molecular and systems levels to control tumor outcomes after treatment, and to translate discoveries into more effective cancer drug combinations and treatment strategies.

Yaffe earned his doctoral degree in biophysical chemistry and his medical degree from Case Western Reserve University. Before joining the MIT faculty in 2000, he completed residencies in both general surgery at University Hospitals of Cleveland and surgical oncology at New England Deaconess Hospital, a fellowship in surgical critical care at Harvard Medical School’s Harvard-Longwood Critical Care Program, and a postdoctoral fellowship with Lewis Cantley at Harvard Medical School. Yaffe is a decorated veteran of the war in Afghanistan and retired as a colonel from the U.S. Army Reserve Medical Corps in 2021. He is also the scientific editor-in-chief of Science Signaling, an elected member of the Association of American Physicians, and a 2021 MacVicar Faculty Fellow.  

MIT alumni who were elected to the NAM for 2026 are affiliated with the following departments:

• Steven Allen Abrams ’79 is an alumnus of the Department of Biology.
• Susan L. Ettner PhD ’91 is an alumna of the Department of Economics.
• Diane Medved Harper ’80, SM ’82 is an alumna of the departments of Chemical Engineering and Materials Science and Engineering.
• Albert Icksang Ko ’81 is an alumnus of the departments of Chemistry and Biology.
• Jennifer Lewis ScD ’91 is an alumna of the Department of Materials Science and Engineering.
• Alexander Marson PhD ’08 is an alumnus of the Department of Biology.

Established originally as the Institute of Medicine in 1970 by the National Academy of Sciences, the National Academy of Medicine addresses critical issues in health, science, medicine, and related policy, and inspires positive actions across sectors.

“I am thrilled to welcome these outstanding health and medicine leaders into the National Academy of Medicine,” said NAM President Monica M. Bertagnolli. “Their extraordinary talent and commitment to advancing evidence-based guidance and solutions for our country’s greatest health-care challenges will strengthen our efforts to improve health for all.”

One of the main ways that the APOE4 gene variant, the biggest genetic risk factor for late onset Alzheimer’s disease, undermines brain circuit function is by disrupting the process of insulating neurons with a fatty sheath that optimizes their electrical transmission. A new study led by neuroscientists at the Picower Institute for Learning and Memory at MIT provides several lines of evidence to implicate a specific molecular pathway in that disruption, and uses that insight to demonstrate an intervention for preventing it in lab experiments.

The study, published Oct. 15 in Cell Stem Cell, shows that APOE4 leads to a suppression of “Wnt” signaling in the oligodendrocyte cells that provide neurons with a fatty insulation, called myelin. When Wnt signaling is deficient, they showed, the cells accumulate droplets of lipids rather than deploying fats to properly myelinate the neurons’ axon branches. When the researchers restored Wnt signaling in APOE4-carrying oligodendrocytes, myelination rebounded, both in human cell cultures and in mice modeling Alzheimer’s.

The research team, led by Picower Professor Li-Huei Tsai and study lead author Leyla Akay PhD ’25, a former graduate student in Tsai’s lab, discovered Wnt’s key role via multiple methods, including a screen in which they used CRISPR gene editing to systematically knock out each protein-coding gene in the genome, one by one, in cultures of human APOE4-carrying oligodendrocytes. The screen showed that when genes promoting Wnt activity in oligodendrocytes were lacking, lipid droplets accumulated, and that when genes suppressing Wnt were lacking, lipid droplets were, too.

“This proof of principle of doing CRISPR screens for genetic modifiers of APOE4-associated lipid accumulation in a central nervous system cell type is very exciting,” says Tsai, who also directs MIT’s Aging Brain Initiative. “I think this type of screen not only provides new insights into cellular pathways contributing to lipid metabolism defects, but really also has the potential to provide new targets for drug development.”

For want of Wnt

In 2022, Tsai’s Lab, led by Akay, Djuna Von Maydell PhD ’25, Jose Davila-Velderrain, and Joel Blanchard (also a co-author of the new study), showed that APOE4 caused lipid droplet accumulation in oligodendrocytes and upset myelination. But, Akay says, that droplet accumulation could happen for many reasons. The new study sought to dig deeper into the underlying molecular mechanisms.

“This CRISPR screen allowed us an unbiased way to test every single possibility,” Akay says. “What kind of lipid enzymes are involved in this process? And what are upstream pathways that could be targeted?”

In parallel with the CRISPR screen, the team also analyzed the chromatin accessibility of the DNA in human oligodendrocyte cell cultures and in postmortem human brain samples, in each case comparing APOE4-carrying samples to ones carrying the neutral APOE3 variant. This analysis of ATAC-seq data allowed them to assess which genes were most accessible for expression versus which ones were locked down from transcription. The chromatin analysis showed that genes promoting Wnt signaling were less accessible in APOE4 carriers.

“There was a striking overlap between ATAC-seq and CRISPR screen results,” Tsai says. “Both pointed to a dysregulation of the Wnt signaling pathway.” 

Toward a therapy

Further analysis, including direct observations in cells at the lab bench, revealed how Wnt signaling became depressed in cultured APOE4 oligodendrocytes. Two proteins, beta-catenin and GSK3b, each compete to regulate Wnt — beta-catenin promotes it, and GSK3b suppresses it. The team found that in APOE4 oligodendrocytes compared to APOE3 ones, there was reduced beta-catenin expression and excessive GSK3b expression.

The team then tested interventions that manipulate GSK3b activity. In human APOE3 oligodendrocyte cultures, they showed that increasing GSK3b with a chemical called Dif3 increased lipid droplets. In APOE4 oligodendrocytes, they showed that inhibiting GSK3b with a chemical called CHIR99021 reduced droplets. In more complex “organoid” cultures combining APOE4 oligodendrocytes with neurons, they found that inhibiting GSK3b increased myelination and promoted the growth of neural axons.

The tests suggested that GSK3b inhibition could be a proof-of-concept therapeutic strategy for restoring Wnt signaling and myelination. As a final test, they treated mice carrying APOE4 and genetically modeling Alzheimer’s tau pathology with doses of CHIR99021. The treated mice exhibited a reduction in lipid droplets in the hippocampus of the brain, a key memory-making region. Moreover, they also showed increased myelination there, compared to untreated controls.

In addition to highlighting suppression of Wnt signaling, the CRISPR screen and chromatin analysis provided key clues about the molecular mechanisms by which loss of Wnt alters how oligodendrocytes metabolize lipids. Akay and Tsai say they are eager to follow up on those clues. They are also interested in investigating GSK3b’s linkage to tau phosphorylation, a major feature of Alzheimer’s pathology.

In addition to Tsai, Akay, and Blanchard, the paper’s other authors are Anna Bright, Daiyun Dong, Ethan Smith, Robert Hurt, Carles Boix, Kate Louderback, Janine Medrano, Dingcheng Sun, Haonan Lin, Oisín King, Gwyneth Welch, Hiba Nawaid, Emre Agbas, Alan Jiang, Adele Bubnys, and Ji-Xin Cheng.

The National Institutes of Health, the Robert and Renee E. Belfer Family Foundation, the Manthripragada McManama Alzheimer's Fund, the CAMA Seed Fund, the J. Crayton Pruitt Foundation, Joseph P. DiSabato and Nancy Sakamoto, and the Freedom Together Foundation provided funding for the study.

Raw data from the study is available on the Open Science Framework. Akay and Tsai have applied for a patent on the CRISPR screen results.

Disorders of the small intestine are often difficult to diagnose and treat. More than 20 feet long, an inch in diameter, and located deep within the body, this organ is harder to access than other parts of the digestive tract, such as the colon or stomach.

To overcome those challenges, MIT engineers have designed a new robotic enteroscope that can move easily through the narrow passage of the small intestine, allowing it to perform imaging, deliver drugs, and remove small polyps or tissue samples for biopsy.

In designing the new robot, the researchers were inspired by the locomotion of snakes, as well as the scaly skin that helps them gain traction on slippery surfaces. A special textured coating helps the robot remain attached to the mucosal lining of the intestine as it inches its way through the narrow tube. 

Similar to an endoscope, the robot contains a variety of tools to help detect and treat any abnormalities that it might encounter.

“When we evaluate the small intestine, we do it for either diagnosis or treatment. If we find a little polyp that needs to be removed, this robot allows us to take a biopsy or remove it,” says Giovanni Traverso, professor of mechanical engineering at MIT, a gastroenterologist at Brigham and Women’s Hospital, and an associate member of the Broad Institute of MIT and Harvard.

Traverso is the senior author of the study, which appears today in Science Robotics. The paper’s lead authors are former MIT postdoc Binbin Ying, who is now an assistant professor at University of Texas Southwestern Medical Center; MIT graduate student Ahmad Mujtaba Jebran; and former MIT research scientist Sahab Babaee.

Snaking through the intestine

The most common problems that doctors need to evaluate within the small intestine include bleeding, lesions, and blockages.

Currently, the only way to diagnose those intestinal complications is with a procedure known as double balloon enteroscopy. During the procedure, an enteroscope advances through the small intestine as a health care worker alternately inflates and deflates two balloons that help propel it through the tract. 

This process is slow and laborious, so the MIT team wanted to design an alternative enteroscope that would be easier to control and could move faster through the intestine.

“The fundamental challenge that we’re trying to overcome is how to evaluate that 20-to-25-foot segment of the small intestine in a way that can be more automated,” Traverso says.

The new tube-like robot moves through the narrow small intestine using a locomotion strategy similar to that of the snake. When slithering along the ground, a snake can steer itself by first contracting muscles on one side of the body, then the other. 

To mimic this, the researchers designed multifunctional actuators that control the robot’s movement. Each actuator contains four chambers, which can be inflated in different combinations, prompting the tube to extend or bend in any direction. 

“By tuning the amount of air that goes into these chambers, you can tune the direction that the robot is moving in,” Traverso says.

The head and tail segments of the robot contain additional expandable anchoring balloons that take turns inflating and deflating, helping the robot move forward. These head and tail segments are coated with special patterned sleeves inspired by kirigami — a variation of origami that involves cutting paper as well as folding it.

Using this technique, the researchers created coatings that lie flat until they are stretched by the expansion of the balloon, which causes three-dimensional kirigami needles to pop out. Similar to the scales of a snake, these needles give the robot more traction within the slippery lining of the intestine. 

In previous work, Traverso’s lab has used this approach to create coatings for shoe soles that give them more traction, as well as stents that can temporarily lodge in the esophagus and release drugs. 

“By using kirigami sleeves to enhance surface friction, the robot can generate localized tissue engagement traction for locomotion without relying on excessive stretching of the delicate small intestinal tissue,” Jebran says.

Diagnosis and treatment

The system also includes electronics that allow for navigation, with a controller that the person operating the device can use to guide the robot through narrow passages and around tight corners. The soft robot is tethered to the external controllers by a cable and is designed so that it could enter the body through either the mouth or the rectum. 

The robot contains tools including a camera for imaging, a sprayer for drug delivery, and clips that can take tissue biopsies or remove polyps. 

In animal studies, the researchers showed that the robot could travel about six and a half feet through the small intestine. They also successfully demonstrated the drug sprayer, tissue clips, and camera. The team is now working on improving the navigation systems and testing this approach for additional applications in the small intestine.

“We hope we can continue to move it forward to eventually develop systems that can help achieve more automated evaluation of the small intestine,” Traverso says.

The research was funded, in part, by the Karl van Tassel Career Development Professorship, the MIT Department of Mechanical Engineering, a Banting Postdoctoral Fellowship, an NSERC Postdoctoral Fellowship, the UT Southwestern Medical Center Startup Fund, Samsung Semiconductor and Eurnekian Nanotechnology Graduate Student Fellowships, the Cooke Undergraduate Transfer Scholarship, and the MIT Undergraduate Research Opportunities Program.

For centuries, infrastructure has evolved alongside technology. New materials and engineering techniques enabled taller buildings, longer bridges, and larger cities. Computing and digital technologies later transformed how infrastructure was designed, monitored, and operated.

Now, the pace of change is accelerating, and challenges are arriving simultaneously. Climate change is increasing pressure on water, energy, and other resources. Artificial intelligence is beginning to transform engineering and design, and its energy needs, along with aging grid infrastructure, is creating significant challenges, as well as new opportunities. In addition, geopolitical complexity is exposing vulnerabilities in global supply chains, and demand for infrastructure is rising, particularly in the developing world.

The result is a fundamental challenge: How can the world build the infrastructure it needs without simply repeating the extractive, carbon- and resource-intensive model of the 20th century?

In this interview, Ali Jadbabaie, JR East Professor and head of the MIT Department of Civil and Environmental Engineering, says the answer will require rethinking not only how infrastructure is designed and built, but how it is financed and operated, and bringing together the many stakeholders who shape those decisions. On Oct. 28, Jadbabaie will join experts from around the world in Madrid to explore these topics at the World Infrastructure Forum, which was co-founded by MIT’s Department of Civil and Environmental Engineering, UPM, the World Bank Group, and the University of Texas at Austin.

Q: Infrastructure has always evolved in response to technological advances. What makes this era different?

A: In the 18th century, civil engineering emerged as the civilian counterpart to military engineering, building the dams, bridges, and canals of its time. Industrialization in the 19th century brought railways and sewage systems. In the early 20th century, the focus scaled up to buildings, highways, tunnels, and metro systems, and by mid-century the infrastructure needed to support megacities and skyscrapers.

Every time technology has changed, with information technologies, computing, sensing, and, more recently, digital transformation, it has changed the shape of infrastructure. It has even changed the definition of what infrastructure is. Today, we consider the power grid, semiconductor manufacturing plants, and data centers part of infrastructure, along with wireless infrastructure like cellphone towers and the infrastructure for high-speed internet, just as much a part of our critical infrastructure as roads, water systems, and power grids. 

What is different now is the combination and speed of the changes we're facing. Climate change, resource constraints, and geopolitical instability are putting pressure on the way we designed infrastructure in the 20th century. At the same time, many people are moving out of poverty because of recent economic growth in the developing world. In fact, according to models, by 2028, for the first time in the history of humanity, the median human inhabitant of the planet will live off $10 a day. As more people move out of abject poverty, there will also be an increase in the demand for infrastructure.

If we try to meet that demand using the same resource-intensive model we used in the 20th century, we simply won't have the resources to do it. The question then becomes: How do we use the remaining resources more efficiently? We need to find a way to provide more infrastructure while using less water, energy, and materials, and produce less carbon.

This is where digital transformation and AI become potentially transformative. Faster and cheaper sensing, greater access to data, and better sensing, actuation, and control can help us make infrastructure decisions more efficiently. AI is slowly permeating the physical world, and we expect it to revolutionize the engineering design process, allowing us to explore many more possibilities, much faster and at a lower cost. 

But the story of that hasn't been written yet, and the outcomes could still be very positive, depending on what we do.

Q: Can you give an example of infrastructure systems becoming more interconnected in a way that changes how we build or manage them?

A: The revolution in information technology and digital transformation over the past 30 years has made infrastructure systems more interconnected. You see this in cities. If the power goes out, water and gas systems can stop functioning, internet fails, and transportation system comes to a halt. If communications networks fail, many other services are affected. We saw this during Covid, when disruptions in supply chains affected energy networks, critical materials, and manufacturing. We see it when geopolitical conflicts disrupt oil and energy markets and those disruptions propagate through other parts of the global economy.

Infrastructure systems that were once managed separately are increasingly dependent on one another. As we connect more things together for more efficiency, we also increase systemic risk and expose the systems to rare but catastrophic failures. They have become rare, but when they happen, they're much bigger and more consequential.

The really tricky thing is that developing infrastructure involves much more than designing and building it. The whole value chain includes financing and operating it, as well as understanding who will use it and what those users need and prefer.

So, designing infrastructure is a highly transdisciplinary, sociotechnical endeavor, involving social, technical, and economic considerations. Understanding how these systems are designed is increasingly important because they are becoming more complex, making decision-making particularly difficult.

There’s also so much uncertainty in large infrastructure projects. They’re very capital-intensive, the business is lower margin than many other industries, and projects take a long time. Combine all of that, and it has historically made the industry very conservative.

But the transformations coming from AI and digital transformation are potentially offering a new way forward. What that new way looks like, no one has quite delineated it yet.

Q: How are you and your colleagues working to change how these decisions get made?  

A: We realized that if we're going to develop a new approach to infrastructure, no single discipline, company, or country can do it alone. Infrastructure value chain is too interconnected, and the challenges are too large.

That's why MIT’s Department of Civil and Environmental Engineering co-founded the World Infrastructure Forum with the World Bank Group, the Universidad Politécnica de Madrid, and University of Texas at Austin. The goal is to bring together academia, industry, governments, and financial institutions across the infrastructure value chain and create an ongoing dialogue about how infrastructure should be designed, financed, built, and operated in the decades ahead.

This is particularly important because the biggest opportunities for new infrastructure development are not necessarily in the United States or other countries with mature infrastructure systems. Those countries still face significant needs for modernization and new investment. But over the coming decades, much of the world's population growth, and much of the infrastructure that will need to be built, will be in countries where infrastructure systems are still developing. 

Those countries have an opportunity to benefit from modern infrastructure without simply repeating the model of the 20th century. But capturing that opportunity will require new approaches to technology, financing, engineering, and governance.

We're trying to create an ecosystem rather than just a forum, a mechanism for continuing the conversation among the different stakeholders across the infrastructure value chain. We've established five working groups and an advisory group of more than 30 leaders from across the infrastructure value chain, including engineering and construction, materials, finance, multilateral institutions, and academia.

Ultimately, the question is not whether we need a new way of developing infrastructure. The question is how we create it and who is going to execute it. There is no single person, company, or country that can solve this problem, because infrastructure itself is interconnected. We need to build the new model together.

When we give our private information to the government to pay taxes, apply for a job, or vote, we should be able to trust that our data won't later be used against us. But in a betrayal of that trust, the federal government has been pooling the information it has about us on an unprecedented scale—and using it for purposes we never agreed to.

EFF and other groups are fighting back. In our latest EFFector newsletter, we're talking about a recent victory in our lawsuit against the government for sharing federal workers' confidential personnel files with DOGE.

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For over 35 years, EFFector has been your guide to understanding the intersection of technology, civil liberties, and the law. This issue covers our free tracker blocker coming to Safari, a call to action for net neutrality in California, and a big win in our lawsuit against the DOGE data grab.

Prefer to listen in? EFFector is now available on all major podcast platforms. This time we're talking to EFF's F. Mario Trujillo about the dangers of government data grabs—and what defenders of privacy are doing to stop it. You can find the episode and subscribe on your podcast platform of choice:

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Researchers set up a fake start-up company to study fraudulent North Korean IT workers.

Nature Climate Change, Published online: 28 October 2026; doi:10.1038/s41558-026-02784-w

As the IPCC is in its seventh assessment cycle, bridging the gap between physical climate science and economics has become more urgent. Estimating climate damages requires a rigorous translation of physical hazards into economic losses, highlighting the need for better communication between the disciplines.

Nature Climate Change, Published online: 28 October 2026; doi:10.1038/s41558-026-02758-y

This work investigates the effect of the 2016 regime shift in Antarctic sea ice on Antarctic Intermediate Water (AAIW). The authors show that decreased sea ice and reduced freshwater subduction lead to saltier and denser AAIW, with implications for wide-scale water-mass properties.

The crack of a bat accompanied by a roar from the crowd can capture a baseball fan’s attention, even if they miss seeing the home run. Humans may be visual creatures, but we also perceive the world around us by listening to it. 

To improve artificial perception, MIT Professor Paris Smaragdis SM ’97, PhD ’01 seeks to make machines that can hear and understand sound even better than humans.

A machine with super-human hearing could rapidly pinpoint the location of a traffic accident by listening for squealing tires and crunching metal, or identify when an industrial drill might break while it is boring through dense bedrock to dig a geothermal well.

“I like to say that I do the same thing the computer vision folks do, but instead I do it for hearing,” says Smaragdis, a professor with joint appointments in the Music and Theatre Arts program of the School of Humanities, Arts, and Social Sciences, and the Department of Electrical Engineering and Computer Science in the School of Engineering and the MIT Schwarzman College of Computing. 

His research group explores areas like machine learning for sound source separation, smart devices that can augment the audio surroundings of humans, and better tools to help people understand, manipulate, analyze, and create music.

“Having had a musical background, I’ve been interested in examining these ideas. What does it take to make machines understand sound? There is a huge domain of applications for machines that can listen,” says Smaragdis, who joined MIT in 2025.

A musical prelude

Smaragdis, who grew up in Greece, began playing classical guitar at a young age. He enjoyed playing traditional pieces but reached a turning point in his musical journey when his father brought home a small synthesizer.

“That little synthesizer had a function that allowed you to make your own sounds, and I became completely captivated by the possibilities,” he says.

Synthesizers were taking a more prominent place in pop music during the 1980s, adding to his fascination with the technology.

As he advanced through school, Smaragdis wanted to study music made with synthesizers. But this was not an educational path offered by the more traditional European conservatories at the time.

Instead, he enrolled at Berklee College of Music in Boston, into a program where he could explore the use of computers and synthesizers to shape and manipulate sound.

“With computers and synthesizers, I could make new sounds that have never been heard before,” he says.

At the same time, Smaragdis became immersed in jazz fusion. He declared bass as his major at Berklee since it would allow him more opportunities to play with jazz ensembles.

“I found the bass to be sonically more interesting than the guitar. It was a more unexplored domain, and I’ve always gravitated toward unexplored domains,” he says.

That interest in the unexplored carried over into his coursework. He and mentor Richard Boulanger, a professor of electronic production and design, created new tools to help people use computers to write, produce, and enhance music. 

Through his studies at Berklee, Smaragdis embarked on a collaborative project with Professor Barry Vercoe (who passed away in 2025) at the MIT Media Lab to create software synthesizers for music creation. Building on that project, Smaragdis pursued graduate studies in Vercoe’s group, where he completed his master’s degree and PhD, followed by a postdoc.

“In the Media Lab, I got exposed more to the computer part of computer music. That’s where my attention shifted a bit. Now I really wanted to make computers that could understand sound,” he says.

Tuning in to unexplored domains

At that time, many students in the Media Lab were using signal processing techniques to help machines handle sound. Smaragdis chose a less explored approach — machine learning — to separate himself from the pack.

He found that training machine-learning models to understand sound offered advantages that couldn’t be attained with traditional signal processing techniques.

“Over time, it became really clear to me that we need to teach computers how to listen. We can’t just tell them how to listen. If anything, we don’t even know how we humans listen,” he says. “We don’t have a vocabulary to explain what it means to listen, or how to tell the difference between a cat’s meow and the sound of a violin.”

After finishing his postdoc, Smaragdis began a career at Mitsubishi Electric Research Labs, where he worked on artificial intelligence systems that could scan video soundtracks and understand what is happening on screen. 

“What if you record an entire soccer game, but you only want to watch the highlights? In computer vision, it is very difficult to identify what a highlight is. But on the other hand, if you only listen to the sounds, then when the crowd goes crazy you would know that something interesting is happening,” he says.

That system was eventually incorporated into electronic devices, including a personal video recording system Mitsubishi was developing at the time, and into traffic monitoring systems and cell phones.

Smaragdis later joined Adobe, where he created the audio research team that built user-friendly tools to help artists, musicians, and producers manipulate sound without needing a lot of expertise.

“As we did that work, I kept coming up with deeper technical problems that needed to be resolved. I jumped into academia to address that itch,” he says.

Smaragdis joined the faculty at the University of Illinois at Urbana-Champaign, where he and his group incorporated the latest machine-learning techniques into audio-processing systems.

One of the technologies they developed utilized neural networks for separating individual sounds from audio mixtures. That project caught the attention of the team working on the 2021 documentary mini-series “The Beatles: Get Back.”

The production team enlisted Smaragdis to help clean up some archival Beatles recordings.

“That was a very different way of audio processing than what I was doing in academia. Now, I had to do something that sounded good but didn’t necessarily have to look good on paper. We didn’t have a formula we could optimize,” he says.

Every recording involved different challenges. For instance, in one clip John Lennon was playing music while Paul McCartney was horsing around, reading headlines from newspapers and making fun of George Harrison.

“We were trying to come up with a technological solution that could help us do everything, as opposed to addressing each problem on its own,” he says.

His contributions helped the team win an Emmy Award for sound editing for a nonfiction or reality program, in 2022.

A concerted effort

After 15 years at the University of Illinois, Smaragdis decided to join the faculty at MIT to tackle the thorny, interdisciplinary problems that were emerging in the field. 

His group now focuses on two main areas. For one, they develop systems that make computers more useful tools for musicians. 

One project in this area is enabling machines to understand how to listen to music, so they can provide constructive feedback to musicians.

“We want to enhance the toolbox a musician has. We don’t want to use computers to replace musicians,” he says.

On the other side, his group focuses on the fundamental tools scientists and artists alike can use to process, analyze, and manipulate audio.

For instance, his team has recently been exploring algorithms that allow sophisticated signal processing where traditional frames of reference, such as sampling rates, frame sizes, or context-windows, are not fixed — or even defined. 

That implies different computational structures that are yet unexplored, despite their potential for more efficient processing, Smaragdis says.

“That requires rethinking a lot of the basics, but once you have that ability, you can start getting much more flexible and more powerful systems,” he adds.

They also explore ways to incorporate the latest techniques, like large language models, into speech recognition and audio enhancement.

“AI is an immensely powerful tool, but I don’t think we have found the ideal way to use it for sound and music yet,” he says.

He also enjoys mentoring students and helping them materialize their visions for research projects.

Since few of his students have experience using computation in sound, he emphasizes hands-on lessons so they see and hear how to transform equations into something tangible.

Smaragdis still feels a thrill from making music, whether with a computer or a more traditional instrument. Off campus, he tries to play jazz bass whenever he can find the time, and enjoys exploring the rich musical community of Boston with his wife and 15-year-old son.

Outside the musical realm, he plays and coaches underwater hockey — a sport where players wear diving masks and use sticks to push a heavy puck across the bottom of a pool toward their opponent’s goal. He coached the underwater hockey team at the University of Illinois, and is hoping to revive the MIT underwater hockey club soon and start hosting tournaments on campus.

While underwater hockey may be a lesser-known sport, it fits with Smaragdis’ lifelong interest in pursuing the underexplored.

“I’ve always like doing things that were different from what everyone else was doing. If you can create a new sound that no one has heard before, what does that mean about your ability to create new things? I still find these questions completely fascinating,” he says.

Everyone knows, or should, that perfect (balanced, targeted, transparent, swift and swiftly appealable) content moderation at scale is impossible. That doesn’t mean powerful social platforms don’t have to try to get at least reasonably close, especially when access to good information can have a profound effect on political participation and speech.

That’s why so many people, including the Meta Oversight Board, criticized Meta for suspending a major political Instagram account for hours during a huge early voting push on October 17; and for allegedly boosting one candidate in Brazil’s recent presidential election. Meta denies deliberate interference in either instance, blaming “mistakes” in its automated content moderation systems (including AI tools that can’t tell the difference between enthusiastic follower engagement and a bot attack).

Mistakes or not, with early voting in the U.S. midterms already underway, these events serve as a stark reminder that all major social media platforms need to have stronger systems in place to ensure that they serve, rather than impede, democratic communication.

Access to good information can have a profound effect on political participation and speech.

This is not inherently an “AI” problem: automated systems can process content at a scale that humans never could, potentially enabling better moderation at scale and alleviating the psychological load on ill-paid moderators whose jobs require them to view incredibly disturbing content. But automated systems also reproduce existing biases, struggle to understand context, and often make mistakes that disproportionately affect journalists, activists, artists, and other vulnerable and marginalized communities. And moderation errors are even more likely when the language is spoken principally by the global majority. In 2020, leaked document showed that Meta’s algorithms incorrectly deleted nonviolent Arabic-language content 77 percent of the time, while failing to detect hate speech under the company’s own policies in many instances. Where these systems are faltering in Arabic, they’re positively failing in less-resourced languages. As a 2025 report from the Center for Democracy and Technology found, labeled datasets in certain languages and dialects such as Maghrebi Arabic and Kiswahili contain inconsistencies, bias, and inaccuracies due to the limited hiring of annotators who actually speak the languages as well as shifts in the languages themselves. An investigation into ChatGPT’s outputs in several low-resource languages demonstrates the depth of problem.

But language disparities are just one of several concerns as automated moderation becomes more widespread. From the systemic suppression of content from Palestine to the repeated misclassification of LGBTQ+ content as adult or explicit material, these varied examples demonstrate the risks of overreliance on automated moderation—and the need for stronger safeguards.

Fortunately, there is a great deal companies, policymakers, and civil society can do to help ensure that highly automated systems operate in ways that respect human rights, minimize predictable harms, and provide meaningful accountability when they fail. If companies are going to continue relying on automation to moderate users’ speech—and there is little reason to believe they won’t—then accountability must evolve alongside these technologies.

That work should start with publicly committing to the Santa Clara Principles 2.0. Specifically:

1. Automated technologies should help, not replace, human moderators. For example, automated systems can help flag and prioritize content for review, while humans can interpret context, handle sensitive cases, and refine system performance. This investment is particularly important during the weeks immediately before and after an election.
2. Companies must be transparent about when and how automation is used in content decisions.
3. Companies must regularly audit their automated systems for bias, with particular attention to low-resource languages, vulnerable and marginalized communities, and conflict zones.
4. Companies should strengthen personal data protection guarantees and policies. Automated content moderation often relies on personal data and profiling, so companies should think carefully about what data these systems use, what's necessary and proportionate and how their systems shape moderation outcomes.
5. Users must have the ability to appeal, and to provide context when they believe human or automated moderation decisions have wrongfully removed their content. Appeals should be promptly evaluated and decided by human moderators.
6. Companies should regularly assess the human rights impact of their moderation decisions, and issue public statements of the results
7. If they rely on third-party vendors, companies should carefully (and regularly) audit those vendors for compliance with these same principles
8. Lawmakers should avoid promoting and passing legislation that effectively or explicitly mandates automated moderation systems
9. Policymakers should also refrain from attempting to dictate platforms technical and design choices to favor or disfavor particular expression.
10. Policymakers should work to educate the public about how their personal data may be collected and used in electoral contexts.

These recommendations understand that automated content moderation isn’t just a technical problem for clever engineers and product teams to solve. Because content moderation shapes public discourse and fundamental rights, its design and oversight must respond to the concerns of policymakers, civil society, independent researchers, and the communities most affected by these systems.

One other distinct and enduring problem makes transparency, checks, and accountability all the more urgent: too few companies have far too much power over our political communication and organizing. Social media gave people the ability to wrest some control over political messaging away from media oligopolies. But we’ve met the new boss and while it’s not the same as the old boss, the song is pretty familiar. The real promise of the web to democratize communication is not likely to be met by social media oligarchs, no matter how sophisticated their content moderation practice.

Like many leaders today, Prabha Jha has been feeling the significant impact artificial intelligence is having on business operations. While the rapid evolution of the technology can bring fear, uncertainty, and confusion, Jha chose a different response: excitement. She began asking herself, “How do I become part of this once-in-a-lifetime thing?” 

Jha holds a bachelor’s degree in information technology from the University of Calcutta and earned her MBA while working at Verizon, where she continues to build her career. As she looked for an educational opportunity to engage more deeply with AI, MIT quickly emerged as a natural choice. 

Growing up, Jha viewed MIT as “the mecca for anybody who is in engineering and technology,” so she naturally turned to the Institute when seeking an opportunity to learn about AI. Unlike other programs that took place fully online, MIT xPRO’s AI for Senior Executives stood out to Jha primarily because it offered an in-person component that allowed her to meet and connect with peers. 

Jha decided to take the leap. She acknowledges that the program was a significant investment of both time and money, but ultimately views it as one of “the best decisions [she] made” — one she “would do all over again if [she] had to.” The experience gave Jha the opportunity she was looking for to invest in herself and strengthen her skills in AI. It also provided her with invaluable professional relationships and the confidence to develop multiple AI solutions for Verizon. Putting those news skills and relationships to work, she co-wrote, with some of her peers, “The AI Anthology,” a collection of AI insights designed to support other leaders navigating similar challenges with AI. 

An unexpected learning obstacle

Jha’s learning journey wasn’t without its curveballs, though. Just two months before she was set to complete the program, she spent two weeks in the hospital with a severe infection and was unable to graduate with her original cohort. With the help of MIT staff, she joined the next cohort, giving her an unexpected opportunity to spend another five days on campus with 100 brand-new peers. 

“You just never know what curveball life can throw and what it might be there for,” Jha says.

What initially felt like a setback turned into an unexpected benefit. Jha valued the opportunity to meet new people and spend more time on campus. She also appreciated that just six months later, the program’s content had already been refreshed. Those additional “five days of immersion” became a vital part of Jha’s learning journey, giving her and her peers more time to collaborate face-to-face and learn from one another. 

“I think it was eye-opening to be able to meet so many people with diverse backgrounds and geography, and then we connected at the human level,” she says. 

Jha particularly valued that sense of connection in the context of learning about AI, a field that, she acknowledges, comes with fears, vulnerabilities, and difficult questions. Learning alongside peers with different professional and cultural backgrounds gave her new perspectives and added another dimension to the experience. Jha estimates that “30 percent of what I was learning was from the program, material, and professor [while] 70 percent was my peers and the interactions.”

Peer discussions spark an idea

The idea that would change the trajectory of Jha’s time in the program came during a “salon gathering” at the home of Manolis Kellis, a professor in MIT’s Department of Electrical Engineering and Computer Science. As students shared personal stories about their experiences with AI, one story in particular stayed with Jha: that of one of her peers, whose motivation to explore AI solutions stemmed from her work to find a cure for her mother’s Alzheimer's disease and dementia. 

At that moment, Jha realized that AI is personal. She still “gets goosebumps thinking of that moment where AI really became human and a connecting point.”

She saw the value in capturing these diverse perspectives and experiences with AI that go beyond operational efficiency and revenue growth, and wanted to continue the conversation beyond the program. Jha expressed to her peers an interest in capturing these stories and connections in a book. One year later, Jha and 20 other leaders released “The AI Anthology,” a collection of essays examining the influence AI has had across industries and across society. 

One of the biggest takeaways from the AI for Senior Executives program — and one that Jha hopes readers will take from her book — is the importance of thinking differently. 

Jha believes leaders may be missing a fundamental shift: “We are still kind of stuck in this traditional measurement of success,” she says. “We cherish revenue; we like cost-cutting and time-saving, and converting them to dollars.” 

While Jha acknowledges this mindset makes sense in corporate America, she believes leaders must move beyond it in order to find more empowerment through AI and its capabilities. She notes that future generations are already asking different questions, including: “What can I get in the quality of my life?” and “How can I use my time in a way that is fulfilling for me early on?” 

The future of embracing AI for business and a better world 

Jha recognizes that AI adoption is not optional for businesses, and that everyone must learn about and embrace it. At the same time, she is a steadfast believer in AI’s ability to create a better world. Instead of viewing AI as a foregone burden, she sees it as a “transformation unlike any other” that is providing us with the opportunity to overcome insecurity, adapt and grow, and invest in ourselves. 

In her work at Verizon, Jha takes seriously the company’s role as “a brand name for reliable, quality service” providing “critical infrastructure” to groups, such as first responders or children, who depend on their services. This responsibility comes with a privileged obligation to participate in and protect society, and Jha finds it empowering that AI can help enable this. In her own experience, she’s appreciated the ability to accelerate progress and impact, when she may have previously needed to rely on a larger team. 

So, what’s next for Jha? Currently, she is working on a new initiative focused on supporting small and medium-sized businesses that are navigating AI implementation. Her goal is to help them understand what tools they need, how AI fits into their specific operational model, and how they can measure success, so they can focus on their strengths as a business and how they can drive value. 

Angeline Peng doesn’t come from a strong faith tradition, but she is a big believer in the power of discussion. In her role with the Addir Fellows Interfaith Dialogue Program at MIT, she convenes and leads regular, small-group interfaith conversations to help other students — and herself — grapple with big questions.

The Addir Fellows Program was started in 2005 through a grant from the U.S. Department of Homeland Security. It is now supported by MIT’s Office of Religious, Spiritual, and Ethical Life. The program has maintained a steady focus on “sharing spiritual values and experiences, not just opinions,” says MIT Chaplain Thea Keith-Lucas.

A fourth-year math major, Peng sees deep connections between what she’s learning in class and the Addir Program. Here, she describes her work with the program, the link between faith and logic, and how she believes discussing big questions changes people.

Q: What is the Addir Fellows program?

A: It’s an interfaith dialogue club. “Addir” comes from the Sumerian word for “bridge,” and that's what we're here to do — build bridges between people from different walks of life. 

We meet every week in small groups of five to eight people. The groups start off with what we call our “spiritual autobiographies.” As much as we can, everyone gives a description of where they're coming from. After that, every week we pick a topic and discuss it. 

We try to balance faith traditions in the small groups. The biggest limiting factor is scheduling. That turns out to be really complicated. 

Q: What’s your own spiritual autobiography?

A: My family is atheist. I was born in Singapore, which is very multicultural, and we moved to Lehi, Utah, when I was 10. Utah is very homogeneous; most people in my neighborhood were part of the Church of Jesus Christ of Latter-Day Saints. Sometimes in high school I would ask friends about their beliefs, but college was the first time I could really explore. 

At some point I realized it's important to know myself better, to understand and have my own principles. Exploring different religions is an attempt — and I am still building this — to understand what I think is important, what I value, what I think is right, and what I think is wrong. 

Getting insight from different faith traditions is really helpful. I believe different religions, or different approaches to religion, are all interpretations of universal truth — and so exploring from all kinds of perspectives will give me a better understanding of what that could mean. 

I'll say, I'm not too sure about it yet. I don't know if there's some kind of universal good, or bad, or whatever. But I do think there are some kernels in everything. 

Q: Who participates? Does the program bring together a range of faith traditions?

A: When I signed up for my first Addir event, I met grad students and undergrads from just about everywhere. It was very refreshing, like — “Wow! I didn't know there were all these people here!” At MIT, you can end up in a kind of bubble. You know people from your dorm or your major. This program’s different.

The people come from a wide spectrum of traditions and backgrounds. Also, we have quite a lot who are somewhat agnostic or less extreme in their beliefs. 

A big part of why people sign up for Addir is they want to listen to other people and learn. Sometimes, this means they don't talk as much. I do my best to instigate — play devil’s advocate and push at people's ideas. I believe that’s part of my job.

Q: Do you think participants feel pressure to speak “for” their faiths?

A: I wouldn't say anyone is trying to represent their faith, because there are so many facets of just one faith anyway. When there are questions, everybody gives an answer like, “This is what I think.” Sometimes people will bring up a text and say, “It says this, and this is how I interpret it, or this is how certain people in my life interpret it.” That can be really helpful.

Also, I wouldn't say we’re focused on just religion. A lot of people are just trying to find their way in life, whether it’s through spiritual or secular questions. In my small groups, we've talked quite a bit about what we can do to just be a better person; exploring different aspects of that, and dealing with more everyday stuff like regrets, guilt, pleasure, pain, punishment. Obviously, religion can help you with answers. 

I like to think: How can we answer those questions as a group, in that room, in that moment? The answers might be different for everyone, but if we can hear what other people think, maybe we can get insight and be persuaded into believing something new. 

Q: How does the mathematician in you come out during these conversations? 

A: I think part of why I do math is spiritual, so they're connected in that sense. It all relates to how I want to live my life. Some people describe doing math like making art — they're in pursuit of beauty and some deeper truth. I think math is really pretty, and there's a lot of beauty in the truth. 

One of the great tools of mathematics is that it teaches you how to abstract and understand which details are just details, and what are the core ideas. Doing a lot of math helps me stay objective, abstracting away things that are less important. 

Q: Can it be difficult to reconcile issues of faith and logic? 

A: You have to always believe in something. It's like picking your axioms. You start with faith in something, and from there you can extrapolate away what you think.  

It can be very difficult. Gödel's incompleteness theorem says you can't prove everything with any set of axioms. You can choose whatever set of axioms you like, and it either is incomplete or inconsistent; incomplete, as in you can't prove every statement is either true or false, and inconsistent in that you will at some point prove that something is both true and false. So you can't have both. But we want both! 

Mathematicians live with the incomplete, and this is probably true for any belief system. Some people are deeply unhappy not knowing the answer, and some people are more OK with it. I tend to be very OK with it. 

Q: Do you think this program changes people?

A: Definitely. Over time, people's opinions really do change. We all have the more “press-ready” opinions we give to others. Even in Addir, it's got to be half or two-thirds of the year before I feel comfortable talking about everything I really believe. This program is genius because you actually become friends by the end. 

To actually care about another person — as a person, outside of what they believe — is really a function of time. You need to be together and have this dialogue for a while. When there’s conflict, finding solutions is very situation-dependent, and maybe not possible. But eventually, you get to know each other. You can talk about controversial issues or opinions that maybe you were scared of sharing before. It's so nice to have this space as your opinion is changing. 

Because of Addir, maybe one person learns a little bit, and they go back to their own group of people and share that perspective. And when they share it, someone else learns. I'm a big proponent of let's try to change things locally — very locally; person by person — and maybe we can spread that positivity. 

New records obtained by EFF expose additional issues with Medicare’s AI-driven prior authorization program and show why we need stronger legal limits around government use of automated decision-making. 

EFF sued the government back in March for information about the Wasteful and Inappropriate Service Reduction (WISeR) model, a new Medicare program that uses AI to evaluate prior authorization requests for certain medical services. We previously released records showing that WISeR has resulted in delays and denials of care, operational chaos, and reports of patient harm. Today, we’re publishing over 800 new pages of records, including:

• Requests for information (RFIs) or requests for corrective action plans (CAPs) sent from the Centers for Medicare & Medicaid Services (CMS) to four of the six WISeR vendors, along with the vendors’ responses.
• Applications of 66 companies to the WISeR model, including those of the 6 selected companies. 
• Task orders and contracts for the evaluation, implementation, and monitoring of the WISeR model.

Documents obtained through EFF’s lawsuit are available here.

These newly released documents show that the WISeR rollout was rushed and rocky from the start, highlighting the dangers that arise when governments treat AI like a silver bullet for complex problems. The documents also highlight the need for more transparency about safeguards against inappropriate, AI-driven denials. The public still lacks the information needed to assess whether clinician review is providing meaningful oversight of AI systems and whether appropriate data is being used to evaluate prior authorization requests. 

EFF has long argued that AI has no place in consequential government decisions about peoples’ rights or access to benefits, such as immigration enforcement and policing decisions. That’s because using automated decision-making in these contexts risks decisions that violate people’s rights or deprive them of benefits they’re entitled to based on biased or inappropriate considerations and without proper due process or accountability if there is an error. 

By outsourcing decision-making to private AI companies without sufficient transparency, testing, or legal limits, WISeR jeopardizes seniors’ access to medical care. Congress should step in to place greater legal limits on the use of automated decision-making in Medicare. 

WISeR’s Rollout Was Rushed and Rocky 

CMS launched the WISeR program just six months after announcing it, ignoring calls from medical providers to delay its rollout. In records previously released by EFF, CMS acknowledged this “extremely condensed timeline.” 

New records suggest that WISeR’s unusually rapid rollout contributed to widespread problems in the first few months of the program. CMS did not disclose the extent of these issues to the public, even as agency employees privately contacted vendors about potential noncompliance with program requirements. 

In the first three months of the program, CMS sent RFIs or requests for CAPs to at least four of the six WISeR vendors. These requests, which describe delays, technical failures, and a lack of communication with providers, suggest that widespread problems during the program’s rollout were not limited to one vendor or state. 

These letters underscore the severity of the problems with the program. For example, CMS requested information from one vendor, Virtix, about numerous reported issues, including “determination turnaround times that exceed established guidelines,” “denials that appear inaccurate or inconsistent with applicable criteria,” and “inadequate customer service.” CMS’s RFI to Zyter–a vendor that uses Palantir software infrastructure–observed that the agency had received reports that “Zyter is not issuing determination letters in a timely manner” and communications indicating that it “may lack adequate processes for responding to and escalating provider/supplier concerns.” The vendor Innovaccer received two CAP requests and a “Performance Notice of Non-Compliance” over its failure to implement a fully functional portal for WISeR providers and suppliers.

Excerpts from CMS’ letters to vendors describe problems during WISeR’s rollout:

Excerpt from the RFI for Virtix, March 17, 2026

Excerpt from the RFI for Zyter, February 27, 2026

Excerpt from the Performance Notice of Non-Compliance for Innovaccer, February 20, 2026

Vendors’ responses to CMS provide further evidence that WISeR’s rushed rollout contributed to its problems. Innovaccer claimed it warned CMS months in advance that it might not be ready to provide full portal functionality by the launch date, even before signing a Participation Agreement. Another vendor claimed that “technical and workflow stabilization challenges were encountered due to the compressed implementation timeframe” it faced after joining the WISeR program a month after the other vendors. 

Excerpt from Innovaccer’s Proposed CAP, January 16, 2026

The issues reflected in CMS’s letters to vendors, and the vendors’ responses, illustrate the risks of deploying automated decision-making systems without proper testing or safeguards. While vendors’ responses describe fixes for the problems CMS identified, after-the-fact remedies cannot undo the harms that patients and providers already experienced during WISeR’s rushed rollout. 

More Transparency Needed About AI Safeguards

The public still knows far too little about any safeguards that WISeR vendors may have adopted—in part because the government chose to conceal some of this information. Transparency about these safeguards is critical to protecting patients, especially because WISeR’s payment structure gives vendors, as the government put it, “an incentive to deny as many claims as possible.” 

 Information provided by a vendor about safeguards that it says "ensure the responsible and clinically appropriate application of automation” appears to have been redacted from records released to EFF

The public has limited means to evaluate the effectiveness of even the safeguards that weren’t redacted from records released to EFF. For example, one vendor’s application touts safeguards like “Human-in-the-loop (HITL) workflows,” “Continuous model monitoring,” and “Transparent audit trails.” Yet it remains unclear whether these measures effectively prevent improper prior authorization denials. Some evidence suggests they may not: the company denied more requests than it approved in the first few months of the program, and CMS inquired about “denials that appear inaccurate or inconsistent with applicable criteria.”

Ultimately, the records obtained by EFF raise more questions than they answer about the safeguards used by WISeR vendors. 

Having a Human in the Loop Is Probably Not Enough

CMS has emphasized having a human in the loop as a key safeguard against inappropriate, AI-driven denials. The WISeR FAQ page on the CMS website states that “Non-affirmations will require the review of a human clinician and cannot be performed solely by technology.” But whether human review provides any meaningful protection depends on the details of its implementation, such as whether human reviewers have enough time to evaluate requests and practical authority to override AI recommendations. We still lack many of those details for WISeR vendors. 

A growing body of scholarship points to the substantial limitations of “human in the loop” policies as guardrails for AI systems. AI-generated recommendations can unduly influence human decisions, leading reviewers to over-rely on automated judgements and rubber stamp them as correct. Even worse, at least one health insurance company actively pressured clinical reviewers to accept its AI systems’ recommendations. Another company built a system that allowed clinical reviewers to reject claims without opening patient files; clinical reviewers using this system spent an average of just 1.2 seconds on each case.

Is the Right Kind of Data Informing Companies’ Decisions?

Some WISeR vendors’ applications offer general descriptions of the types of data informing their decisions. But far more details are needed to allow medical professionals to assess whether the data inputs to these AI systems are appropriate for evaluating prior authorization requests. 

Inappropriate training data or input data can lead to biased, unfair, or inaccurate decisions. CMS guidance for Medicare Advantage organizations using AI to make coverage decisions emphasizes the importance of basing decisions on individual patients’ circumstances. It cautions against using “an algorithm that determines coverage based on a larger data set instead of the individual patient's medical history, the physician’s recommendations, or clinical notes.” 

WISeR vendors’ applications reference data sources like “provider behavior,” “patient demographics,” “utilization management datasets,” “provider and payer performance metrics,” and “historical claims data.” Whether these sources could introduce bias or give too much weight to population-level patterns depends on how vendors use them to inform individual decisions. But we don’t yet have these important details about vendors’ data and algorithms. By outsourcing decision-making to private companies’ AI systems, the government has made it harder for the public to evaluate whether decisions are being made fairly.

Next Steps

As the government expands its use of automated decision-making, the potential for consequential mistakes increases rapidly. The records we’ve obtained so far raise questions about the rushed rollout and lack of guardrails for automated decision-making by the U.S. government. EFF urges transparency, oversight, and legal limits to protect people from the harms of automated decision-making in high risk systems.  

Related Cases: EFF v. CMS

At any given moment, a U.S. Air Force pilot may be maneuvering an aircraft mid-mission, a U.S. Navy officer resurfacing a submarine after weeks undersea, or a U.S. Army technician offloading drone data in a combat zone. Each operation depends on satellite communications (satcom) and, specifically, on cryptographic keys that allow terminals to communicate securely while keeping adversaries locked out.

At the scale of modern operations, managing these keys is a technical challenge. Every terminal needs to have the right keys at the right time, quickly and securely, and if any keys are compromised, they need to be refreshed without leaving out devices that may be offline, disconnected, or under attack.

MIT Lincoln Laboratory researchers have now solved this challenge with the Protected Anti-Jam Tactical Satcom (PATS) Key Management System (KMS) Prototype. This new architecture enables keys to refresh rapidly across terminals dispersed worldwide, even in contested or bandwidth-constrained environments.

"We're enabling the nation to achieve highly assured, highly available communications. Even when adversaries know where forces are operating and are trying to stop them from communicating, they're unable to do so, because we've built in smarts across this entire system to keep talking,” says Joseph Sobchuk, a principal investigator of the PATS KMS Prototype program and researcher in the Secure Resilient Systems and Technology Group.

This architecture is being adopted as the cryptographic backbone of the U.S. Space Force's next-generation satcom system, PATS. The KMS Prototype serves as the gold-standard reference implementation for the industry-built operational KMS, which will be integrated across the PATS ecosystem, encompassing satellites, user terminals on military platforms, and ground-based communication hubs.

Developed under sponsorship of the Space Force’s Space Systems Command (SSC), the KMS Prototype reflects Lincoln Laboratory's end-to-end approach to technology development, from shaping the core key-management concepts to putting them into practice in a prototype to transitioning a technical baseline to government and industry. For this transitioned innovation, the SSC and Lincoln Laboratory team received a 2025 R&D 100 Award, recognizing the KMS Prototype among the year’s most impactful new technologies.

Managing key challenges

Cryptographic keys are foundational to secure communications. These keys, strings of random characters used by cryptographic algorithms, help protect communications by encrypting data and supporting protected transmission patterns, such as frequency hopping. Without key protection, the communications sent and received by terminals are more susceptible to eavesdropping and interference.

Historically, operators manually uploaded keys to terminals before missions. More recently, some systems have supported over-the-air key updates, but bandwidth constraints, security concerns, and operational complexity have limited real-time, wide-scale refresh.  

"Key management is the linchpin that turns advanced, anti-jam hardware and waveforms into a usable mission capability," says Roger Khazan, leader of the Secure Resilient Systems and Technology Group. "Without a scalable way to deliver the right keys to the right systems at the right time, protected satcom cannot operate reliably across a dynamic force."

One primary threat to satcom is signal jamming, where adversaries flood specific frequencies with noise. To resist jamming, PATS uses frequency hopping, in which signals jump rapidly between frequencies in a pattern that looks random to anyone without the key. This hopping only works when every legitimate terminal holds current keys and stays in sync. Keeping all those terminals correctly keyed is the KMS's job. "Designing a system to handle that coordination efficiently, without breaking the conversation, is incredibly difficult," Sobchuk says.

Maintaining synchronization becomes even more critical when devices are compromised. Terminals share keying material so they can communicate as a group and follow protected hopping patterns. If an adversary captures a device, such as a downed drone, and extracts its keys, the exposure can extend beyond that one device. Depending on what keying material is exposed, an adversary may gain access to protected communications or help a jammer follow the hopping pattern. Restoring security means refreshing keys for legitimate terminals — including those that may be offline or operating in contested conditions — while locking the captured device out.

But here's the catch: To send new keys, you need to establish a secure link to terminals, and to establish a secure link, terminals need valid keys. This situation creates a long-standing "chicken-or-egg" problem for key management.

Solving the chicken-or-egg problem

Lincoln Laboratory's solution is a hybrid key distribution method using a "pull-and-push" approach. Each month, each terminal "pulls" a package of keys tailored to that terminal over the satcom link. Then, daily, the satellite "pushes" a smaller key to every terminal. The monthly keys encrypt the daily keys, creating layered security. The daily key determines the unpredictable frequency-hopping patterns. Even if an adversary captures today's key, tomorrow's will be different, and encrypted to exclude them.

"This way of sending keys hadn't existed before," Sobchuk says, adding that Lincoln Laboratory researchers have been pioneering this key-management technology for more than a decade. "The combination of pull and push, monthly and daily, is the magic behind all of it."

This hybrid approach also solves the issue of leaving out devices that were disconnected during a key refresh. For instance, if a submarine submerges for six months, it can request keys for the entire period in advance. Even if keys are refreshed while it's offline, the submarine can immediately reconnect when it resurfaces because the monthly keys provide access to the daily key.

"Submarine crews want to log on to the satellite and talk right away, not wait to get back to shore for new keys. They want to turn on their system and have it work," Sobchuk says.

Monthly and daily key broadcasts must reach thousands of devices spanning the globe. To enable this large-scale sharing, the team adapted theoretical algorithms from academia to create the first operational-scale implementation of broadcast encryption for such a protected satcom application. Broadcast encryption is a method for securely sending information to many users at once. These algorithms encrypt each daily key using just a small subset of keys instead of separately encrypting the daily key for every terminal. This implementation preserves communication bandwidth that would otherwise be consumed just by sending keys.

"The point isn't just stronger cryptography. It's making secure communications usable at operational scale, in contested conditions, without imposing a crippling burden on the warfighters and operators who depend on them," says Sean O'Melia, an assistant leader in the Secure Resilient Systems and Technology Group.

Transitioning to operations

Lincoln Laboratory has transitioned the KMS Prototype to multiple government and industry partners developing PATS components across service branches. To facilitate this coordination, the team has supported dozens of integration events and produced in-depth technical documentation. The prototype is allowing developers to test and validate their components while defense contractors build the operational version of KMS.

The laboratory's work is also enabling contractors to achieve National Security Agency (NSA) certification of end cryptographic units (ECUs), the hardware devices within a terminal that transmit, receive, or store keys. Last year, the first PATS ECU — the space-hub ECU that goes on the satellite — earned NSA certification. Achieving this certification is an arduous process requiring proof that the design, implementation, and supporting processes are all secure.

After years of work, the team is grateful to have helped lay a foundation for the future of secure satcom, both through the KMS Prototype and the larger PATS technical vision, Khazan says. The effort brought together expertise from across the laboratory’s Cyber Security and Information Sciences Division and Communication Systems Division.

"PATS KMS is the kind of problem Lincoln Laboratory was built to solve: high-risk research, rigorous engineering, and transition into a national-security capability. Working with Space Systems Command and the PATS community, our team helped turn advanced key-management ideas into a technical baseline that industry can build on and the government can use. The result is a more-resilient satcom architecture that can scale across a complex operational ecosystem," he says.