More than 600 undergraduate students crowded into the Stratton Student Center on Oct. 28, for MIT’s first-ever Institute-wide Undergraduate Research Opportunities Program (UROP) mixer.

“At MIT, we believe in the transformative power of learning by doing, and there’s no better example than UROP,” says MIT President Sally Kornbluth, who attended the mixer with Provost Anantha Chandrakasan and Chancellor Melissa Nobles. “The energy at the inaugural UROP mixer was exhilarating, and I’m delighted that students now have this easy way to explore different paths to the frontiers of research.”

The event gave students the chance to explore internships and undergraduate research opportunities — in fields ranging from artificial intelligence to the life sciences to the arts, and beyond — all in one place, with approximately 150 researchers from labs available to discuss the projects and answer questions in real time. The offices of the Chancellor and Provost co-hosted the event, which the UROP office helped coordinate. 

First-year student Isabell Luo recently began a UROP project in the Living Matter lab led by Professor Rafael Gómez-Bombarelli, where she is benchmarking machine-learned interatomic potentials that simulate chemical reactions at the molecular level and exploring fine-tuning strategies to improve their accuracy. She’s passionate about AI and machine learning, eco-friendly design, and entrepreneurship, and was attending the UROP mixer to find more “real-world” projects to work on.

“I’m trying to dip my toes into different areas, which is why I’m at the mixer,” said Luo. “On the internet it would be so hard to find the right opportunities. It’s nice to have a physical space and speak to people from so many disciplines.”

More than nine out of every 10 members of MIT’s class of 2025 took part in a UROP before graduating. In recent years, approximately 3,200 undergraduates have participated in a UROP project each year. To meet the strong demand for UROPs, the Institute will commit up to $1 million in funding this year to create more of them. The funding will come from MIT’s schools and Office of the Provost. 

“UROPs have become an indispensable part of the MIT undergraduate education, providing hands-on experience that really helps students learn new ways to problem-solve and innovate,” says Chandrakasan. “I was thrilled to see so many students at the mixer — it was a testament to their willingness to roll up their sleeves and get to work on really tough challenges.”

Arielle Berman, a postdoc in the Raman Lab, was looking to recruit an undergraduate researcher for a project on sensor integration for muscle actuators for biohybrid robots — robots that include living parts. She spoke about how her own research experience as an undergraduate had shaped her career.

“It’s a really important event because we’re able to expose undergraduates to research,” says Berman. “I’m the first PhD in my family, so I wasn’t aware that research existed, or could be a career. Working in a research lab as an undergraduate student changed my life trajectory, and I’m happy to pass it forward and help students have experiences they wouldn’t have otherwise.”

The event drew students with interests as varied as the projects available. For first-year Nate Black, who plans to major in mechanical engineering, “I just wanted something to develop my interest in 3D printing and additive manufacturing.” First-year Akpandu Ekezie, who expects to major in Course 6-5 (Electrical Engineering with Computing), was interested in photonic circuits. “I’m looking mainly for EE-related things that are more hands-on,” he explained. “I want to get more physical experience.”

Nobles has a message for students considering a UROP project: Just go for it. “There’s a UROP for every student, regardless of experience,” she says. “Find something that excites you and give it a try.” She encourages students who weren’t able to attend the mixer, as well as those who did attend but still have questions, to get in touch with the UROP office.

First-year students Ruby Mykkanen and Aditi Deshpande attended the mixer together. Both were searching for UROP projects they could work on during Independent Activities Period in January. Deshpande also noted that the mixer was helpful for understanding “what research is being done at MIT.”

Said Mykkanen, “It’s fun to have it all in one place!”

Imagine having a continuum soft robotic arm bend around a bunch of grapes or broccoli, adjusting its grip in real time as it lifts the object. Unlike traditional rigid robots that generally aim to avoid contact with the environment as much as possible and stay far away from humans for safety reasons, this arm senses subtle forces, stretching and flexing in ways that mimic more of the compliance of a human hand. Its every motion is calculated to avoid excessive force while achieving the task efficiently. In MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) and Laboratory for Information and Decisions Systems (LIDS) labs, these seemingly simple movements are the culmination of complex mathematics, careful engineering, and a vision for robots that can safely interact with humans and delicate objects.

Soft robots, with their deformable bodies, promise a future where machines move more seamlessly alongside people, assist in caregiving, or handle delicate items in industrial settings. Yet that very flexibility makes them difficult to control. Small bends or twists can produce unpredictable forces, raising the risk of damage or injury. This motivates the need for safe control strategies for soft robots. 

“Inspired by advances in safe control and formal methods for rigid robots, we aim to adapt these ideas to soft robotics — modeling their complex behavior and embracing, rather than avoiding, contact — to enable higher-performance designs (e.g., greater payload and precision) without sacrificing safety or embodied intelligence,” says lead senior author and MIT Assistant Professor Gioele Zardini, who is a principal investigator in LIDS and the Department of Civil and Environmental Engineering, and an affiliate faculty with the Institute for Data, Systems, and Society (IDSS). “This vision is shared by recent and parallel work from other groups.”

Safety first

The team developed a new framework that blends nonlinear control theory (controlling systems that involve highly complex dynamics) with advanced physical modeling techniques and efficient real-time optimization to produce what they call “contact-aware safety.” At the heart of the approach are high-order control barrier functions (HOCBFs) and high-order control Lyapunov functions (HOCLFs). HOCBFs define safe operating boundaries, ensuring the robot doesn’t exert unsafe forces. HOCLFs guide the robot efficiently toward its task objectives, balancing safety with performance.

“Essentially, we’re teaching the robot to know its own limits when interacting with the environment while still achieving its goals,” says MIT Department of Mechanical Engineering PhD student Kiwan Wong, the lead author of a new paper describing the framework. “The approach involves some complex derivation of soft robot dynamics, contact models, and control constraints, but the specification of control objectives and safety barriers is rather straightforward for the practitioner, and the outcomes are very tangible, as you see the robot moving smoothly, reacting to contact, and never causing unsafe situations.”

“Compared with traditional kinematic CBFs — where forward-invariant safe sets are hard to specify — the HOCBF framework simplifies barrier design, and its optimization formulation accounts for system dynamics (e.g., inertia), ensuring the soft robot stops early enough to avoid unsafe contact forces,” says Worcester Polytechnic Institute Assistant Professor and former CSAIL postdoc Wei Xiao.

“Since soft robots emerged, the field has highlighted their embodied intelligence and greater inherent safety relative to rigid robots, thanks to passive material and structural compliance. Yet their “cognitive” intelligence — especially safety systems — has lagged behind that of rigid serial-link manipulators,” says co-lead author Maximilian Stölzle, a research intern at Disney Research and formerly a Delft University of Technology PhD student and visiting researcher at MIT LIDS and CSAIL. “This work helps close that gap by adapting proven algorithms to soft robots and tailoring them for safe contact and soft-continuum dynamics.”

The LIDS and CSAIL team tested the system on a series of experiments designed to challenge the robot’s safety and adaptability. In one test, the arm pressed gently against a compliant surface, maintaining a precise force without overshooting. In another, it traced the contours of a curved object, adjusting its grip to avoid slippage. In yet another demonstration, the robot manipulated fragile items alongside a human operator, reacting in real time to unexpected nudges or shifts. “These experiments show that our framework is able to generalize to diverse tasks and objectives, and the robot can sense, adapt, and act in complex scenarios while always respecting clearly defined safety limits,” says Zardini.

Soft robots with contact-aware safety could be a real value-add in high-stakes places, of course. In health care, they could assist in surgeries, providing precise manipulation while reducing risk to patients. In industry, they might handle fragile goods without constant supervision. In domestic settings, robots could help with chores or caregiving tasks, interacting safely with children or the elderly — a key step toward making soft robots reliable partners in real-world environments. 

“Soft robots have incredible potential,” says co-lead senior author Daniela Rus, director of CSAIL and a professor in the Department of Electrical Engineering and Computer Science. “But ensuring safety and encoding motion tasks via relatively simple objectives has always been a central challenge. We wanted to create a system where the robot can remain flexible and responsive while mathematically guaranteeing it won’t exceed safe force limits.”

Combining soft robot models, differentiable simulation, and control theory

Underlying the control strategy is a differentiable implementation of something called the Piecewise Cosserat-Segment (PCS) dynamics model, which predicts how a soft robot deforms and where forces accumulate. This model allows the system to anticipate how the robot’s body will respond to actuation and complex interactions with the environment. “The aspect that I most like about this work is the blend of integration of new and old tools coming from different fields like advanced soft robot models, differentiable simulation, Lyapunov theory, convex optimization, and injury-severity–based safety constraints. All of this is nicely blended into a real-time controller fully grounded in first principles,” says co-author Cosimo Della Santina, who is an associate professor at Delft University of Technology. 

Complementing this is the Differentiable Conservative Separating Axis Theorem (DCSAT), which estimates distances between the soft robot and obstacles in the environment that can be approximated with a chain of convex polygons in a differentiable manner. “Earlier differentiable distance metrics for convex polygons either couldn’t compute penetration depth — essential for estimating contact forces — or yielded non-conservative estimates that could compromise safety,” says Wong. “Instead, the DCSAT metric returns strictly conservative, and therefore safe, estimates while simultaneously allowing for fast and differentiable computation.” Together, PCS and DCSAT give the robot a predictive sense of its environment for more proactive, safe interactions.

Looking ahead, the team plans to extend their methods to three-dimensional soft robots and explore integration with learning-based strategies. By combining contact-aware safety with adaptive learning, soft robots could handle even more complex, unpredictable environments. 

“This is what makes our work exciting,” says Rus. “You can see the robot behaving in a human-like, careful manner, but behind that grace is a rigorous control framework ensuring it never oversteps its bounds.”

“Soft robots are generally safer to interact with than rigid-bodied robots by design, due to the compliance and energy-absorbing properties of their bodies,” says University of Michigan Assistant Professor Daniel Bruder, who wasn’t involved in the research. “However, as soft robots become faster, stronger, and more capable, that may no longer be enough to ensure safety. This work takes a crucial step towards ensuring soft robots can operate safely by offering a method to limit contact forces across their entire bodies.”

The team’s work was supported, in part, by The Hong Kong Jockey Club Scholarships, the European Union’s Horizon Europe Program, Cultuurfonds Wetenschapsbeurzen, and the Rudge (1948) and Nancy Allen Chair. Their work was published earlier this month in the Institute of Electrical and Electronics Engineers’ Robotics and Automation Letters.

Researchers at MIT have demonstrated that wedge-shaped vortex generators attached to a ship’s hull can reduce drag by up to 7.5 percent, which reduces overall ship emissions and fuel expenses. The paper, “Net Drag Reduction in High Block Coefficient Ships and Vehicles Using Vortex Generators,” was presented at the Society of Naval Architects and Marine Engineers 2025 Maritime Convention in Norfolk, Virginia.

The work offers a promising path toward decarbonization, addressing the pressing need to meet the International Maritime Organization (IMO) goal to reduce carbon intensity of international shipping by at least 40 percent by 2030, compared to 2008 levels. Achieving such ambitious emissions reduction will require a coordinated approach, employing multiple methods, from redesigning ship hulls, propellers, and engines to using novel fuels and operational methods.

The researchers — José del Águila Ferrandis, Jack Kimmeth, and Michael Triantafyllou of MIT Sea Grant and the Department of Mechanical Engineering, along with Alfonso Parra Rubio and Neil Gershenfeld of the Center for Bits and Atoms — determined the optimized vortex generator shape and size using a combination of computational fluid dynamics (CFD) and experimental methods guided by AI optimization methods. 

The team first established parametric trends through extensive CFD analysis, and then tested multiple hulls through rapid prototyping to validate the results experimentally. Scale models of an axisymmetric hull with a bare tail, a tail with delta wing vortex generators, and a tail with wedge vortex generators were produced and tested. The team identified wedge-like vortex generators as the key shape that could achieve this level of drag reduction. 

Through flow visualization, the researchers could see that drag was reduced by delaying turbulent flow separation, helping water flow more smoothly along the ship’s hull, shrinking the wake behind the vessel. This also allows the propeller and rudder to work more efficiently in a uniform flow. “We document for the first time experimentally a reduction in fuel required by ships using vortex generators, relatively small structures in the shape of a wedge attached at a specific point of the ship’s hull,” explains Michael Triantafyllou, professor of mechanical engineering and director of MIT Sea Grant. 

Vortex generators have long been used in aircraft-wing design to maintain lift and delay stalling. This study is the first to show that the vortex generators can be applied for drag reduction in commercial ships.

The modular adaptability of the wedge vortex generators would allow integration into a broad range of hull forms, including bulk carriers and tankers, and the devices can synergize with, or even replace, existing technologies like pre-swirl stators (fixed fins mounted in front of propellers), improving overall system performance. As an example case, the researchers estimate that installing the vortex generators on a 300-meter Newcastlemax bulk carrier operating at 14.5 knots over a cross-Pacific route would result in significantly reduced emissions and approximately $750,000 in fuel savings per year.

The findings offer a practical, cost-effective solution that could be implemented efficiently across existing fleets. This study was supported through the CBA Consortium, working with Oldendorff Carriers, which operates about 700 bulk carriers around the world. An extension of this research is supported by the MIT Maritime Consortium, led by MIT professors Themis Sapsis and Fotini Christia. The Maritime Consortium was formed in 2025 to address critical gaps in the modernization of the commercial fleet through interdisciplinary research and collaboration across academia, industry, and regulatory agencies.

EFF intern Alexandra Halbeck contributed to this blog

When people talk to a chatbot, they often reveal highly personal information they wouldn’t share with anyone else. Chat logs are digital repositories of our most sensitive and revealing information. They are also tempting targets for law enforcement, to which the U.S. Constitution gives only one answer: get a warrant.

AI companies have a responsibility to their users to make sure the warrant requirement is strictly followed, to resist unlawful bulk surveillance requests, and to be transparent with their users about the number of government requests they receive.

Chat logs are deeply personal, just like your emails.

Tens of millions of people use chatbots to brainstorm, test ideas, and explore questions they might never post publicly or even admit to another person. Whether advisable or not, people also turn to consumer AI companies for medical information, financial advice, and even dating tips. These conversations reveal people’s most sensitive information.

Without privacy protections, users would be chilled in their use of AI systems.

Consider the sensitivity of the following prompts: “how to get abortion pills,” “how to protect myself at a protest,” or “how to escape an abusive relationship.” These exchanges can reveal everything from health status to political beliefs to private grief. A single chat thread can expose the kind of intimate detail once locked away in a handwritten diary.

Without privacy protections, users would be chilled in their use of AI systems for learning, expression, and seeking help.

Chat logs require a warrant.

Whether you draft an email, edit an online document, or ask a question to a chatbot, you have a reasonable expectation of privacy in that information. Chatbots may be a new technology, but the constitutional principle is old and clear. Before the government can rifle through your private thoughts stored on digital platforms, it must do what it has always been required to do: get a warrant.

For over a century, the Fourth Amendment has protected the content of private communications—such as letters, emails, and search engine prompts—from unreasonable government searches. AI prompts require the same constitutional protection.

This protection is not aspirational—it already exists. The Fourth Amendment draws a bright line around private communications: the government must show probable cause and obtain a particularized warrant before compelling a company to turn over your data. Companies like OpenAI acknowledge this warrant requirement explicitly, while others like Anthropic could stand to be more precise.

AI companies must resist bulk surveillance orders.

AI companies that create chatbots should commit to having your back and resisting unlawful bulk surveillance orders. A valid search warrant requires law enforcement to provide a judge with probable cause and to particularly describe the thing to be searched. This means that bulk surveillance orders often fail that test.

What do these overbroad orders look like? In the past decade or so, police have often sought “reverse” search warrants for user information held by technology companies. Rather than searching for one particular individual, police have demanded that companies rummage through their giant databases of personal data to help develop investigative leads. This has included “tower dumps” or “geofence warrants,” in which police order a company to search all users’ location data to identify anyone that’s been near a particular place at a particular time. It has also included “keyword” warrants, which seek to identify any person who typed a particular phrase into a search engine. This could include a chilling keyword search for a well-known politician’s name or busy street, or a geofence warrant near a protest or church.

Courts are beginning to rule that these broad demands are unconstitutional. And after years of complying, Google has finally made it technically difficult—if not impossible—to provide mass location data in response to a geofence warrant.

This is an old story: if a company stores a lot of data about its users, law enforcement (and private litigants) will eventually seek it out. Law enforcement is already demanding user data from AI chatbot companies, and it will only increase. These companies must be prepared for this onslaught, and they must commit to fighting to protect their users.

In addition to minimizing the amount of data accessible to law enforcement, they can start with three promises to their users. These aren’t radical ideas. They are basic transparency and accountability standards to preserve user trust and to ensure constitutional rights keep pace with technology:

1. commit to fighting bulk orders for user data in court,
2. commit to providing users with advanced notice before complying with a legal demand so that users can choose to fight on their own behalf, and 
3. commit to publishing periodic transparency reports, which tally up how many legal demands for user data the company receives (including the number of bulk orders specifically).

U.S. Customs and Border Protection (CBP), the Drug Enforcement Administration (DEA), and scores of state and local law enforcement agencies have installed a massive dragnet of automated license plate readers (ALPRs) in the US-Mexico borderlands. 

In many cases, the agencies have gone out of their way to disguise the cameras from public view. And the problem is only going to get worse: as recently as July 2025, CBP put out a solicitation to purchase 100 more covert trail cameras with license plate-capture ability. 

Last month, the Associated Press published an in-depth investigation into how agencies have deployed these systems and exploited this data to target drivers. But what do these cameras look like? Here's a guide to identifying ALPR systems when you're driving the open road along the border.

Special thanks to researcher Dugan Meyer and AZ Mirror's Jerod MacDonald-Evoy. All images by EFF and Meyer were taken within the last three years. 

ALPR at Checkpoints and Land Ports of Entry 

All land ports of entry have ALPR systems that collect all vehicles entering and exiting the country. They typically look like this: 

ALPR systems at the Eagle Pass International Bridge Port of Entry. Source: EFF

Most interior checkpoints, which are anywhere from a few miles to more than 60 from the border, are also equipped with ALPR systems operated by CBP. However, the DEA operates a parallel system at most interior checkpoints in southern border states. 

When it comes to checkpoints, here's the rule of thumb: If you're traveling away from the border, you are typically being captured by a CBP/Border Patrol system (Border Patrol is a sub-agency of CBP). If you're traveling toward the border, it is most likely a DEA system.

Here's a representative example of a CBP checkpoint camera system:

ALPR system at the Border Patrol checkpoint near Uvalde, Texas. Source: EFF

At a typical port of entry or checkpoint, each vehicle lane will have an ALPR system. We've even seen border patrol checkpoints that were temporarily closed continue to funnel people through these ALPR lanes, even though there was no one on hand to vet drivers face-to-face. According CBP's Privacy Impact Assessments (2017, 2020), CBP keeps this data for 15 years, but generally agents can only search the most recent five years worth of data. 

The scanners were previously made by a company called Perceptics which was infamously hacked, leading to a breach of driver data. The systems have since been "modernized" (i.e. replaced) by SAIC.

Here's a close up of the new systems:

Frontal ALPR camera at the checkpoint near Uvalde, Texas. Source: EFF

In 2024, the DEA announced plans to integrate port of entry ALPRs into its National License Plate Reader Program (NLPRP), which the agency says is a network of both DEA systems and external law enforcement ALPR systems that it uses to investigate crimes such as drug trafficking and bulk cash smuggling.

Again, if you're traveling towards the border and you pass a checkpoint, you're often captured by parallel DEA systems set up on the opposite side of the road. However, these systems have also been found to be installed on their own away from checkpoints. 

These are a major component of the DEA's NLPRP, which has a standard retention period of 90 days. This program dates back to at least 2010, according to records obtained by the ACLU. 

Here is a typical DEA system that you will find installed near existing Border Patrol checkpoints:

DEA ALPR set-up in southern Arizona. Source: EFF

These are typically made by a different vendor, Selex ES, which also includes the brands ELSAG and Leonardo. Here is a close-up:

Close-up of a DEA camera near the Tohono O'odham Nation in Arizona. Source: EFF

Covert ALPR

As you drive along border highways, law enforcement agencies have disguised cameras in order to capture your movements. 

The exact number of covert ALPRs at the border is unknown, but to date we have identified approximately 100 sites. We know CBP and DEA each operate covert ALPR systems, but it isn't always possible to know which agency operates any particular set-up. 

Another rule of thumb: if a covert ALPR has a Motorola Solutions camera (formerly Vigilant Solutions) inside, it's likely a CBP system. If it has a Selex ES camera inside, then it is likely a DEA camera. 

Here are examples of construction barrels with each kind of camera: 

A covert ALPR with a Motorola Solutions ALPR camera near Calexico, Calif. Source: EFF

These are typically seen along the roadside, often in sets of three, but almost always connected to some sort of solar panel. They are often placed behind existing barriers.

A covert ALPR with a Selex ES camera in southern Arizona. Source: EFF

The DEA models are also found by the roadside, but they also can be found inside or near checkpoints. 

If you're curious (as we were), here's what they look like inside, courtesy of the US Patent and Trademark Office:

Patent for portable covert license plate reader. Source: USPTO

In addition to orange construction barrels, agencies also conceal ALPRs in yellow sandbarrels. For example, these can be found throughout southern Arizona, especially in the southeastern part of the state.

A covert ALPR system in Arizona. Source: EFF

ALPR Trailers

Sometimes a speed trailer or signage trailer isn't designed so much for safety but to conceal ALPR systems. Sometimes ALPRs are attached to indistinct trailers with no discernible purpose that you'd hardly notice by the side of the road. 

It's important to note that its difficult to know who these belong to, since they aren't often marked. We know that all levels of government, even in the interior of the country, have purchased these set ups.  

Here are some of the different flavors of ALPR trailers:

An ALPR speed trailer in Texas. Source: EFF

ALPR trailer in Southern California. Source. EFF

ALPR trailer in Southern California. Source. EFF

An ALPR unit in southern Arizona. Source: EFF

ALPR unit in southern Arizona. Source: EFF

A Jenoptik Vector ALPR trailer in La Joya, Texas. Source: EFF

One particularly worrisome version of an ALPR trailer is the Jenoptik Vector: at least two jurisdictions along the border have equipped these trailers not only with ALPR, but with TraffiCatch technology that gathers Bluetooth and Wi-Fi identifiers. This means that in addition to gathering plates, these devices would also document mobile devices, such as phones, laptops, and even vehicle entertainment systems.

Stationary ALPR 

Stationary or fixed ALPR is one of the more traditional ways of installing these systems. The cameras are placed on existing utility poles or other infrastructure or on poles installed by the ALPR vendor. 

For example, here's a DEA system installed on a highway arch:

The lower set of ALPR cameras belong to the DEA. Source: Dugan Meyer CC BY

ALPR camera in Arizona. Source: Dugan Meyer CC BY

Flock Safety

At the local level, thousands of cities around the United States have adopted fixed ALPR, with the company Flock Safety grabbing a huge chunk of the market over the last few years. County sheriffs and municipal police along the border have also embraced the trend, with many using funds earmarked for border security to purchase these systems. Flock allows these agencies to share with one another and contribute their ALPR scans to a national pool of data. As part of a pilot program, Border Patrol had access to this ALPR data for most of 2025. 

A typical Flock Safety setup involves attaching cameras and solar panels to poles. For example:

Flock Safety ALPR poles installed just outside the Tohono O'odham Nation in Arizona. Source: EFF

A close-up of a Flock Safety camera in Douglas, Arizona. Source: EFF

We've also seen these camera poles placed outside the Santa Teresa Border Patrol station in New Mexico.

Flock may now be the most common provider nationwide, but it isn't the only player in the field. DHS recently released a market survey of 16 different vendors providing similar technology.  

Mobile ALPR 

ALPR cameras can also be found attached to patrol cars. Here's an example of a Motorola Solutions ALPR attached to a Hidalgo County Constable vehicle in South Texas:

Mobile ALPR on a Hidalgo County Constable vehicle. Source: Weslaco Police Department

These allow officers not only to capture ALPR data in real time as they are driving along, but they will also receive an in-car alert when a scan matches a vehicle on a "hot list," the term for a list of plates that law enforcement has flagged for further investigation. 

Here's another example: 

Mobile ALPR in La Mesa, Calif.. Source: La Mesa Police Department Facebook page

Identifying Other Technologies 

EFF has been documenting the wide variety of technologies deployed at the border, including surveillance towers, aerostats, and trail cameras. To learn more, download EFF's zine, "Surveillance Technology at the US-Mexico Border" and explore our map of border surveillance, which includes Google Streetview links so you can see exactly how each installation looks on the ground. Currently we have mapped out most DEA and CBP checkpoint ALPR setups, with covert cameras planned for addition in the near future.

In his 2020 book, “Future Politics,” British barrister Jamie Susskind wrote that the dominant question of the 20th century was “How much of our collective life should be determined by the state, and what should be left to the market and civil society?” But in the early decades of this century, Susskind suggested that we face a different question: “To what extent should our lives be directed and controlled by powerful digital systems—and on what terms?”

Artificial intelligence (AI) forces us to confront this question. It is a technology that in theory amplifies the power of its users: A manager, marketer, political campaigner, or opinionated internet user can utter a single instruction, and see their message—whatever it is—instantly written, personalized, and propagated via email, text, social, or other channels to thousands of people within their organization, or millions around the world. It also allows us to individualize solicitations for political donations, elaborate a grievance into a well-articulated policy position, or tailor a persuasive argument to an identity group, or even a single person...

Scientists say global warming can accelerate the spread of microplastics, which threaten the health of people, plants and animals.

Washington state residents say the industry misled consumers about fossil fuel dangers and “precipitated a home-owners insurance crisis."

A state-chartered insurer has started a price war with private insurers that have been raising premiums for owners of condo buildings.

A judge moved the case closer to trial after rejecting the company's request to toss it out.

The case accuses the state of approving fossil fuel projects without considering the effects on climate change and health.

The government says it opposes the cutting-edge and controversial climate technology but is willing to debate its regulation.

Replacing oil and gas with homegrown biomass will boost strategic autonomy and cut emissions, Brussels argues.

Businesses say Brussels got its math wrong on the carbon footprint of imports from China, Brazil and the U.S.

The flooding and landslides killed at least 604 people in Indonesia, 366 in Sri Lanka and 176 in Thailand, authorities said.

Technology can uplift democracy, or it can be an authoritarian weapon. EFF is making sure it stays on the side of freedom. We’re defending encryption, exposing abusive surveillance tech, fighting government overreach, and standing up for free expression. But we need your help to protect digital rights—and right now, your donation will be matched dollar-for-dollar.

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Digital rights are human rights. Governments have silenced online speech, corporations seek to exploit our data for profit, and police are deploying dystopian tools to track our every move. But the fight is far from over, with the support of EFF’s members.

How EFF is fighting back:

• Creating tools to help people understand and protect their rights
• Holding powerful institutions accountable in court when those rights are threatened
• Pushing back against surveillance regimes through the justice system and in legislatures
• Locking arms with attorneys, technologists, and defenders of digital freedom—including you

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Norway is the world’s largest producer of farmed Atlantic salmon and a top exporter of seafood, while the United States remains the largest importer of these products, according to the Food and Agriculture Organization. Two MIT students recently traveled to Trondheim, Norway to explore the cutting-edge technologies being developed and deployed in offshore aquaculture. 

Beckett Devoe, a senior in artificial intelligence and decision-making, and Tony Tang, a junior in mechanical engineering, first worked with MIT Sea Grant through the Undergraduate Research Opportunities Program (UROP). They contributed to projects focusing on wave generator design and machine learning applications for analyzing oyster larvae health in hatcheries. While near-shore aquaculture is a well-established industry across Massachusetts and the United States, open-ocean farming is still a nascent field here, facing unique and complex challenges. 

To help better understand this emerging industry, MIT Sea Grant created a collaborative initiative, AquaCulture Shock, with funding from an Aquaculture Technologies and Education Travel Grant through the National Sea Grant College Program. Collaborating with the MIT-Scandinavia MISTI (MIT International Science and Technology Initiatives) program, MIT Sea Grant matched Devoe and Tang with aquaculture-related summer internships at SINTEF Ocean, one of the largest research institutes in Europe. 

“The opportunity to work on this hands-on aquaculture project, under a world-renowned research institution, in an area of the world known for its innovation in marine technology — this is what MISTI is all about,” says Madeline Smith, managing director for MIT-Scandinavia. “Not only are students gaining valuable experience in their fields of study, but they’re developing cultural understanding and skills that equip them to be future global leaders.” Both students worked within SINTEF Ocean’s Aquaculture Robotics and Autonomous Systems Laboratory (ACE-Robotic Lab), a facility designed to develop and test new aquaculture technologies. 

“Norway has this unique geography where it has all of these fjords,” says Sveinung Ohrem, research manager for the Aquaculture Robotics and Automation Group at SINTEF Ocean. “So you have a lot of sheltered waters, which makes it ideal to do sea-based aquaculture.” He estimates that there are about a thousand fish farms along Norway’s coast, and walks through some of the tools being used in the industry: decision-making systems to gather and visualize data for the farmers and operators; robots for inspection and cleaning; environmental sensors to measure oxygen, temperature, and currents; echosounders that send out acoustic signals to track where the fish are; and cameras to help estimate biomass and fine-tune feeding. “Feeding is a huge challenge,” he notes. “Feed is the largest cost, by far, so optimizing feeding leads to a very significant decrease in your cost.”

During the internship, Devoe focused on a project that uses AI for fish feeding optimization. “I try to look at the different features of the farm — so maybe how big the fish are, or how cold the water is ... and use that to try to give the farmers an optimal feeding amount for the best outcomes, while also saving money on feed,” he explains. “It was good to learn some more machine learning techniques and just get better at that on a real-world project.” 

In the same lab, Tang worked on the simulation of an underwater vehicle-manipulator system to navigate farms and repair damage on cage nets with a robotic arm. Ohrem says there are thousands of aquaculture robots operating in Norway today. “The scale is huge,” he says. “You can’t have 8,000 people controlling 8,000 robots — that’s not economically or practically feasible. So the level of autonomy in all of these robots needs to be increased.”

The collaboration between MIT and SINTEF Ocean began in 2023 when MIT Sea Grant hosted Eleni Kelasidi, a visiting research scientist from the ACE-Robotic Lab. Kelasidi collaborated with MIT Sea Grant director Michael Triantafyllou and professor of mechanical engineering Themistoklis Sapsis developing controllers, models, and underwater vehicles for aquaculture, while also investigating fish-machine interactions. 

“We have had a long and fruitful collaboration with the Norwegian University of Science and Technology (NTNU) and SINTEF, which continues with important efforts such as the aquaculture project with Dr. Kelasidi,” Triantafyllou says. “Norway is at the forefront of offshore aquaculture and MIT Sea Grant is investing in this field, so we anticipate great results from the collaboration.”

Kelasidi, who is now a professor at NTNU, also leads the Field Robotics Lab, focusing on developing resilient robotic systems to operate in very complex and harsh environments. “Aquaculture is one of the most challenging field domains we can demonstrate any autonomous solutions, because everything is moving,” she says. Kelasidi describes aquaculture as a deeply interdisciplinary field, requiring more students with backgrounds both in biology and technology. “We cannot develop technologies that are applied for industries where we don’t have biological components,” she explains, “and then apply them somewhere where we have a live fish or other live organisms.” 

Ohrem affirms that maintaining fish welfare is the primary driver for researchers and companies operating in aquaculture, especially as the industry continues to grow. “So the big question is,” he says, “how can you ensure that?” SINTEF Ocean has four research licenses for farming fish, which they operate through a collaboration with SalMar, the second-largest salmon farmer in the world. The students had the opportunity to visit one of the industrial-scale farms, Singsholmen, on the island of Hitra. The farm has 10 large, round net pens about 50 meters across that extend deep below the surface, each holding up to 200,000 salmon. “I got to physically touch the nets and see how the [robotic] arm might be able to fix the net,” says Tang. 

Kelasidi emphasizes that the information gained in the field cannot be learned from the office or lab. “That opens up and makes you realize, what is the scale of the challenges, or the scale of the facilities,” she says. She also highlights the importance of international and institutional collaboration to advance this field of research and develop more resilient robotic systems. “We need to try to target that problem, and let’s solve it together.”

MIT Sea Grant and the MIT-Scandinavia MISTI program are currently recruiting a new cohort of four MIT students to intern in Norway this summer with institutes advancing offshore farming technologies, including NTNU’s Field Robotics Lab in Trondheim. Students interested in autonomy, deep learning, simulation modeling, underwater robotic systems, and other aquaculture-related areas are encouraged to reach out to Lily Keyes at MIT Sea Grant.

Advancements in battery innovation are transforming both mobility and energy systems alike, according to Kurt Kelty, vice president of battery, propulsion, and sustainability at General Motors (GM). At the MIT Energy Initiative (MITEI) Fall Colloquium, Kelty explored how GM is bringing next-generation battery technologies from lab to commercialization, driving American battery innovation forward. The colloquium is part of the ongoing MITEI Presents: Advancing the Energy Transition speaker series.

At GM, Kelty’s team is primarily focused on three things: first, improving affordability to get more electric vehicles (EVs) on the road. “How do you drive down the cost?” Kelty asked the audience. “It's the batteries. The batteries make up about 30 percent of the cost of the vehicle.” Second, his team strives to improve battery performance, including charging speed and energy density. Third, they are working on localizing the supply chain. “We've got to build up our resilience and our independence here in North America, so we're not relying on materials coming from China,” Kelty explained.

To aid their efforts, resources are being poured into the virtualization space, significantly cutting down on time dedicated to research and development. Now, Kelty’s team can do modeling up front using artificial intelligence, reducing what previously would have taken months to a couple of days.

“If you want to modify … the nickel content ever so slightly, we can very quickly model: ‘OK, how’s that going to affect the energy density? The safety? How’s that going to affect the charge capability?’” said Kelty. “We can look at that at the cell level, then the pack level, then the vehicle level.”

Kelty revealed that they have found a solution that addresses affordability, accessibility, and commercialization: lithium manganese-rich (LMR) batteries. Previously, the industry looked to reduce costs by lowering the amount of cobalt in batteries by adding greater amounts of nickel. These high-nickel batteries are in most cars on the road in the United States due to their high range. LMR batteries, though, take things a step further by reducing the amount of nickel and adding more manganese, which drives the cost of batteries down even further while maintaining range.

Lithium-iron-phosphate (LFP) batteries are the chemistry of choice in China, known for low cost, high cycle life, and high safety. With LMR batteries, the cost is comparable to LFP with a range that is closer to high-nickel. “That’s what’s really a breakthrough,” said Kelty.

LMR batteries are not new, but there have been challenges to adopting them, according to Kelty. “People knew about it, but they didn’t know how to commercialize it. They didn’t know how to make it work in an EV,” he explained. Now that GM has figured out commercialization, they will be the first to market these batteries in their EVs in 2028.

Kelty also expressed excitement over the use of vehicle-to-grid technologies in the future. Using a bidirectional charger with a two-way flow of energy, EVs could charge, but also send power from their batteries back to the electrical grid. This would allow customers to charge “their vehicles at night when the electricity prices are really low, and they can discharge it during the day when electricity rates are really high,” he said.

In addition to working in the transportation sector, GM is exploring ways to extend their battery expertise into applications in grid-scale energy storage. “It’s a big market right now, but it’s growing very quickly because of the data center growth,” said Kelty.

When looking to the future of battery manufacturing and EVs in the United States, Kelty remains optimistic: “we’ve got the technology here to make it happen. We’ve always had the innovation here. Now, we’re getting more and more of the manufacturing. We’re getting that all together. We’ve got just tremendous opportunity here that I’m hopeful we’re going to be able to take advantage of and really build a massive battery industry here.”

This speaker series highlights energy experts and leaders at the forefront of the scientific, technological, and policy solutions needed to transform our energy systems. Visit MITEI’s Events page for more information on this and additional events.

“MIT hasn’t just prepared me for the future of work — it’s pushed me to study it. As AI systems become more capable, more of our online activity will be carried out by artificial agents. That raises big questions: How should we design these systems to understand our preferences? What happens when AI begins making many of our decisions?”

These are some of the questions MIT Sloan School of Management PhD candidate Benjamin Manning is researching. Part of his work investigates how to design and evaluate artificial intelligence agents that act on behalf of people, and how their behavior shapes markets and institutions. 

Previously, he received a master’s degree in public policy from the Harvard Kennedy School and a bachelor’s in mathematics from Washington University in St. Louis. After working as a research assistant, Manning knew he wanted to pursue an academic career.

“There’s no better place in the world to study economics and computer science than MIT,” he says. “Nobel and Turing award winners are everywhere, and the IT group lets me explore both fields freely. It was my top choice — when I was accepted, the decision was clear.” 

After receiving his PhD, Manning hopes to secure a faculty position at a business school and do the same type of work that MIT Sloan professors — his mentors — do every day.

“Even in my fourth year, it still feels surreal to be an MIT student. I don’t think that feeling will ever fade. My mom definitely won’t ever get over telling people about it.”

Of his MIT Sloan experience, Manning says he didn’t know it was possible to learn so much so quickly. “It’s no exaggeration to say I learned more in my first year as a PhD candidate than in all four years of undergrad. While the pace can be intense, wrestling with so many new ideas has been incredibly rewarding. It’s given me the tools to do novel research in economics and AI — something I never imagined I’d be capable of.”

As an economist studying AI simulations of humans, for Manning, the future of work not only means understanding how AI acts on our behalf, but also radically improving and accelerating social scientific discovery.

“Another part of my research agenda explores how well AI systems can simulate human responses. I envision a future where researchers test millions of behavioral simulations in minutes, rapidly prototyping experimental designs, and identifying promising research directions before investing in costly human studies. This isn’t about replacing human insight, but amplifying it: Scientists can focus on asking better questions, developing theory, and interpreting results while AI handles the computational heavy lifting.”

He’s excited by the prospect: “We are possibly moving toward a world where the pace of understanding may get much closer to the speed of economic change.”

Our muscles are nature’s actuators. The sinewy tissue is what generates the forces that make our bodies move. In recent years, engineers have used real muscle tissue to actuate “biohybrid robots” made from both living tissue and synthetic parts. By pairing lab-grown muscles with synthetic skeletons, researchers are engineering a menagerie of muscle-powered crawlers, walkers, swimmers, and grippers.

But for the most part, these designs are limited in the amount of motion and power they can produce. Now, MIT engineers are aiming to give bio-bots a power lift with artificial tendons.

In a study appearing today in the journal Advanced Science, the researchers developed artificial tendons made from tough and flexible hydrogel. They attached the rubber band-like tendons to either end of a small piece of lab-grown muscle, forming a “muscle-tendon unit.” Then they connected the ends of each artificial tendon to the fingers of a robotic gripper.

When they stimulated the central muscle to contract, the tendons pulled the gripper’s fingers together. The robot pinched its fingers together three times faster, and with 30 times greater force, compared with the same design without the connecting tendons.

The researchers envision the new muscle-tendon unit can be fit to a wide range of biohybrid robot designs, much like a universal engineering element.

“We are introducing artificial tendons as interchangeable connectors between muscle actuators and robotic skeletons,” says lead author Ritu Raman, an assistant professor of mechanical engineering (MechE) at MIT. “Such modularity could make it easier to design a wide range of robotic applications, from microscale surgical tools to adaptive, autonomous exploratory machines.”

The study’s MIT co-authors include graduate students Nicolas Castro, Maheera Bawa, Bastien Aymon, Sonika Kohli, and Angel Bu; undergraduate Annika Marschner; postdoc Ronald Heisser; alumni Sarah J. Wu ’19, SM ’21, PhD ’24 and Laura Rosado ’22, SM ’25; and MechE professors Martin Culpepper and Xuanhe Zhao.

Muscle’s gains

Raman and her colleagues at MIT are at the forefront of biohybrid robotics, a relatively new field that has emerged in the last decade. They focus on combining synthetic, structural robotic parts with living muscle tissue as natural actuators.

“Most actuators that engineers typically work with are really hard to make small,” Raman says. “Past a certain size, the basic physics doesn’t work. The nice thing about muscle is, each cell is an independent actuator that generates force and produces motion. So you could, in principle, make robots that are really small.”

Muscle actuators also come with other advantages, which Raman’s team has already demonstrated: The tissue can grow stronger as it works out, and can naturally heal when injured. For these reasons, Raman and others envision that muscly droids could one day be sent out to explore environments that are too remote or dangerous for humans. Such muscle-bound bots could build up their strength for unforeseen traverses or heal themselves when help is unavailable. Biohybrid bots could also serve as small, surgical assistants that perform delicate, microscale procedures inside the body.

All these future scenarios are motivating Raman and others to find ways to pair living muscles with synthetic skeletons. Designs to date have involved growing a band of muscle and attaching either end to a synthetic skeleton, similar to looping a rubber band around two posts. When the muscle is stimulated to contract, it can pull the parts of a skeleton together to generate a desired motion.

But Raman says this method produces a lot of wasted muscle that is used to attach the tissue to the skeleton rather than to make it move. And that connection isn’t always secure. Muscle is quite soft compared with skeletal structures, and the difference can cause muscle to tear or detach. What’s more, it is often only the contractions in the central part of the muscle that end up doing any work — an amount that’s relatively small and generates little force.

“We thought, how do we stop wasting muscle material, make it more modular so it can attach to anything, and make it work more efficiently?” Raman says. “The solution the body has come up with is to have tendons that are halfway in stiffness between muscle and bone, that allow you to bridge this mechanical mismatch between soft muscle and rigid skeleton. They’re like thin cables that wrap around joints efficiently.”

“Smartly connected”

In their new work, Raman and her colleagues designed artificial tendons to connect natural muscle tissue with a synthetic gripper skeleton. Their material of choice was hydrogel — a squishy yet sturdy polymer-based gel. Raman obtained hydrogel samples from her colleague and co-author Xuanhe Zhao, who has pioneered the development of hydrogels at MIT. Zhao’s group has derived recipes for hydrogels of varying toughness and stretch that can stick to many surfaces, including synthetic and biological materials.

To figure out how tough and stretchy artificial tendons should be in order to work in their gripper design, Raman’s team first modeled the design as a simple system of three types of springs, each representing the central muscle, the two connecting tendons, and the gripper skeleton. They assigned a certain stiffness to the muscle and skeleton, which were previously known, and used this to calculate the stiffness of the connecting tendons that would be required in order to move the gripper by a desired amount.

From this modeling, the team derived a recipe for hydrogel of a certain stiffness. Once the gel was made, the researchers carefully etched the gel into thin cables to form artificial tendons. They attached two tendons to either end of a small sample of muscle tissue, which they grew using lab-standard techniques. They then wrapped each tendon around a small post at the end of each finger of the robotic gripper — a skeleton design that was developed by MechE professor Martin Culpepper, an expert in designing and building precision machines.

When the team stimulated the muscle to contract, the tendons in turn pulled on the gripper to pinch its fingers together. Over multiple experiments, the researchers found that the muscle-tendon gripper worked three times faster and produced 30 times more force compared to when the gripper is actuated just with a band of muscle tissue (and without any artificial tendons). The new tendon-based design also was able to keep up this performance over 7,000 cycles, or muscle contractions.

Overall, Raman saw that the addition of artificial tendons increased the robot’s power-to-weight ratio by 11 times, meaning that the system required far less muscle to do just as much work.

“You just need a small piece of actuator that’s smartly connected to the skeleton,” Raman says. “Normally, if a muscle is really soft and attached to something with high resistance, it will just tear itself before moving anything. But if you attach it to something like a tendon that can resist tearing, it can really transmit its force through the tendon, and it can move a skeleton that it wouldn’t have been able to move otherwise.”

The team’s new muscle-tendon design successfully merges biology with robotics, says biomedical engineer Simone Schürle-Finke, associate professor of health sciences and technology at ETH Zürich.

“The tough-hydrogel tendons create a more physiological muscle–tendon–bone architecture, which greatly improves force transmission, durability, and modularity,” says Schürle-Finke, who was not involved with the study. “This moves the field toward biohybrid systems that can operate repeatably and eventually function outside the lab.”

With the new artificial tendons in place, Raman’s group is moving forward to develop other elements, such as skin-like protective casings, to enable muscle-powered robots in practical, real-world settings.

This research was supported, in part, by the U.S. Department of Defense Army Research Office, the MIT Research Support Committee, and the National Science Foundation.