If you’re a Californian, there are a few new state laws that you should know will be going into effect in the new year. EFF has worked hard in Sacramento this session to advance bills that protect privacy, fight surveillance, and promote transparency.

California’s legislature runs in a two-year cycle, meaning that it’s currently halftime for legislators. As we prepare for the next year of the California legislative session in January, it’s a good time to showcase what’s happened so far—and what’s left to do.

Wins Worth Celebrating

In a win for every Californian’s privacy rights, we were happy to support A.B. 566 (Assemblymember Josh Lowenthal). This is a common-sense law that makes California’s main consumer data privacy law, the California Consumer Privacy Act, more user-friendly. It requires that browsers support people’s rights to send opt-out signals, such as the global opt-out in Privacy Badger, to businesses. Managing your privacy as an individual can be a hard job, and EFF wants stronger laws that make it easier for you to do so.

Additionally, we were proud to advance government transparency by supporting A.B. 1524 (Judiciary Committee), which allows members of the public to make copies of public court records using their own devices, such as cell-phone cameras and overhead document scanners, without paying fees.

We also supported two bills that will improve law enforcement accountability at a time when we desperately need it. S.B. 627 (Senator Scott Wiener) prohibits law enforcement officers from wearing masks to avoid accountability (The Trump administration has sued California over this law). We also supported S.B. 524 (Asm. Jesse Arreguín), which requires law enforcement to disclose when a police report was written using artificial intelligence.

On the To-Do List for Next Year

On the flip side, we also stopped some problematic bills from becoming law. This includes S.B. 690 (Sen. Anna Caballero), which we dubbed the Corporate Coverup Act. This bill would have gutted California’s wiretapping statute by allowing businesses to ignore those privacy rights for “any business purpose.” Working with several coalition partners, we were able to keep that bill from moving forward in 2025. We do expect to see it come back in 2026, and are ready to fight back against those corporate business interests.

And, of course, not every fight ended in victory. There are still many areas where we have work left to do. California Governor Gavin Newsom vetoed a bill we supported, S.B. 7, which would have given workers in California greater transparency into how their employers use artificial intelligence and was sponsored by the California Federation of Labor Unions. S.B. 7  was vetoed in response to concerns from companies including Uber and Lyft, but we expect to continue working with the labor community on the ways AI affects the workplace in 2026.

Trends of Note

California continued a troubling years-long trend of lawmakers pushing problematic proposals that would require every internet user to verify their age to access information—often by relying on privacy-invasive methods to do so. Earlier this year EFF sent a letter to the California legislature expressing grave concerns with lawmakers’ approach to regulating young people’s ability to speak online. We continue to raise these concerns, and would welcome working with any lawmaker in California on a better solution.

We also continue to keep a close eye on government data sharing. On this front, there is some good news. Several of the bills we supported this year sought to place needed safeguards on the ways various government agencies in California share data. These include: A.B. 82 (Asm. Chris Ward) and S.B. 497 (Wiener), which would add privacy protections to data collected by the state about those who may be receiving gender-affirming or reproductive health care; A.B. 1303 (Asm. Avelino Valencia), which prohibits warrantless data sharing from California’s low-income broadband program to immigration and other government officials; and S.B. 635 (Sen. Maria Elena Durazo), which places similar limits on data collected from sidewalk vendors.

We are also heartened to see California correct course on broad government data sharing. Last session, we opposed A.B. 518 (Asm. Buffy Wicks), which let state agencies ignore existing state privacy law to allow broader information sharing about people eligible for CalFresh—the state’s federally funded food assistance program. As we’ve seen, the federal government has since sought data from food assistance programs to use for other purposes. We were happy to have instead supported A.B. 593 this year, also authored by Asm. Wicks—which reversed course on that data sharing.

We hope to see this attention to the harms of careless government data sharing continue. EFF’s sponsored bill this year, A.B. 1337, would update and extend vital privacy safeguards present at the state agency level to counties and cities. These local entities today collect enormous amounts of data and administer programs that weren’t contemplated when the original law was written in 1977. That information should be held to strong privacy standards.

We’ve been fortunate to work with Asm. Chris Ward, who is also the chair of the LGBTQ Caucus in the legislature, on that bill. The bill stalled in the Senate Judiciary Committee during the 2025 legislative session, but we plan to bring it back in the next session with a renewed sense of urgency.

The National Academy of Inventors (NAI) has named nine MIT affiliates as members of the 2025 class of NAI Fellows. They include Ahmad Bahai, an MIT professor of the practice in the Department of Electrical Engineering and Computer Science (EECS), and Kripa K. Varanasi, MIT professor in the Department of Mechanical Engineering, as well as seven additional MIT alumni. NAI fellowship is the highest professional distinction awarded solely to inventors. 

“NAI Fellows are a driving force within the innovation ecosystem, and their contributions across scientific disciplines are shaping the future of our world,” says Paul R. Sanberg, fellow and president of the National Academy of Inventors. “We are thrilled to welcome this year’s class of fellows to the academy.”

This year’s 169 U.S. fellows represent 127 universities, government agencies, and research institutions across 40 U.S. states. Together, the 2025 class hold more than 5,300 U.S. patents and include recipients of the Nobel Prize, the National Medal of Science and National Medal of Technology and Innovation, as well as members of the national academies of Sciences, Engineering, and Medicine, among others. 

Ahmad Bahai is professor of the practice in EECS. He was an adjunct professor at Stanford University from 2017 to 2022 and a professor in residence at the University of California at Berkeley from 2001 to 2010. Bahai has held a number of leadership roles, including director of research labs and chief technology officer of National Semiconductor, technical manager of a research group at Bell Laboratories, and founder of Algorex, a communication and acoustic integrated circuit and system company, which was acquired by National Semiconductor. 

Currently, Bahai is the chief technology officer and director of corporate research of Texas Instruments and director of Kilby Labs and corporate research, and is a member of the Industrial Advisory Committee of CHIPS Act. Bahai is an IEEE Fellow and an AIMBE Fellow; he has authored over 80 publications in IEEE/IEE journals and holds more than 40 patents related to systems and circuits.

He holds an MS in electrical engineering from Imperial College London and a doctorate degree in electrical engineering from UC Berkeley.

Kripa K. Varanasi SM ’02, PhD ’04, professor of mechanical engineering, is widely recognized for his significant contributions in the field of interfacial science, thermal fluids, electrochemical systems, advanced materials, and manufacturing. A member of the MIT faculty since 2009, he leads the interdisciplinary Varanasi Research Group, which focuses on understanding physico-chemical and biological phenomena at the interfaces of matter. His group develops innovative surfaces, materials, devices, processes, and associated technologies that improve efficiency and performance across industries, including energy, decarbonization, life sciences, water, agriculture, transportation, and consumer products. 

Varanasi has also scaled basic research into practical, market-ready technologies. He has co-founded six companies, including AgZen, Alsym Energy, CoFlo Medical, Dropwise, Infinite Cooling, and LiquiGlide, and his companies have been widely recognized for driving innovation across a range of industries. Throughout his career, Varanasi has been recognized for excellence in research and mentorship. Honors include the National Science Foundation CAREER Award, DARPA Young Faculty Award, SME Outstanding Young Manufacturing Engineer Award, ASME’s Bergles-Rohsenow Heat Transfer Award and Gustus L. Larson Memorial Award, Boston Business Journal’s 40 Under 40, and MIT’s Frank E. Perkins Award for Excellence in Graduate Advising​.

Varanasi earned his undergraduate degree in mechanical engineering from the Indian Institute of Technology Madras, and his master’s degree and PhD from MIT. Prior to joining the faculty, he served as lead researcher and project leader at the GE Global Research Center, where he received multiple internal awards for innovation, leadership, and technical excellence​. He was recently named faculty director of the Deshpande Center for Technological Innovation. 

The seven additional MIT alumni who were elected to the NAI for 2025 include:

• Robert William Brown PhD ’68 (Physics);
• André DeHon ’90, SM ’93, PhD ’96 (Electrical Engineering and Computer Science);
• Shanhui Fan PhD ’97 (Physics);
• Jun O. Liu PhD ’90 (Chemistry);
• Marios-Christos Papaefthymiou SM ’90, PhD ’93 (Electrical Engineering and Computer Science);
• Darryll J. Pines SM ’88, PhD ’92 (Mechanical Engineering); and
• Yasha Yi PhD ’04 (Physics).

The NAI Fellows program was founded in 2012 and has grown to include 2,253 distinguished researchers and innovators, who hold over 86,000 U.S. patents and 20,000 licensed technologies. Collectively, NAI Fellows’ innovations have generated an estimated $3.8 trillion in revenue and 1.4 million jobs. 

The 2025 class will be honored and presented with their medals by a senior official of the United States Patent and Trademark Office at the NAI 15th Annual Conference on June 4, 2026, in Los Angeles.

What if there were a way to solve one of the most significant obstacles to the use of nuclear energy — the disposal of high-level nuclear waste (HLW)? Dauren Sarsenbayev, a third-year doctoral student at the MIT Department of Nuclear Science and Engineering (NSE), is addressing the challenge as part of his research.

Sarsenbayev focuses on one of the primary problems related to HLW: decay heat released by radioactive waste. The basic premise of his solution is to extract the heat from spent fuel, which simultaneously takes care of two objectives: gaining more energy from an existing carbon-free resource while decreasing the challenges associated with storage and handling of HLW. “The value of carbon-free energy continues to rise each year, and we want to extract as much of it as possible,” Sarsenbayev explains.

While the safe management and disposal of HLW has seen significant progress, there can be more creative ways to manage or take advantage of the waste. Such a move would be especially important for the public’s acceptance of nuclear energy. “We’re reframing the problem of nuclear waste, transforming it from a liability to an energy source,” Sarsenbayev says.

The nuances of nuclear

Sarsenbayev had to do a bit of reframing himself in how he perceived nuclear energy. Growing up in Almaty, the largest city in Kazakhstan, the collective trauma of Soviet nuclear testing loomed large over the public consciousness. Not only does the country, once a part of the Soviet Union, carry the scars of nuclear weapon testing, Kazakhstan is the world’s largest producer of uranium. It’s hard to escape the collective psyche of such a legacy.

At the same time, Sarsenbayev saw his native Almaty choking under heavy smog every winter, due to the burning of fossil fuels for heat. Determined to do his part to accelerate the process of decarbonization, Sarsenbayev gravitated to undergraduate studies in environmental engineering at Kazakh-German University. It was during this time that Sarsenbayev realized practically every energy source, even the promising renewable ones, came with challenges, and decided nuclear was the way to go for its reliable, low-carbon power. “I was exposed to air pollution from childhood; the horizon would be just black. The biggest incentive for me with nuclear power was that as long as we did it properly, people could breathe cleaner air,” Sarsenbayev says.

Studying transport of radionuclides

Part of “doing nuclear properly” involves studying — and reliably predicting — the long-term behavior of radionuclides in geological repositories.

Sarsenbayev discovered an interest in studying nuclear waste management during an internship at Lawrence Berkeley National Laboratory as a junior undergraduate student.

While at Berkeley, Sarsenbayev focused on modeling the transport of radionuclides from the nuclear waste repository’s barrier system to the surrounding host rock. He discovered how to use the tools of the trade to predict long-term behavior. “As an undergrad, I was really fascinated by how far in the future something could be predicted. It’s kind of like foreseeing what future generations will encounter,” Sarsenbayev says.

The timing of the Berkeley internship was fortuitous. It was at the laboratory that he worked with Haruko Murakami Wainwright, who was herself getting started at MIT NSE. (Wainwright is the Mitsui Career Development Professor in Contemporary Technology, and an assistant professor of NSE and of civil and environmental engineering).

Looking to pursue graduate studies in the field of nuclear waste management, Sarsenbayev followed Wainwright to MIT, where he has further researched the modeling of radionuclide transport. He is the first author on a paper that details mechanisms to increase the robustness of models describing the transport of radionuclides. The work captures the complexity of interactions between engineered barrier components, including cement-based materials and clay barriers, the typical medium proposed for the storage and disposal of spent nuclear fuel.

Sarsenbayev is pleased with the results of the model’s prediction, which closely mirrors experiments conducted at the Mont Terri research site in Switzerland, famous for studies in the interactions between cement and clay. “I was fortunate to work with Doctor Carl Steefel and Professor Christophe Tournassat, leading experts in computational geochemistry,” he says.

Real-life transport mechanisms involve many physical and chemical processes, the complexities of which increase the size of the computational model dramatically. Reactive transport modeling — which combines the simulation of fluid flow, chemical reactions, and the transport of substances through subsurface media — has evolved significantly over the past few decades. However, running accurate simulations comes with trade-offs: The software can require days to weeks of computing time on high-performance clusters running in parallel.

To arrive at results faster by saving on computing time, Sarsenbayev is developing a framework that integrates AI-based “surrogate models,” which train on simulated data and approximate the physical systems. The AI algorithms make predictions of radionuclide behavior faster and less computationally intensive than the traditional equivalent.

Doctoral research focus

Sarsenbayev is using his modeling expertise in his primary doctoral work as well — in evaluating the potential of spent nuclear fuel as an anthropogenic geothermal energy source. “In fact, geothermal heat is largely due to the natural decay of radioisotopes in Earth’s crust, so using decay heat from spent fuel is conceptually similar,” he says. A canister of nuclear waste can generate, under conservative assumptions, the energy equivalent of 1,000 square meters (a little under a quarter of an acre) of solar panels.

Because the potential for heat from a canister is significant — a typical one (depending on how long it was cooled in the spent fuel pool) has a temperature of around 150 degrees Celsius — but not enormous, extracting heat from this source makes use of a process called a binary cycle system. In such a system, heat is extracted indirectly: the canister warms a closed water loop, which in turn transfers that heat to a secondary low-boiling-point fluid that powers the turbine.

Sarsenbayev’s work develops a conceptual model of a binary-cycle geothermal system powered by heat from high-level radioactive waste. Early modeling results have been published and look promising. While the potential for such energy extraction is at the proof-of-concept stage in modeling, Sarsenbayev is hopeful that it will find success when translated to practice. “Converting a liability into an energy source is what we want, and this solution delivers,” he says.

Despite work being all-consuming — “I’m almost obsessed with and love my work” — Sarsenbayev finds time to write reflective poetry in both Kazakh, his native language, and Russian, which he learned growing up. He’s also enamored by astrophotography, taking pictures of celestial bodies. Finding the right night sky can be a challenge, but the canyons near his home in Almaty are an especially good fit. He goes on photography sessions whenever he visits home for the holidays, and his love for Almaty shines through. “Almaty means 'the place where apples originated.' This part of Central Asia is very beautiful; although we have environmental pollution, this is a place with a rich history,” Sarsenbayev says.

Sarsenbayev is especially keen on finding ways to communicate both the arts and sciences to future generations. “Obviously, you have to be technically rigorous and get the modeling right, but you also have to understand and convey the broader picture of why you’re doing the work, what the end goal is,” he says. Through that lens, the impact of Sarsenbayev’s doctoral work is significant. The end goal? Removing the bottleneck for nuclear energy adoption by producing carbon-free power and ensuring the safe disposal of radioactive waste.

All starting from the same DNA, neurons ultimately take on individual characteristics in the brain and body. Differences in which genes they transcribe into RNA help determine which type of neuron they become, and from there, a new MIT study shows, individual cells edit a selection of sites in those RNA transcripts, each at their own widely varying rates.

The new study surveyed the whole landscape of RNA editing in more than 200 individual cells commonly used as models of fundamental neural biology: tonic and phasic motor neurons of the fruit fly. One of the main findings is that most sites were edited at rates between the “all-or-nothing” extremes many scientists have assumed based on more limited studies in mammals, says senior author Troy Littleton, the Menicon Professor in the MIT departments of Biology and Brain and Cognitive Sciences. The resulting dataset and open-access analyses, recently published in eLife, set the table for discoveries about how RNA editing affects neural function and what enzymes implement those edits.

“We have this ‘alphabet’ now for RNA editing in these neurons,” Littleton says. “We know which genes are edited in these neurons, so we can go in and begin to ask questions as to what is that editing doing to the neuron at the most interesting targets.”

Andres Crane PhD ’24, who earned his doctorate in Littleton’s lab based on this work, is the study’s lead author.

From a genome of about 15,000 genes, Littleton and Crane’s team found, the neurons made hundreds of edits in transcripts from hundreds of genes. For example, the team documented “canonical” edits of 316 sites in 210 genes. Canonical means that the edits were made by the well-studied enzyme ADAR, which is also found in mammals, including humans. Of the 316 edits, 175 occurred in regions that encode the contents of proteins. Analysis indeed suggested 60 are likely to significantly alter amino acids. But they also found 141 more editing sites in areas that don’t code for proteins but instead affect their production, which means they could affect protein levels, rather than their contents.

The team also found many “non-canonical” edits that ADAR didn’t make. That’s important, Littleton says, because that information could aid in discovering more enzymes involved in RNA editing, potentially across species. That, in turn, could expand the possibilities for future genetic therapies.

“In the future, if we can begin to understand in flies what the enzymes are that make these other non-canonical edits, it would give us broader coverage for thinking about doing things like repairing human genomes where a mutation has broken a protein of interest,” Littleton says.

Moreover, by looking specifically at fly larvae, the team found many edits that were specific to juveniles, versus adults, suggesting potential significance during development. And because they looked at full gene transcripts of individual neurons, the team was also able to find editing targets that had not been cataloged before.

Widely varying rates

Some of the most heavily edited RNAs were from genes that make critical contributions to neural circuit communication such as neurotransmitter release, and the channels that cells form to regulate the flow of chemical ions that vary their electrical properties. The study identified 27 sites in 18 genes that were edited more than 90 percent of the time.

Yet neurons sometimes varied quite widely in whether they would edit a site, which suggests that even neurons of the same type can still take on significant degrees of individuality.

“Some neurons displayed ~100 percent editing at certain sites, while others displayed no editing for the same target,” the team wrote in eLife. “Such dramatic differences in editing rate at specific target sites is likely to contribute to the heterogeneous features observed within the same neuronal population.”

On average, any given site was edited about two-thirds of the time, and most sites were edited within a range well between all-or-nothing extremes.

“The vast majority of editing events we found were somewhere between 20 percent and 70 percent,” Littleton says. “We were seeing mixed ratios of edited and unedited transcripts within a single cell.”

Also, the more a gene was expressed, the less editing it experienced, suggesting that ADAR could only keep up so much with its editing opportunities.

Potential impacts on function

One of the key questions the data enables scientists to ask is what impact RNA edits have on the function of the cells. In a 2023 study, Littleton’s lab began to tackle this question by looking at just two edits they found in the most heavily edited gene: complexin. Complexin’s protein product restrains release of the neurotransmitter glutamate, making it a key regulator of neural circuit communication. They found that by mixing and matching edits, neurons produced up to eight different versions of the protein with significant effects on their glutamate release and synaptic electrical current. But in the new study, the team reports 13 more edits in complexin that are yet to be studied.

Littleton says he’s intrigued by another key protein, called Arc1, that the study shows experienced a non-canonical edit. Arc is a vitally important gene in “synaptic plasticity,” which is the property neurons have of adjusting the strength or presence of their “synapse” circuit connections in response to nervous system activity. Such neural nimbleness is hypothesized to be the basis of how the brain can responsively encode new information in learning and memory. Notably, Arc1 editing fails to occur in fruit flies that model Alzheimer’s disease.

Littleton says the lab is now working hard to understand how the RNA edits they’ve documented affect function in the fly motor neurons.

In addition to Crane and Littleton, the study’s other authors are Michiko Inouye and Suresh Jetti.

The National Institutes of Health, The Freedom Together Foundation, and The Picower Institute for Learning and Memory provided support for the study.

A number of advanced energy technologies — including fuel cells, electrolyzers, and an emerging class of low-power electronics — use protons as the key charge carrier. Whether or not these devices will be widely adopted hinges, in part, on how efficiently they can move protons.

One class of materials known as metal oxides has shown promise in conducting protons at temperatures above 400 degrees Celsius. But researchers have struggled to find the best materials to increase the proton conductivity at lower temperatures and improve efficiency.

Now, MIT researchers have developed a physical model to predict proton mobility across a wide range of metal oxides. In a new paper, the researchers ranked the most important features of metal oxides for facilitating proton conduction, and demonstrated for the first time how much the flexibility of the materials’ oxide ions improves their ability to transfer protons.

The researchers believe their findings can guide scientists and engineers as they develop materials for more efficient energy technologies enabled by protons, which are lighter, smaller, and more abundant than more common charge carriers like lithium ions.

“If you understand the mechanism of a process and what material traits govern that mechanism, then you can tune those traits to improve the speed of that process — in this case, proton conduction,” says Bilge Yildiz, the Breen M. Kerr Professor in the departments of Nuclear Science and Engineering (NSE) and Materials Science and Engineering (DMSE) at MIT and the senior author of a paper describing the work. “For this application, we need to understand these quantitative relations between the proton transfer and the material’s structural, chemical, electronic, and dynamic traits. Establishing these relations can help us screen material databases to find compounds that satisfy those material traits, or even go beyond screening. There could be ways to use generative AI tools to create compounds that optimize for those traits.”

The paper appears in the journal Matter. Joining Yildiz are Heejung W. Chung, the paper’s first author and an MIT PhD student in DMSE; Pjotrs Žguns, a former postdoc in DMSE; and Ju Li, the Carl Richard Soderberg Professor of Power Engineering in NSE and DMSE.

Making protons hop

Protons are already used at scale in electrolyzers for hydrogen production and in fuel cells. They are also expected to be used in promising energy-storage technologies such as proton batteries, which could be water-based and rely on cheaper materials than lithium-ion batteries. A more recent and exciting application is low-energy, brain-inspired computing to emulate synaptic functions in devices for artificial intelligence.

“Proton conductors are important materials in different energy conversion technologies for clean electricity, clean fuels, and clean industrial chemical synthesis,” explains Yildiz. “Inorganic, scalable proton conductors that work at room temperature are also needed for energy-efficient brain-inspired computing.”

Protons, which are the positively charged state of hydrogen, are different from lithium or sodium ions because they don’t have their own electrons — protons consist of just the bare nucleus. Therefore, protons prefer to embed into the electron clouds of nearby ions, hopping from one to the next. In metal oxides, protons embed into oxygen ions, forming a covalent bond, and hop to a nearby oxygen ion through a hydrogen bond. After every hop, the covalent H-O bond rotates to prevent the proton from shuttling back and forth.

All that hopping and rotating got MIT’s researchers thinking that the flexibility of those oxide ion sublattices must be important for conducting protons. Indeed, their previous studies in another class of proton conductors had shown how lattice flexibility impacts proton transport.

For their study, the researchers created a metric to quantify lattice flexibility across materials that they call “O…O fluctuation,” which measures the change in spacing between oxygen ions contributed by phonons at finite temperature. They also created a dataset of other material features that influence proton mobility and set out to quantify how important each one is for facilitating proton conduction.

“We were trying to better understand how protons move through these inorganic materials so that we can optimize them and improve the efficiency of downstream energy and computing applications,” Chung explains.

The researchers ranked the importance of all seven features they studied, which also included structural and chemical traits of materials, and trained a model on the findings to predict how well materials would conduct protons. The model found that the two most important features in predicting proton transfer barriers are the hydrogen bond length and the oxygen sublattice flexibility characterized by the O…O fluctuation metric. The shorter the hydrogen bond length, the better the material was at transporting protons, which aligned with previous studies of metal oxides. The researchers’ O…O fluctuation metric was the new and the second most important feature they studied. The more flexible the oxygen ion chains, the better the proton conduction.

Better proton conductors

The researchers believe their model could be used to estimate proton conduction across a broader range of materials.

“We always have to be cautious about generalizing findings, but the local chemistries and structures we studied have a wide enough spectrum that we think this finding is broadly applicable to a range of inorganic proton conductors,” Yildiz says.

Beyond being used to screen for promising materials, the researchers say their findings could also be used to train generative AI models to create materials optimized for proton transfer. As our understanding of materials improves, that could enable a new class of hyper-efficient clean energy technologies.

“There are very large materials databases generated recently in the field, for example those by Google and Microsoft, that could be screened for these relations we’ve found,” Yildiz says. “If the material compound that satisfies these parameters does not exist, we could also use these parameters to generate new compounds. That would enable increases in the energy efficiency and viability of clean energy conversion and low-power computing devices. For that, we need to figure out how to get more flexible oxide ion sublattices that are percolated. What are the composition and structure metrics that I can use to design the material to have that flexibility? Those are the next steps.”

The research was supported by the U.S. Department of Energy’s Energy Frontier Center – Hydrogen in Energy and Information Sciences – and the National Science Foundation’s Graduate Research Fellowship Program.

Since the Online Safety Act took effect in late July, UK internet users have made it very clear to their politicians that they do not want anything to do with this censorship regime. Just days after age checks came into effect, VPN apps became the most downloaded on Apple's App Store in the UK, and a petition calling for the repeal of the Online Safety Act (OSA) hit over 400,000 signatures. 

In the months since, more than 550,000 people have petitioned Parliament to repeal or reform the Online Safety Act, making it one of the largest public expressions of concern about a UK digital law in recent history. The OSA has galvanized swathes of the UK population, and it’s high time for politicians to take that seriously. 

Last week, EFF joined Open Rights Group, Big Brother Watch, and Index on Censorship in sending a briefing to UK politicians urging them to listen to their constituents and repeal the Online Safety Act ahead of this week’s Parliamentary petition debate on 15 December.

The legislation is a threat to user privacy, restricts free expression by arbitrating speech online, exposes users to algorithmic discrimination through face checks, and effectively blocks millions of people without a personal device or form of ID from accessing the internet. The briefing highlights how, in the months since the OSA came into effect, we have seen the legislation:

1. Make it harder for not-for-profits and community groups to run their own websites. 
2. Result in the wrong types of content being taken down.
3. Lead to age-assurance being applied widely to all sorts of content.

Our briefing continues:

“Those raising concerns about the Online Safety Act are not opposing child safety. They are asking for a law that does both: protects children and respects fundamental rights, including children’s own freedom of expression rights.”

The petition shows that hundreds of thousands of people feel the current Act tilts too far, creating unnecessary risks for free expression and ordinary online life. With sensible adjustments, Parliament can restore confidence that online safety and freedom of expression rights can coexist.

If the UK really wants to achieve its goal of being the safest place in the world to go online, it must lead the way in introducing policies that actually protect all users—including children—rather than pushing the enforcement of legislation that harms the very people it was meant to protect.

Read the briefing in full here.

Cast your mind back to May of this year: Congress was in the throes of debate over the massive budget bill. Amidst the many seismic provisions, Senator Ted Cruz dropped a ticking time bomb of tech policy: a ten-year moratorium on the ability of states to regulate artificial intelligence. To many, this was catastrophic. The few massive AI companies seem to be swallowing our economy whole: their energy demands are overriding household needs, their data demands are overriding creators’ copyright, and their products are triggering mass unemployment as well as new types of clinical ...

The DOE report by climate contrarians has caused legal problems for Administrator Lee Zeldin's attempts to roll back the scientific finding.

The green light came months after Democratic Gov. Bob Ferguson chastised the president for denying the state's past disaster aid requests.

Power plant operators in 10 Northeast states are paying more to comply with regional emissions standards after Gov. Josh Shapiro’s decision.

Gov. Wes Moore announced a bid to analyze emissions costs and whether companies should compensate the state for climate impacts.

The state purchased $5 million in the cryptocurrency to begin filling its new Strategic Bitcoin Reserve.

The measure responds to cities and an environmental group that challenged provisions meant to spur rebuilding after hurricanes.

Policymakers are poised to approve a road map for energy policy that doesn’t achieve mandated emissions cuts.

The hurricane killed at least 43 people across Haiti, many of them in Petit-Goâve, where residents are still digging out from under the storm.

Flooding has displaced more than 375,000 people this year in South Sudan, one of the most vulnerable countries to global warming.

During early development, tissues and organs begin to bloom through the shifting, splitting, and growing of many thousands of cells.

A team of MIT engineers has now developed a way to predict, minute by minute, how individual cells will fold, divide, and rearrange during a fruit fly’s earliest stage of growth. The new method may one day be applied to predict the development of more complex tissues, organs, and organisms. It could also help scientists identify cell patterns that correspond to early-onset diseases, such as asthma and cancer.

In a study appearing today in the journal Nature Methods, the team presents a new deep-learning model that learns, then predicts, how certain geometric properties of individual cells will change as a fruit fly develops. The model records and tracks properties such as a cell’s position, and whether it is touching a neighboring cell at a given moment.

The team applied the model to videos of developing fruit fly embryos, each of which starts as a cluster of about 5,000 cells. They found the model could predict, with 90 percent accuracy, how each of the 5,000 cells would fold, shift, and rearrange, minute by minute, during the first hour of development, as the embryo morphs from a smooth, uniform shape into more defined structures and features.

“This very initial phase is known as gastrulation, which takes place over roughly one hour, when individual cells are rearranging on a time scale of minutes,” says study author Ming Guo, associate professor of mechanical engineering at MIT. “By accurately modeling this early period, we can start to uncover how local cell interactions give rise to global tissues and organisms.”

The researchers hope to apply the model to predict the cell-by-cell development in other species, such zebrafish and mice. Then, they can begin to identify patterns that are common across species. The team also envisions that the method could be used to discern early patterns of disease, such as in asthma. Lung tissue in people with asthma looks markedly different from healthy lung tissue. How asthma-prone tissue initially develops is an unknown process that the team’s new method could potentially reveal.

“Asthmatic tissues show different cell dynamics when imaged live,” says co-author and MIT graduate student Haiqian Yang. “We envision that our model could capture these subtle dynamical differences and provide a more comprehensive representation of tissue behavior, potentially improving diagnostics or drug-screening assays.”

The study’s co-authors are Markus Buehler, the McAfee Professor of Engineering in MIT’s Department of Civil and Environmental Engineering; George Roy and Tomer Stern of the University of Michigan; and Anh Nguyen and Dapeng Bi of Northeastern University.

Points and foams

Scientists typically model how an embryo develops in one of two ways: as a point cloud, where each point represents an individual cell as point that moves over time; or as a “foam,” which represents individual cells as bubbles that shift and slide against each other, similar to the bubbles in shaving foam.

Rather than choose between the two approaches, Guo and Yang embraced both.

“There’s a debate about whether to model as a point cloud or a foam,” Yang says. “But both of them are essentially different ways of modeling the same underlying graph, which is an elegant way to represent living tissues. By combining these as one graph, we can highlight more structural information, like how cells are connected to each other as they rearrange over time.”

At the heart of the new model is a “dual-graph” structure that represents a developing embryo as both moving points and bubbles. Through this dual representation, the researchers hoped to capture more detailed geometric properties of individual cells, such as the location of a cell’s nucleus, whether a cell is touching a neighboring cell, and whether it is folding or dividing at a given moment in time.

As a proof of principle, the team trained the new model to “learn” how individual cells change over time during fruit fly gastrulation.

“The overall shape of the fruit fly at this stage is roughly an ellipsoid, but there are gigantic dynamics going on at the surface during gastrulation,” Guo says. “It goes from entirely smooth to forming a number of folds at different angles. And we want to predict all of those dynamics, moment to moment, and cell by cell.”

Where and when

For their new study, the researchers applied the new model to high-quality videos of fruit fly gastrulation taken by their collaborators at the University of Michigan. The videos are one-hour recordings of developing fruit flies, taken at single-cell resolution. What’s more, the videos contain labels of individual cells’ edges and nuclei — data that are incredibly detailed and difficult to come by.

“These videos are of extremely high quality,” Yang says. “This data is very rare, where you get submicron resolution of the whole 3D volume at a pretty fast frame rate.”

The team trained the new model with data from three of four fruit fly embryo videos, such that the model might “learn” how individual cells interact and change as an embryo develops. They then tested the model on an entirely new fruit fly video, and found that it was able to predict with high accuracy how most of the embryo’s 5,000 cells changed from minute to minute.

Specifically, the model could predict properties of individual cells, such as whether they will fold, divide, or continue sharing an edge with a neighboring cell, with about 90 percent accuracy.

“We end up predicting not only whether these things will happen, but also when,” Guo says. “For instance, will this cell detach from this cell seven minutes from now, or eight? We can tell when that will happen.”

The team believes that, in principle, the new model, and the dual-graph approach, should be able to predict the cell-by-cell development of other multiceullar systems, such as more complex species, and even some human tissues and organs. The limiting factor is the availability of high-quality video data.

“From the model perspective, I think it’s ready,” Guo says. “The real bottleneck is the data. If we have good quality data of specific tissues, the model could be directly applied to predict the development of many more structures.”

This work is supported, in part, by the U.S. National Institutes of Health.

Nature Climate Change, Published online: 15 December 2025; doi:10.1038/s41558-025-02513-9

Many mountain glaciers will disappear with warming. Here the authors assess how many glaciers will disappear per year under different warming scenarios, finding that a peak in glacier loss will happen during the mid-twenty-first century.

This is a current list of where and when I am scheduled to speak:

• I’m speaking and signing books at the Chicago Public Library in Chicago, Illinois, USA, at 6:00 PM CT on February 5, 2026. Details to come.
• I’m speaking at Capricon 44 in Chicago, Illinois, USA. The convention runs February 5-8, 2026. My speaking time is TBD.
• I’m speaking at the Munich Cybersecurity Conference in Munich, Germany on February 12, 2026.
• I’m speaking at Tech Live: Cybersecurity in New York City, USA on March 11, 2026.
• I’m giving the Ross Anderson Lecture at the University of Cambridge’s Churchill College on March 19, 2026...

I have no context for this video—it’s from Reddit—but one of the commenters adds some context:

Hey everyone, squid biologist here! Wanted to add some stuff you might find interesting.

With so many people carrying around cameras, we’re getting more videos of giant squid at the surface than in previous decades. We’re also starting to notice a pattern, that around this time of year (peaking in January) we see a bunch of giant squid around Japan. We don’t know why this is happening. Maybe they gather around there to mate or something? who knows! but since so many people have cameras, those one-off monster-story encounters are now caught on video, like this one (which, btw, rips. This squid looks so healthy, it’s awesome)...