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

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

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

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

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

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

Overcoming the limits

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

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

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

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

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

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

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

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

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

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

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

Leveraging magnetism

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

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

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

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

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

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

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

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

The bank's goal of steering 45 percent of its financing toward climate projects is being attacked by the White House before it expires at the end of June.

The budget agreement would levy a new, capped tax on the industry's power usage, while preserving its existing tax breaks.

A proposal to send treated water from the oil patch to farmland is drawing pushback from multiple sources.

The future of climate negotiations is uncertain as focus shifts from discussing treaties to actually implementing them.

When possible, relocation should happen before crises occur, the principles state, “with access to skills training, fair employment opportunities, and social integration.”

A lot of the country is witnessing rising day and nighttime temperatures and longer summer months in part due to climate change, and workers say the heat inside factories is unbearable at times.

The tech sector says only carbon-emitting gas plants are reliable enough today to power the EU’s AI goals.

Nature Climate Change, Published online: 22 June 2026; doi:10.1038/s41558-026-02657-2

The authors assess 133 avoided deforestation projects for their ability to safeguard forest ecological integrity. While some projects maintain integrity, most show variable outcomes, with mixed, negligible or negative effects relative to matched controls.

Dolphins, sharks, turtles, and human workers are all victims of unregulated squid fishing fleets.

Another news article.

As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.

Blog moderation policy.

Companies working at the frontier of aerospace, energy, and computing are constantly looking for new materials to improve performance. But in order to understand how those materials will actually behave once they’re inside rockets or on computer chips, companies first have to make the material and then test it. That’s because even the most powerful simulation techniques struggle to model the complex chemical arrangements in most of today’s solid materials. The problem adds costs and time to materials innovation.

Now a team of MIT researchers has created a way to accurately model the behavior of metals, regardless of the complexity of their chemical arrangement. At the center of the approach are machine-learning models that make simulations of materials faster and more accurate. The researchers improved those models by building training datasets that capture the diversity of atomic environments in chemically disordered materials.

In a new paper in Sciences Advances, the researchers showed their approach could be used to accurately predict material properties for a diverse group of metal alloys under a range of conditions. They also showed how the approach could be used to develop new materials, especially in scenarios where experimentation is expensive.

“The focus of the paper is metallic alloys, which is the field I work in, but this could be adapted to other types of materials, like semiconductors,” says senior author Rodrigo Freitas, MIT’s TDK Career Development Professor in Materials Science and Engineering. “This is not specific to any one application — you could use this approach to create new sustainable steels, new materials for aerospace, and more. That’s what makes this exciting.”

Joining Freitas on the paper are first author Killian Sheriff PhD ’26; MIT PhD students Daniel Xiao and Yifan Cao; and University of Sheffield Senior Lecturer Lewis R. Owen.

Modeling metals

Material properties are mostly determined by the internal arrangement of their chemical elements. Even if two materials have the same mix of chemical elements, different chemical arrangements can make the difference between a brittle material and one that deforms without breaking.

Capturing that distinction requires simulating materials atom by atom. To do that, researchers rely on models that describe how atoms interact with each other. Over the last two decades, machine learning has become the most accurate way to build those models. Such models work well when the chemical arrangements inside materials follow highly ordered patterns, but that’s not the case with most solid materials, whose atomic chemical arrangements are disordered and vary from one region to another.

“The real challenge in our field is modelling these chemically disordered phases,” Freitas says. “Chemical disorder means there’s a huge variety of local chemical environments, which is hard for the machine-learning model to learn. This is a problem because every single metal we use in practice is chemically disordered.”

The problem comes down to a lack of representative training data for those atom-by-atom simulations. The current leading approach for creating such data works by brute force, often requiring more than 100,000 hours of computation to create the training data for a single material. Even then, it does not transfer well when researchers change the material’s composition.

In previous work, Freitas’ group had developed a way to measure the chemical complexity of solid materials by analyzing the frequency and spacing of tiny groups of atoms. For this study, the researchers used that capability to build better training datasets. They used a mathematical approach known as information theory to generate training datasets that capture a wider variety of local chemical environments inside disordered materials. The method works by swapping out atoms from samples to reduce repetition and expose the model to chemical environments it might otherwise miss.

“We kept optimizing the training set so it captured as many different local environments as possible,” Freitas says. “If the same kind of environment showed up many times, we replaced redundant examples with ones the model hadn’t seen before. That makes the training set much more informative because each example adds something new.”

When trained on the researchers’ datasets, the models predicted material properties more accurately than models trained using random sampling or another popular sampling method.

“The starting point for all these atom-by-atom simulations is: Are you able to accurately describe the chemical bond between atoms?” Freitas explains. “If not, it can still teach you about materials in general, but it doesn’t tell you what will happen to specific materials in the real world. This approach makes the simulations high fidelity in terms of their chemistry, to better reflect what’s happening to materials.”

The researchers applied their technique to create machine-learning training datasets for a group of chemically diverse metal alloys. Using a set of machine-learning models, they showed the models trained on their datasets are more accurate than much larger models created by companies like Google and Microsoft.

“We got to a point where we were convinced it worked without using these expensive brute-force methods,” Freitas says. “I told Killian, ‘This is a good paper. But if you can show that simulations with these models can now accurately predict useful materials properties, then it becomes a very good paper.’ Killian took that to heart and tested this as widely as he could.”

Sheriff worked with Xiao and Cao to test the approach across different alloys and properties. The team also drew on Owen’s experimental data to compare the simulations against real measurements of atomic ordering in alloys.

From the lab to industry

The method works, in part, by capturing hidden patterns in the sample data. The researchers describe the patterns in the paper as “subtle energetic biases toward certain local chemical configurations.”

Those small energetic differences matter because they determine which phases form in an alloy, how those phases change with temperature and composition, and ultimately which properties the material will have. As one test, Daniel Xiao led simulations showing that the team’s models could predict phase diagrams that closely matched experimental data. Phase diagrams map which phases are stable across different temperatures and chemical compositions, and they are a central tool for designing and processing alloys.

“Phase diagrams are one of the main ways people connect materials modeling to real processing decisions,” Freitas says. “If you are welding, casting, or heat-treating an alloy, you need to know which phases are likely to form under different conditions. Our goal is to make these kinds of predictions accurate enough, and accessible enough, that they become part of how people design materials.”

The researchers are now using the approach to study how changing an alloy’s composition affects mechanical properties and radiation tolerance, with the goal of designing materials that remain strong and damage-tolerant in harsh environments. They are also working to make the method easier to use with the kinds of tools and workflows materials engineers already rely on.

“Industry isn’t going to change the way they do things if what you’re creating doesn’t fit into their existing operating procedures,” Freitas says. “The goal is to make these predictions useful in the places where materials decisions are actually made.”

The research was supported by the U.S. Air Force Office of Scientific Research.

On June 9th, Anthropic released its Fable generative AI model. Three days later, the US government classified it as a dangerous munition, and used its export-control authority to prohibit any foreign nationals from accessing it. Unable to differentiate between Americans and foreigners, the company shut off access for everyone.

The government’s actions won’t help. The problem isn’t any one particular model; it’s the general trend of increasing AI capabilities. And any real solution requires the sort of collective action that just isn’t possible right now...

This week, politicians in the UK pushed forward with plans to eviscerate privacy and free speech on the internet by announcing a ban on social media for users under 16 that is set to take effect in Spring 2027. 

The UK government continues to falsely characterize this policy as a necessary response to growing concerns about online harms for young people. In reality, much like the Online Safety Act, it will cause more harm than it will prevent. 

Users of all ages are burdened with proving their age before accessing content, with social media platforms such as Snapchat, TikTok, YouTube, Instagram, Facebook, and X included in the ban. There remains no reliable, privacy-preserving method of verifying the age of every internet user and methods vary from one platform to the next.

Young people will not simply be protected from being contacted by adults or endlessly scrolling—they’ll also lose access to educational videos on YouTube, local events on Facebook, and potentially cut off from distant friends and family. 

Public policy must be effective, proportionate and respectful of fundamental rights. Young people deserve better than a policy built on panic, and all internet users deserve a safe and free internet. A social media ban generates headlines, but it will not solve the problem. 

A Brief History of Age-Gating in the UK

Age restriction proposals in the UK date back to a decade ago, when the proposed Digital Economy Bill was put forth to (among other things) restrict young people from accessing pornographic websites. While the Digital Economy Act of 2017 passed without age-based restrictions, it laid the groundwork for later age verification measures.

Over the next few years, age checks for porn websites were announced then delayed several times. But it wasn’t until a consultation under the 2016-2019 May government and the 2020 publication of the Online Harms Whitepaper that age verification became a broader idea.

In 2023, the UK passed the controversial Online Safety Act, establishing powers that could weaken privacy protections and freedom of expression for internet users worldwide. In July 2025, the government implemented age assurance measures on sites hosting “harmful” content. 

And despite politicians affirming repeatedly that the Online Safety Act would solve all of the problems with online safety, this year they decided it in fact did not go far enough. American social psychologist and The Anxious Generation author Jonathan Haidt—who has called for age-related social media bans around the world, despite significant scientific doubt about his research—met with the UK Health Secretary in February to push for the ban.

In March, politicians introduced plans for a social media ban into the Children’s Wellbeing and Schools Bill to “prevent children under the age of 16 from becoming or being users” of “all regulated user-to-user services,” to be implemented by “highly-effective age assurance measures”—effectively banning under-16s from social media. 

When this proposal came before the House of Commons, MPs defeated and proposed their own amendment: enabling the Secretary of State to introduce provisions “requiring providers of specified internet services” to prevent access by children, under age 18 rather than 16, to specified internet services or to specified features; and to restrict access by children to specified internet services which ministers provide. 

But the social media ban does not stop there. The provision also requires internet service providers to limit the time kids spend online, and has rules about who can contact them online. These extreme rules will take decisions about using technology away from families and put them in the hands of government regulators. 

The history of this proposal shows that the UK government has repeatedly returned to the same flawed idea: restricting access to online services by requiring age checks for everyone. But the fundamental problems have not changed. There is still no widely available way to verify age online without compromising privacy—but even if there were, broad restrictions on social media will inevitably limit access to lawful speech, and valuable online communities, and arts and culture.

This week, EFF joined Foxglove, Human Rights Watch, and 60 other organizations in writing to the UK’s Minister of State for Border Security and Asylum, Alex Norris, raising serious concern about the Home Office’s decision to deploy Facial Age Estimation (FAE) to assess asylum-seeking children from 2027. 

The letter points to four key concerns:

Discrimination 

As with most face estimation and recognition tools, there is ongoing bias in the deployment of these technologies. With FAE, many have highlighted its baked-in failures and discrimination, particularly in relation to women and people of color. Evidence shows that FAE is most accurate for estimating the ages of Eastern European men, but even then it consistently produces errors. The Home Office itself noted “that FAE performance can vary depending on ethnicity” and skin tone. 

Inaccuracy

The Home Office has admitted that FAE systems are imprecise for analyzing 16-to 18-year-olds, with even the “top systems” having an “error margin of around 2.5 years here.” This is exactly the age range for which the Home Office has chosen to deploy this technology. And this error margin will be widened yet further because children seeking asylum often suffer from trauma-induced aging. 

Lawfulness of Use of Children’s Data

Major concerns exist around the lawful basis on which the Home Office, or its chosen third-party FAE vendors, could have sought consent to collect and process photographs or data from asylum-seeking children to train this system. Further, there is no clarity on the images and/or data that this technology has been trained on. 

Lack of Necessary Disclosure 

The Home Office claims “extensive testing has already been carried out across diverse groups, including different ethnicities, genders and age ranges, indicating promising performance and accuracy.” But these purported “promising” results have not been published, nor have any Equality or Data Protection Impact Assessments. 

The letter continues by requesting clarification on several key questions regarding these concerns. EFF and partners have provided the UK government 21 days for a response, and we urge the Home Office to take on this uphill task in good faith and release the information.

You can read the letter in full here. 

Nature Climate Change, Published online: 19 June 2026; doi:10.1038/s41558-026-02672-3

Ecosystems are changing rapidly because of climate change, and this will have increasing social effects around the globe. We suggest that common social responses to rising novelty are often counterproductive, and we advocate for strategies that also allow for acceptance and adaptation to changes in nature.

Nature Climate Change, Published online: 19 June 2026; doi:10.1038/s41558-026-02665-2

The economic impact of climate change has been widely acknowledged, yet current assessments remain fragmented and uncertain. Researchers develop a comprehensive channel-specific framework, apply it to the UK and show that the potential welfare loss could be much larger than previous estimates.

With no serious debate, including on proposed amendments, Canada is blazing full speed ahead with Bill C-22, which would threaten encryption and increase surveillance. Also known as the Lawful Access Bill, Bill C-22 is currently moving forward quickly to a vote despite the many, many criticisms civil liberty groups and the tech industry have hurled at it.

As we’ve discussed before, Bill C-22 is dangerous on multiple levels. It pushes for requirements for metadata retention, expands information sharing with foreign governments, and establishes a mechanism that allows Canada’s Ministry of Public Safety to demand that companies create backdoors, effectively breaking encryption. That mechanism was a key facet of Part 2 in Bill C-22, and the government prevented it from being independently debated.

In a deep analysis of the bill, Citizen Lab and the Canadian Civil Liberties Association detail every one of flaws of this proposal, concluding that most elements are unsalvageable. 

A wide range of tech companies agree. Signal, Apple, Google, and several VPN providers oppose the bill, and some have said they’d likely be forced to either cut Canadians off from certain features or shut down services in Canada altogether.

The Canadian government wants this dangerous, complicated, overreaching bill passed before June 19. Bill C-22 is riddled with privacy problems that affect millions of people. It should be debated and studied fully, not jammed through on an arbitrary deadline. 

OpenMedia is offering a tool for Canadians to contact their elected representatives about the bill. Actions taken on OpenMedia's website are governed by OpenMedia's privacy policy, not EFF's.

EFF is grateful for SerpApi’s generous support, helping us fight for your rights to speak and access information online. SerpApi has been giving to EFF every year since 2018, and alongside our 32,000 individual donors, their gift is critical to keeping up the fight.

Whether in the courts, halls of power, or broader policy debates, we appreciate the work this support has made possible over the years. Some examples:

• We sued the U.S. Department of Homeland Security and Department of State to stop an unconstitutional social media surveillance program to identify and punish individuals who express viewpoints the government disagrees with.
• We helped develop the Santa Clara Principles, a framework to reign in overbroad content moderation so that all users are treated fairly and offered consistent tools for recourse if their speech is censored by tech companies.
• In the whitepaper Unfiltered: How YouTube’s Content ID Discourages Fair Use and Dictates What We See Online, we pushed back on YouTube for silencing individual creators in the interest of protecting a small number of giant copyright holders.
• We stood with whistleblowers and dissidents persecuted for their online speech.
• We continued the fight to protect Section 230.

We live in an era when lawful speech and the right to access information are being targeted by Big Tech and governments around the world that are hostile to dissent. Free speech online is core to EFF’s mission, and SerpApi’s support will help us continue the fight to protect everyone’s right to free expression.

This Pride season, join EFF and the Queer Arts Collective in building a creative space at the intersection of digital justice and artistic expression. 

We’re looking for fresh, untold, historically censored takes on digital liberation. 

Whether it’s pointing the lens towards an issue you feel is underrepresented in digital justice efforts; sharing personal accounts of joy, pleasure, or sorrow under surveillance; painting your widest imagination for our communities using technology for good instead of carcerality and doom—we want to see it and we want it to expand our own understanding of what’s important and beautiful. 

We’re going to be curating between five and nine art pieces across writing (fiction, nonfiction, poetry) and visual arts (photography, drawing, painting). We welcome fluidity in medium and genre, and cross-genre works of all kinds, such as graphic storytelling and collaborations. 

We are looking for works that convey the importance of digital liberation and ways of achieving it, particularly from under-represented perspectives. Pieces will be selected based on interpretation of the theme, emotional resonance (does it surprise, move, frighten, delight?), and overall curatorial cohesion for each issue. 

Submissions that adhere to the following length guidelines are preferred: 

(NON)FICTION - max 1500 words
POETRY - max 2 poems 
VISUAL ARTS - max 1 artwork, which can be a serialized collection. 

Please submit to paige+pride@eff.org by June 30, 2026, including your piece as an attachment and a short bio in the body of the email, alongside anything else we should know about your submission. You can expect to hear back from us around July 31, and we aim to have the first issue published in September. If we select your submission for publication on both EFF and Queer Arts Collective websites, we will compensate you between $25 - $50, depending on the number of pieces published. 

There is no fee for entry. Please only submit one piece or a contained series for this call, and wait for us to get back to you before submitting again. If you plan to submit both individually and as part of a collective, one submission in each of these categories applies. 

Your submission must be your original work and you must have the legal right to authorize us to publish it, but it need not be created specifically for this project; you may submit a work you have published previously. Please disclose any use of AI in a note in your application—this will not disqualify your entry, though we value transparency of labor exchange. 

As attempting to witness art is a highly subjective endeavor, please don't consider not being selected as anything other than circumstantial. We are looking to foster a community of artists working for digital justice, and would love to see more from you in the future. 

You will retain all legal rights to your work, but agree to provide EFF and Queer Arts Collective with a non-exclusive and non-time-limited license to publish your work on their websites and other promotional materials, such as in zines. 

Meet the Judges

Kit Walsh is an EFF attorney who works to protect the rights of activists, journalists, researchers, and dissenters in order to build a better world. She is also a Nebula-award-winning author and is best known for her tabletop roleplaying game Thirsty Sword Lesbians.

Paige Collings is an EFF activist working to dismantle systems of oppression and advance collective liberation. Her work focuses on highlighting how state surveillance and corporate restrictions stifle marginalized communities and perpetuate historic injustices and harm. She works with activists across the globe to facilitate systemic change by speaking truth to power and creating spaces for alternative imaginations.

The Queer Arts Collective is an NYC-based collective run by queer and racialized artist-activists, looking to make space for art that is deliberately disruptive of structural hierarchies that power the status quo.

Last week, Senators Ted Cruz and Ron Wyden introduced the Justice Against Weaponized Bureaucratic Overreach to Networked Expression, or JAWBONE Act. The bipartisan legislation creates a federal cause of action against government officials who coerce or attempt to coerce broadcasters, interactive computer services, or AI providers into taking actions against lawful, First-Amendment-protected speech, and establishes a transparency system for government communications with those intermediaries about user expression.

We thank the Senators for their leadership on this important issue. Jawboning occurs when the government pressures private companies to censor speech protected by the First Amendment, and it’s not always obvious to the public or to the victims what has actually happened. Deleting posts or cancelling accounts because a government official or agency demanded it or even made threats in making those demands—just like spying on people’s communications on behalf of the government—raises serious free speech concerns. Among other things, this bill would provide a new legal right to bring claims against the government in federal court, in addition to what the First Amendment provides.

At EFF, we’re continuing to fight back on behalf of those censored by government coercion. One recent example: we represent the creator of ICEBlock, an app that allows the public to report immigration enforcement activity in their communities. In June 2025, high-ranking federal officials began threatening to investigate and prosecute the creator of ICEBlock, Joshua Aaron. In October 2025, the U.S. Attorney General demanded Apple remove ICEBlock from the App Store, and the company complied. The government’s coercion violated Aaron’s First Amendment rights.

We’ve also filed a Freedom of Information Act lawsuit against the same government agencies that threatened Aaron and other services that provided forums to report ICE activity. The lawsuit seeks the disclosure of the government’s communications with Apple, Google, and Meta that forced the services to remove lawful speech.

When federal officials pressure private companies into censoring protected speech, it can violate the First Amendment. But, not every communication from a government agency to a platform is unconstitutionally coercive. Treating legitimate communication and information-sharing between the government and private actors as though it were always unconstitutional would chill the valuable, good-faith engagement that supports a healthier and safer internet and nation for all Americans. This is a complex issue, and one that is important for Congress and the courts to get right. 

Finally, contrary to what many in Congress have been saying, social media platforms and other internet intermediaries have their own First Amendment rights to decide how they moderate users’ speech. They are not “state actors” and do not have an obligation under the First Amendment to allow all user speech on their platforms. EFF filed an amicus brief setting out our position in 2018, and we’ve said it in many cases since. The Supreme Court recognized again in the Netchoice cases that these services have a right to curate and edit their users’ speech, whether or not it aligns with the government’s position. And, it’s important to defend that First Amendment right so that governments cannot dictate how to edit a company’s site according to the government’s wishes and desires. To prevent jawboning by default, companies must be free to curate their platforms as they wish.

EFF applauds Senators Cruz and Wyden for taking this critical issue seriously, and we look forward to working with Congress on this bipartisan bill as it moves through the process. We hope it lands on the right balance to provide additional protections for everyday users around freedom of expression.