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EFF to California Appellate Court: Reject Trial Judge’s Ruling That Would Penalize Beneficial Features and Tools on Social Media
EFF legal intern Jack Beck contributed to this post.
A California trial court recently departed from wide-ranging precedent and held that Snap, Inc., the maker of Snapchat, the popular social media app, had created a “defective” product by including features like disappearing messages, the ability to connect with people through mutual friends, and even the well-known “Stories” feature. We filed an amicus brief in the appeal, Neville v. Snap, Inc., at the California Court of Appeal, and are calling for the reversal of the earlier decision, which jeopardizes protections for online intermediaries and thus the free speech of all internet users.
At issue in the case is Section 230, without which the free and open internet as we know it would not exist. Section 230 provides that online intermediaries are generally not responsible for harmful user-generated content. Rather, responsibility for what a speaker says online falls on the person who spoke.
The plaintiffs are a group of parents whose children overdosed on fentanyl-laced drugs obtained through communications enabled by Snapchat. Even though the harm they suffered was premised on user-generated content—messages between the drug dealers and their children—the plaintiffs argued that Snapchat is a “defective product.” They highlighted various features available to all users on Snapchat, including disappearing messages, arguing that the features facilitate illegal drug deals.
Snap sought to have the case dismissed, arguing that the plaintiffs’ claims were barred by Section 230. The trial court disagreed, narrowly interpreting Section 230 and erroneously holding that the plaintiffs were merely trying to hold the company responsible for its own “independent tortious conduct—independent, that is, of the drug sellers’ posted content.” In so doing, the trial court departed from congressional intent and wide-ranging California and federal court precedent.
In a petition for a writ of mandate, Snap urged the appellate court to correct the lower court’s distortion of Section 230. The petition rightfully contends that the plaintiffs are trying to sidestep Section 230 through creative pleading. The petition argues that Section 230 protects online intermediaries from liability not only for hosting third-party content, but also for crucial editorial decisions like what features and tools to offer content creators and how to display their content.
We made two arguments in our brief supporting Snap’s appeal.
First, we explained that the features the plaintiffs targeted—and which the trial court gave no detailed analysis of—are regular parts of Snapchat’s functionality with numerous legitimate uses. Take Snapchat’s option to have messages disappear after a certain period of time. There are times when the option to make messages disappear can be crucial for protecting someone’s safety—for example, dissidents and journalists operating in repressive regimes, or domestic violence victims reaching out for support. It’s also an important privacy feature for everyday use. Simply put: the ability for users to exert control over who can see their messages and for how long, advances internet users’ privacy and security under legitimate circumstances.
Second, we highlighted in our brief that this case is about more than concerned families challenging a big tech company. Our modern communications are mediated by private companies, and so any weakening of Section 230 immunity for internet platforms would stifle everyone’s ability to communicate. Should the trial court’s ruling stand, Snapchat and similar platforms will be incentivized to remove features from their online services, resulting in bland and sanitized—and potentially more privacy invasive and less secure—communications platforms. User experience will be degraded as internet platforms are discouraged from creating new features and tools that facilitate speech. Companies seeking to minimize their legal exposure for harmful user-generated content will also drastically increase censorship of their users, and smaller platforms trying to get off the ground will fail to get funding or will be forced to shut down.
There’s no question that what happened in this case was tragic, and people are right to be upset about some elements of how big tech companies operate. But Section 230 is the wrong target. We strongly advocate for Section 230, yet when a tech company does something legitimately irresponsible, the statute still allows for them to be liable—as Snap knows from a lawsuit that put an end to its speed filter.
If the trial court’s decision is upheld, internet platforms would not have a reliable way to limit liability for the services they provide and the content they host. They would face too many lawsuits that cost too much money to defend. They would be unable to operate in their current capacity, and ultimately the internet would cease to exist in its current form. Billions of internet users would lose.
New algorithm unlocks high-resolution insights for computer vision
Imagine yourself glancing at a busy street for a few moments, then trying to sketch the scene you saw from memory. Most people could draw the rough positions of the major objects like cars, people, and crosswalks, but almost no one can draw every detail with pixel-perfect accuracy. The same is true for most modern computer vision algorithms: They are fantastic at capturing high-level details of a scene, but they lose fine-grained details as they process information.
Now, MIT researchers have created a system called “FeatUp” that lets algorithms capture all of the high- and low-level details of a scene at the same time — almost like Lasik eye surgery for computer vision.
When computers learn to “see” from looking at images and videos, they build up “ideas” of what's in a scene through something called “features.” To create these features, deep networks and visual foundation models break down images into a grid of tiny squares and process these squares as a group to determine what's going on in a photo. Each tiny square is usually made up of anywhere from 16 to 32 pixels, so the resolution of these algorithms is dramatically smaller than the images they work with. In trying to summarize and understand photos, algorithms lose a ton of pixel clarity.
The FeatUp algorithm can stop this loss of information and boost the resolution of any deep network without compromising on speed or quality. This allows researchers to quickly and easily improve the resolution of any new or existing algorithm. For example, imagine trying to interpret the predictions of a lung cancer detection algorithm with the goal of localizing the tumor. Applying FeatUp before interpreting the algorithm using a method like class activation maps (CAM) can yield a dramatically more detailed (16-32x) view of where the tumor might be located according to the model.
FeatUp not only helps practitioners understand their models, but also can improve a panoply of different tasks like object detection, semantic segmentation (assigning labels to pixels in an image with object labels), and depth estimation. It achieves this by providing more accurate, high-resolution features, which are crucial for building vision applications ranging from autonomous driving to medical imaging.
“The essence of all computer vision lies in these deep, intelligent features that emerge from the depths of deep learning architectures. The big challenge of modern algorithms is that they reduce large images to very small grids of 'smart' features, gaining intelligent insights but losing the finer details,” says Mark Hamilton, an MIT PhD student in electrical engineering and computer science, MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) affiliate, and a co-lead author on a paper about the project. “FeatUp helps enable the best of both worlds: highly intelligent representations with the original image’s resolution. These high-resolution features significantly boost performance across a spectrum of computer vision tasks, from enhancing object detection and improving depth prediction to providing a deeper understanding of your network's decision-making process through high-resolution analysis.”
Resolution renaissance
As these large AI models become more and more prevalent, there’s an increasing need to explain what they’re doing, what they’re looking at, and what they’re thinking.
But how exactly can FeatUp discover these fine-grained details? Curiously, the secret lies in wiggling and jiggling images.
In particular, FeatUp applies minor adjustments (like moving the image a few pixels to the left or right) and watches how an algorithm responds to these slight movements of the image. This results in hundreds of deep-feature maps that are all slightly different, which can be combined into a single crisp, high-resolution, set of deep features. “We imagine that some high-resolution features exist, and that when we wiggle them and blur them, they will match all of the original, lower-resolution features from the wiggled images. Our goal is to learn how to refine the low-resolution features into high-resolution features using this 'game' that lets us know how well we are doing,” says Hamilton. This methodology is analogous to how algorithms can create a 3D model from multiple 2D images by ensuring that the predicted 3D object matches all of the 2D photos used to create it. In FeatUp’s case, they predict a high-resolution feature map that’s consistent with all of the low-resolution feature maps formed by jittering the original image.
The team notes that standard tools available in PyTorch were insufficient for their needs, and introduced a new type of deep network layer in their quest for a speedy and efficient solution. Their custom layer, a special joint bilateral upsampling operation, was over 100 times more efficient than a naive implementation in PyTorch. The team also showed this new layer could improve a wide variety of different algorithms including semantic segmentation and depth prediction. This layer improved the network’s ability to process and understand high-resolution details, giving any algorithm that used it a substantial performance boost.
“Another application is something called small object retrieval, where our algorithm allows for precise localization of objects. For example, even in cluttered road scenes algorithms enriched with FeatUp can see tiny objects like traffic cones, reflectors, lights, and potholes where their low-resolution cousins fail. This demonstrates its capability to enhance coarse features into finely detailed signals,” says Stephanie Fu ’22, MNG ’23, a PhD student at the University of California at Berkeley and another co-lead author on the new FeatUp paper. “This is especially critical for time-sensitive tasks, like pinpointing a traffic sign on a cluttered expressway in a driverless car. This can not only improve the accuracy of such tasks by turning broad guesses into exact localizations, but might also make these systems more reliable, interpretable, and trustworthy.”
What next?
Regarding future aspirations, the team emphasizes FeatUp’s potential widespread adoption within the research community and beyond, akin to data augmentation practices. “The goal is to make this method a fundamental tool in deep learning, enriching models to perceive the world in greater detail without the computational inefficiency of traditional high-resolution processing,” says Fu.
“FeatUp represents a wonderful advance towards making visual representations really useful, by producing them at full image resolutions,” says Cornell University computer science professor Noah Snavely, who was not involved in the research. “Learned visual representations have become really good in the last few years, but they are almost always produced at very low resolution — you might put in a nice full-resolution photo, and get back a tiny, postage stamp-sized grid of features. That’s a problem if you want to use those features in applications that produce full-resolution outputs. FeatUp solves this problem in a creative way by combining classic ideas in super-resolution with modern learning approaches, leading to beautiful, high-resolution feature maps.”
“We hope this simple idea can have broad application. It provides high-resolution versions of image analytics that we’d thought before could only be low-resolution,” says senior author William T. Freeman, an MIT professor of electrical engineering and computer science professor and CSAIL member.
Lead authors Fu and Hamilton are accompanied by MIT PhD students Laura Brandt SM ’21 and Axel Feldmann SM ’21, as well as Zhoutong Zhang SM ’21, PhD ’22, all current or former affiliates of MIT CSAIL. Their research is supported, in part, by a National Science Foundation Graduate Research Fellowship, by the National Science Foundation and Office of the Director of National Intelligence, by the U.S. Air Force Research Laboratory, and by the U.S. Air Force Artificial Intelligence Accelerator. The group will present their work in May at the International Conference on Learning Representations.
Five MIT faculty members take on Cancer Grand Challenges
Cancer Grand Challenges recently announced five winning teams for 2024, which included five researchers from MIT: Michael Birnbaum, Regina Barzilay, Brandon DeKosky, Seychelle Vos, and Ömer Yilmaz. Each team is made up of interdisciplinary cancer researchers from across the globe and will be awarded $25 million over five years.
Birnbaum, an associate professor in the Department of Biological Engineering, leads Team MATCHMAKERS and is joined by co-investigators Barzilay, the School of Engineering Distinguished Professor for AI and Health in the Department of Electrical Engineering and Computer Science and the AI faculty lead at the MIT Abdul Latif Jameel Clinic for Machine Learning in Health; and DeKosky, Phillip and Susan Ragon Career Development Professor of Chemical Engineering. All three are also affiliates of the Koch Institute for Integrative Cancer Research At MIT.
Team MATCHMAKERS will take advantage of recent advances in artificial intelligence to develop tools for personalized immunotherapies for cancer patients. Cancer immunotherapies, which recruit the patient’s own immune system against the disease, have transformed treatment for some cancers, but not for all types and not for all patients.
T cells are one target for immunotherapies because of their central role in the immune response. These immune cells use receptors on their surface to recognize protein fragments called antigens on cancer cells. Once T cells attach to cancer antigens, they mark them for destruction by the immune system. However, T cell receptors are exceptionally diverse within one person’s immune system and from person to person, making it difficult to predict how any one cancer patient will respond to an immunotherapy.
Team MATCHMAKERS will collect data on T cell receptors and the different antigens they target and build computer models to predict antigen recognition by different T cell receptors. The team’s overarching goal is to develop tools for predicting T cell recognition with simple clinical lab tests and designing antigen-specific immunotherapies. “If successful, what we learn on our team could help transform prediction of T cell receptor recognition from something that is only possible in a few sophisticated laboratories in the world, for a few people at a time, into a routine process,” says Birnbaum.
“The MATCHMAKERS project draws on MIT’s long tradition of developing cutting-edge artificial intelligence tools for the benefit of society,” comments Ryan Schoenfeld, CEO of The Mark Foundation for Cancer Research. “Their approach to optimizing immunotherapy for cancer and many other diseases is exemplary of the type of interdisciplinary research The Mark Foundation prioritizes supporting.” In addition to The Mark Foundation, the MATCHMAKERS team is funded by Cancer Research UK and the U.S. National Cancer Institute.
Vos, the Robert A. Swanson (1969) Career Development Professor of Life Sciences and HHMI Freeman Hrabowksi Scholar in the Department of Biology, will be a co-investigator on Team KOODAC. The KOODAC team will develop new treatments for solid tumors in children, using protein degradation strategies to target previously “undruggable” drivers of cancers. KOODAC is funded by Cancer Research UK, France's Institut National Du Cancer, and KiKa (Children Cancer Free Foundation) through Cancer Grand Challenges.
As a co-investigator on team PROSPECT, Yilmaz, who is also a Koch Institute affiliate, will help address early-onset colorectal cancers, an emerging global problem among individuals younger than 50 years. The team seeks to elucidate pathways, risk factors, and molecules involved in the disease’s development. Team PROSPECT is supported by Cancer Research UK, the U.S. National Cancer Institute, the Bowelbabe Fund for Cancer Research UK, and France's Institut National Du Cancer through Cancer Grand Challenges.
Unlocking the quantum future
Quantum computing is the next frontier for faster and more powerful computing technologies. It has the potential to better optimize routes for shipping and delivery, speed up battery development for electric vehicles, and more accurately predict trends in financial markets. But to unlock the quantum future, scientists and engineers need to solve outstanding technical challenges while continuing to explore new applications.
One place where they’re working towards this future is the MIT Interdisciplinary Quantum Hackathon, or iQuHACK for short (pronounced “i-quack,” like a duck). Each year, a community of quhackers (quantum hackers) gathers at iQuHACK to work on quantum computing projects using real quantum computers and simulators. This year, the hackathon was held both in-person at MIT and online over three days in February.
Quhackers worked in teams to advance the capability of quantum computers and to investigate promising applications. Collectively, they tackled a wide range of projects, such as running a quantum-powered dating service, building an organ donor matching app, and breaking into quantum vaults. While working, quhackers could consult with scientists and engineers in attendance from sponsoring companies. Many sponsors also received feedback and ideas from quhackers to help improve their quantum platforms.
But organizing iQuHACK 2024 was no easy feat. Co-chairs Alessandro Buzzi and Daniela Zaidenberg led a committee of nine members to hold the largest iQuHACK yet. “It wouldn’t have been possible without them,” Buzzi said. The hackathon hosted 260 in-person quhackers and 1,000 remote quhackers, representing 77 countries in total. More than 20 scientists and engineers from sponsoring companies also attended in person as mentors for quhackers.
Each team of quhackers tackled one of 10 challenges posed by the hackathon’s eight major sponsoring companies. Some challenges asked quhackers to improve computing performance, such as by making quantum algorithms faster and more accurate. Other challenges asked quhackers to explore applying quantum computing to other fields, such as finance and machine learning. The sponsors worked with the iQuHACK committee to craft creative challenges with industry relevance and societal impact. “We wanted people to be able to address an interesting challenge [that has] applications in the real world,” says Zaidenberg.
One team of quhackers looked for potential quantum applications and found one close to home: dating. A team member, Liam Kronman, had previously built dating apps but disliked that matching algorithms for normal classical computers “require [an overly] strict setup.” With these classical algorithms, people must be split into two groups — for example, men and women — and matches can only be made between these groups. But with quantum computers, matching algorithms are more flexible and can consider all possible combinations, enabling the inclusion of multiple genders and gender preferences.
Kronman and his team members leveraged these quantum algorithms to build a quantum-powered dating platform called MITqute (pronounced “meet cute”). To date, the platform has matched at least 240 people from the iQuHACK and MIT undergrad communities. In a follow-up survey, 13 out of 41 respondents reported having talked with their match, with at least two pairs setting up dates. “I really lucked out with this one,” one respondent wrote.
Another team of quhackers also based their project on quantum matching algorithms but instead leveraged the algorithms’ power for medical care. The team built a mobile app that matches organ donors to patients, earning them the hackathon’s top social impact award.
But they almost didn’t go through with their project. “At one point, we were considering scrapping the whole thing because we thought we couldn’t implement the algorithm,” says Alma Alex, one of the developers. After talking with their hackathon mentor for advice, though, the team learned that another group was working on a similar type of project — incidentally, the MITqute team. Knowing that others were tackling the same problem inspired them to persevere.
A sense of community also helped to motivate other quhackers. For one of the challenges, quhackers were tasked with hacking into 13 virtual quantum vaults. Teams could see each other’s progress on each vault in real time on a leaderboard, and this knowledge informed their strategies. When the first vault was successfully hacked by a team, progress from many other teams spiked on that vault and slowed down on others, says Daiwei Zhu, a quantum applications scientist at IonQ and one of the challenge’s two architects.
The vault challenge may appear to be just a fun series of puzzles, but the solutions can be used in quantum computers to improve their efficiency and accuracy. To hack into a vault, quhackers had to first figure out its secret key — an unknown quantum state — using a maximum of 20 probing tests. Then, they had to change the key’s state to a target state. These types of characterizations and modifications of quantum states are “fundamental” for quantum computers to work, says Jason Iaconis, a quantum applications engineer at IonQ and the challenge’s other architect.
But the best way to characterize and modify states is not yet clear. “Some of the [vaults] we [didn’t] even know how to solve ourselves,” Zhu says. At the end of the hackathon, six vaults had at least one team mostly hack into them. (In the quantum world where gray areas exist, it’s possible to partly hack into a vault.)
The community of scientists and engineers formed at iQuHACK persists beyond the weekend, and many members continue to grow the community outside the hackathon. Inspired quhackers have gone on to start their own quantum computing clubs at their universities. A few years ago, a group of undergraduate quhackers from different universities formed a Quantum Coalition that now hosts their own quantum hackathons. “It’s crazy to see how the hackathon itself spreads and how many people start their own initiatives,” co-chair Zaidenberg says.
The three-day hackathon opened with a keynote from MIT Professor Will Oliver, which included an overview of basic quantum computing concepts, current challenges, and computing technologies. Following that were industry talks and a panel of six industry and academic quantum experts, including MIT Professor Peter Shor, who is known for developing one of the most famous quantum algorithms. The panelists discussed current challenges, future applications, the importance of collaboration, and the need for ample testing.
Later, sponsors held technical workshops where quhackers could learn the nitty-gritty details of programming on specific quantum platforms. Day one closed out with a talk by research scientist Xinghui Yin on the role of quantum technology at LIGO, the Laser Interferometer Gravitational-Wave Observatory that first detected gravitational waves. The next day, the hackathon’s challenges were announced at 10 a.m., and hacking kicked off at the MIT InnovationHQ. In the afternoon, attendees could also tour MIT quantum computing labs.
Hacking continued overnight at the MIT Museum and ended back at MIT iHQ at 10 a.m. on the final day. Quhackers then presented their projects to panels of judges. Afterward, industry speakers gave lightning talks about each of their company’s latest quantum technologies and future directions. The hackathon ended with a closing ceremony, where sponsors announced the awards for each of the 10 challenges.
The hackathon was captured in a three-part video by Albert Figurt, a resident artist at MIT. Figurt shot and edited the footage in parallel with the hackathon. Each part represented one day of the hackathon and was released on the subsequent day.
Throughout the weekend, quhackers and sponsors consistently praised the hackathon’s execution and atmosphere. “That was amazing … never felt so much better, one of the best hackathons I did from over 30 hackathons I attended,” Abdullah Kazi, a quhacker, wrote on the iQuHACK Slack.
Ultimately, “[we wanted to] help people to meet each other,” co-chair Buzzi says. “The impact [of iQuHACK] is scientific in some way, but it’s very human at the most important level.”
Drones and the US Air Force
Fascinating analysis of the use of drones on a modern battlefield—that is, Ukraine—and the inability of the US Air Force to react to this change.
The F-35A certainly remains an important platform for high-intensity conventional warfare. But the Air Force is planning to buy 1,763 of the aircraft, which will remain in service through the year 2070. These jets, which are wholly unsuited for countering proliferated low-cost enemy drones in the air littoral, present enormous opportunity costs for the service as a whole. In a set of comments posted on LinkedIn...
California’s insurer of last resort is a ‘ticking time bomb’
How EPA could change the power plant rule’s ‘finer details’
24 states sue over EPA methane rule
Q&A: He got US funding to protect his tiny island nation. Now what?
HHS to target heat, smoke effects on farmworkers
House schedules first hearings on final SEC climate rule
A warming island’s mice are breeding out of control and eating seabirds
South Sudan shutters schools as it prepares for extreme heat wave
India’s Bengaluru is running out of water as summer looms
Australia to miss 2030 climate goal, Oxford says
Lawmakers: Ban TikTok to Stop Election Misinformation! Same Lawmakers: Restrict How Government Addresses Election Misinformation!
In a case being heard Monday at the Supreme Court, 45 Washington lawmakers have argued that government communications with social media sites about possible election interference misinformation are illegal.
Agencies can't even pass on information about websites state election officials have identified as disinformation, even if they don't request that any action be taken, they assert.
Yet just this week the vast majority of those same lawmakers said the government's interest in removing election interference misinformation from social media justifies banning a site used by 150 million Americans.
On Monday, the Supreme Court will hear oral arguments in Murthy v. Missouri, a case that raises the issue of whether the federal government violates the First Amendment by asking social media platforms to remove or negatively moderate user posts or accounts. In Murthy, the government contends that it can strongly urge social media sites to remove posts without violating the First Amendment, as long as it does not coerce them into doing so under the threat of penalty or other official sanction.
We recognize both the hazards of government involvement in content moderation and the proper role in some situations for the government to share its expertise with the platforms. In our brief in Murthy, we urge the court to adopt a view of coercion that includes indirectly coercive communications designed and reasonably perceived as efforts to replace the platform’s editorial decision-making with the government’s.
And we argue that close cases should go against the government. We also urge the court to recognize that the government may and, in some cases, should appropriately inform platforms of problematic user posts. But it’s the government’s responsibility to make sure that its communications with the platforms are reasonably perceived as being merely informative and not coercive.
In contrast, the Members of Congress signed an amicus brief in Murthy supporting placing strict limitations on the government’s interactions with social media companies. They argued that the government may hardly communicate at all with social media platforms when it detects problematic posts.
Notably, the specific posts they discuss in their brief include, among other things, posts the U.S. government suspects are foreign election interference. For example, the case includes allegations about the FBI and CISA improperly communicating with social media sites that boil down to the agency passing on pertinent information, such as websites that had already been identified by state and local election officials as disinformation. The FBI did not request that any specific action be taken and sought to understand how the sites' terms of service would apply.
As we argued in our amicus brief, these communications don't add up to the government dictating specific editorial changes it wanted. It was providing information useful for sites seeking to combat misinformation. But, following an injunction in Murthy, the government has ceased sharing intelligence about foreign election interference. Without the information, Meta reports its platforms could lack insight into the bigger threat picture needed to enforce its own rules.
The problem of election misinformation on social media also played a prominent role this past week when the U.S. House of Representatives approved a bill that would bar app stores from distributing TikTok as long as it is owned by its current parent company, ByteDance, which is headquartered in Beijing. The bill also empowers the executive branch to identify and similarly ban other apps that are owned by foreign adversaries.
As stated in the House Report that accompanied the so-called "Protecting Americans from Foreign Adversary Controlled Applications Act," the law is needed in part because members of Congress fear the Chinese government “push[es] misinformation, disinformation, and propaganda on the American public” through the platform. Those who supported the bill thus believe that the U.S. can take the drastic step of banning an app for the purposes of preventing the spread of “misinformation and propaganda” to U.S. users. A public report from the Office of the Director for National Intelligence was more specific about the threat, indicating a special concern for information meant to interfere with the November elections and foment societal divisions in the U.S.
Over 30 members of the House who signed the amicus brief in Murthy voted for the TikTok ban. So, many of the same people who supported the U.S. government’s efforts to rid a social media platform of foreign misinformation, also argued that the government’s ability to address the very same content on other social media platforms should be sharply limited.
Admittedly, there are significant differences between the two positions. The government does have greater limits on how it regulates the speech of domestic companies than it does the speech of foreign companies.
But if the true purpose of the bill is to get foreign election misinformation off of social media, the inconsistency in the positions is clear. If ByteDance sells TikTok to domestic owners so that TikTok can stay in business in the U.S., and if the same propaganda appears on the site, is the U.S. now powerless to do anything about it? If so, that would seem to undercut the importance in getting the information away from U.S. users, which is one the chief purposes of the TikTik ban.
We believe there is an appropriate role for the government to play, within the bounds of the First Amendment, when it truly believes that there are posts designed to interfere with U.S. elections or undermine U.S. security on any social media platform. It is a far more appropriate role than banning a platform altogether.
Friday Squid Blogging: Operation Squid
Operation Squid found 1.3 tons of cocaine hidden in frozen fish.
As usual, you can also use this squid post to talk about the security stories in the news that I haven’t covered.
Read my blog posting guidelines here.
Making the clean energy transition work for everyone
The clean energy transition is already underway, but how do we make sure it happens in a manner that is affordable, sustainable, and fair for everyone?
That was the overarching question at this year’s MIT Energy Conference, which took place March 11 and 12 in Boston and was titled “Short and Long: A Balanced Approach to the Energy Transition.”
Each year, the student-run conference brings together leaders in the energy sector to discuss the progress and challenges they see in their work toward a greener future. Participants come from research, industry, government, academia, and the investment community to network and exchange ideas over two whirlwind days of keynote talks, fireside chats, and panel discussions.
Several participants noted that clean energy technologies are already cost-competitive with fossil fuels, but changing the way the world works requires more than just technology.
“None of this is easy, but I think developing innovative new technologies is really easy compared to the things we’re talking about here, which is how to blend social justice, soft engineering, and systems thinking that puts people first,” Daniel Kammen, a distinguished professor of energy at the University of California at Berkeley, said in a keynote talk. “While clean energy has a long way to go, it is more than ready to transition us from fossil fuels.”
The event also featured a keynote discussion between MIT President Sally Kornbluth and MIT’s Kyocera Professor of Ceramics Yet-Ming Chiang, in which Kornbluth discussed her first year at MIT as well as a recently announced, campus-wide effort to solve critical climate problems known as the Climate Project at MIT.
“The reason I wanted to come to MIT was I saw that MIT has the potential to solve the world’s biggest problems, and first among those for me was the climate crisis,” Kornbluth said. “I’m excited about where we are, I’m excited about the enthusiasm of the community, and I think we’ll be able to make really impactful discoveries through this project.”
Fostering new technologies
Several panels convened experts in new or emerging technology fields to discuss what it will take for their solutions to contribute to deep decarbonization.
“The fun thing and challenging thing about first-of-a-kind technologies is they’re all kind of different,” said Jonah Wagner, principal assistant director for industrial innovation and clean energy in the U.S. Office of Science and Technology Policy. “You can map their growth against specific challenges you expect to see, but every single technology is going to face their own challenges, and every single one will have to defy an engineering barrier to get off the ground.”
Among the emerging technologies discussed was next-generation geothermal energy, which uses new techniques to extract heat from the Earth’s crust in new places.
A promising aspect of the technology is that it can leverage existing infrastructure and expertise from the oil and gas industry. Many newly developed techniques for geothermal production, for instance, use the same drills and rigs as those used for hydraulic fracturing.
“The fact that we have a robust ecosystem of oil and gas labor and technology in the U.S. makes innovation in geothermal much more accessible compared to some of the challenges we’re seeing in nuclear or direct-air capture, where some of the supply chains are disaggregated around the world,” said Gabrial Malek, chief of staff at the geothermal company Fervo Energy.
Another technology generating excitement — if not net energy quite yet — is fusion, the process of combining, or fusing, light atoms together to form heavier ones for a net energy gain, in the same process that powers the sun. MIT spinout Commonwealth Fusion Systems (CFS) has already validated many aspects of its approach for achieving fusion power, and the company’s unique partnership with MIT was discussed in a panel on the industry’s progress.
“We’re standing on the shoulders of decades of research from the scientific community, and we want to maintain those ties even as we continue developing our technology,” CFS Chief Science Officer Brandon Sorbom PhD ’17 said, noting that CFS is one of the largest company sponsors of research at MIT and collaborates with institutions around the world. “Engaging with the community is a really valuable lever to get new ideas and to sanity check our own ideas.”
Sorbom said that as CFS advances fusion energy, the company is thinking about how it can replicate its processes to lower costs and maximize the technology’s impact around the planet.
“For fusion to work, it has to work for everyone,” Sorbom said. “I think the affordability piece is really important. We can’t just build this technological jewel that only one class of nations can afford. It has to be a technology that can be deployed throughout the entire world.”
The event also gave students — many from MIT — a chance to learn more about careers in energy and featured a startup showcase, in which dozens of companies displayed their energy and sustainability solutions.
“More than 700 people are here from every corner of the energy industry, so there are so many folks to connect with and help me push my vision into reality,” says GreenLIB CEO Fred Rostami, whose company recycles lithium-ion batteries. “The good thing about the energy transition is that a lot of these technologies and industries overlap, so I think we can enable this transition by working together at events like this.”
A focused climate strategy
Kornbluth noted that when she came to MIT, a large percentage of students and faculty were already working on climate-related technologies. With the Climate Project at MIT, she wanted to help ensure the whole of those efforts is greater than the sum of its parts.
The project is organized around six distinct missions, including decarbonizing energy and industry, empowering frontline communities, and building healthy, resilient cities. Kornbluth says the mission areas will help MIT community members collaborate around multidisciplinary challenges. Her team, which includes a committee of faculty advisors, has begun to search for the leads of each mission area, and Kornbluth said she is planning to appoint a vice president for climate at the Institute.
“I want someone who has the purview of the whole Institute and will report directly to me to help make sure this project stays on track,” Kornbluth explained.
In his conversation about the initiative with Kornbluth, Yet-Ming Chiang said projects will be funded based on their potential to reduce emissions and make the planet more sustainable at scale.
“Projects should be very high risk, with very high impact,” Chiang explained. “They should have a chance to prove themselves, and those efforts should not be limited by resources, only by time.”
In discussing her vision of the climate project, Kornbluth alluded to the “short and long” theme of the conference.
“It’s about balancing research and commercialization,” Kornbluth said. “The climate project has a very variable timeframe, and I think universities are the sector that can think about the things that might be 30 years out. We have to think about the incentives across the entire innovation pipeline and how we can keep an eye on the long term while making sure the short-term things get out rapidly.”
3 Questions: What you need to know about audio deepfakes
Audio deepfakes have had a recent bout of bad press after an artificial intelligence-generated robocall purporting to be the voice of Joe Biden hit up New Hampshire residents, urging them not to cast ballots. Meanwhile, spear-phishers — phishing campaigns that target a specific person or group, especially using information known to be of interest to the target — go fishing for money, and actors aim to preserve their audio likeness.
What receives less press, however, are some of the uses of audio deepfakes that could actually benefit society. In this Q&A prepared for MIT News, postdoc Nauman Dawalatabad addresses concerns as well as potential upsides of the emerging tech. A fuller version of this interview can be seen at the video below.
Q: What ethical considerations justify the concealment of the source speaker's identity in audio deepfakes, especially when this technology is used for creating innovative content?
A: The inquiry into why research is important in obscuring the identity of the source speaker, despite a large primary use of generative models for audio creation in entertainment, for example, does raise ethical considerations. Speech does not contain the information only about “who you are?” (identity) or “what you are speaking?” (content); it encapsulates a myriad of sensitive information including age, gender, accent, current health, and even cues about the upcoming future health conditions. For instance, our recent research paper on “Detecting Dementia from Long Neuropsychological Interviews” demonstrates the feasibility of detecting dementia from speech with considerably high accuracy. Moreover, there are multiple models that can detect gender, accent, age, and other information from speech with very high accuracy. There is a need for advancements in technology that safeguard against the inadvertent disclosure of such private data. The endeavor to anonymize the source speaker's identity is not merely a technical challenge but a moral obligation to preserve individual privacy in the digital age.
Q: How can we effectively maneuver through the challenges posed by audio deepfakes in spear-phishing attacks, taking into account the associated risks, the development of countermeasures, and the advancement of detection techniques?
A: The deployment of audio deepfakes in spear-phishing attacks introduces multiple risks, including the propagation of misinformation and fake news, identity theft, privacy infringements, and the malicious alteration of content. The recent circulation of deceptive robocalls in Massachusetts exemplifies the detrimental impact of such technology. We also recently spoke with the spoke with The Boston Globe about this technology, and how easy and inexpensive it is to generate such deepfake audios.
Anyone without a significant technical background can easily generate such audio, with multiple available tools online. Such fake news from deepfake generators can disturb financial markets and even electoral outcomes. The theft of one's voice to access voice-operated bank accounts and the unauthorized utilization of one's vocal identity for financial gain are reminders of the urgent need for robust countermeasures. Further risks may include privacy violation, where an attacker can utilize the victim’s audio without their permission or consent. Further, attackers can also alter the content of the original audio, which can have a serious impact.
Two primary and prominent directions have emerged in designing systems to detect fake audio: artifact detection and liveness detection. When audio is generated by a generative model, the model introduces some artifact in the generated signal. Researchers design algorithms/models to detect these artifacts. However, there are some challenges with this approach due to increasing sophistication of audio deepfake generators. In the future, we may also see models with very small or almost no artifacts. Liveness detection, on the other hand, leverages the inherent qualities of natural speech, such as breathing patterns, intonations, or rhythms, which are challenging for AI models to replicate accurately. Some companies like Pindrop are developing such solutions for detecting audio fakes.
Additionally, strategies like audio watermarking serve as proactive defenses, embedding encrypted identifiers within the original audio to trace its origin and deter tampering. Despite other potential vulnerabilities, such as the risk of replay attacks, ongoing research and development in this arena offer promising solutions to mitigate the threats posed by audio deepfakes.
Q: Despite their potential for misuse, what are some positive aspects and benefits of audio deepfake technology? How do you imagine the future relationship between AI and our experiences of audio perception will evolve?
A: Contrary to the predominant focus on the nefarious applications of audio deepfakes, the technology harbors immense potential for positive impact across various sectors. Beyond the realm of creativity, where voice conversion technologies enable unprecedented flexibility in entertainment and media, audio deepfakes hold transformative promise in health care and education sectors. My current ongoing work in the anonymization of patient and doctor voices in cognitive health-care interviews, for instance, facilitates the sharing of crucial medical data for research globally while ensuring privacy. Sharing this data among researchers fosters development in the areas of cognitive health care. The application of this technology in voice restoration represents a hope for individuals with speech impairments, for example, for ALS or dysarthric speech, enhancing communication abilities and quality of life.
I am very positive about the future impact of audio generative AI models. The future interplay between AI and audio perception is poised for groundbreaking advancements, particularly through the lens of psychoacoustics — the study of how humans perceive sounds. Innovations in augmented and virtual reality, exemplified by devices like the Apple Vision Pro and others, are pushing the boundaries of audio experiences towards unparalleled realism. Recently we have seen an exponential increase in the number of sophisticated models coming up almost every month. This rapid pace of research and development in this field promises not only to refine these technologies but also to expand their applications in ways that profoundly benefit society. Despite the inherent risks, the potential for audio generative AI models to revolutionize health care, entertainment, education, and beyond is a testament to the positive trajectory of this research field.
The SAFE Act to Reauthorize Section 702 is Two Steps Forward, One Step Back
Section 702 of the Foreign Intelligence Surveillance Act (FISA) is one of the most insidious and secretive mass surveillance authorities still in operation today. The Security and Freedom Enhancement (SAFE) Act would make some much-needed and long fought-for reforms, but it also does not go nearly far enough to rein in a surveillance law that the federal government has abused time and time again.
You can read the full text of the bill here.
While Section 702 was first sold as a tool necessary to stop foreign terrorists, it has since become clear that the government uses the communications it collects under this law as a domestic intelligence source. The program was intended to collect communications of people outside of the United States, but because we live in an increasingly globalized world, the government retains a massive trove of communications between people overseas on U.S. persons. Now, it’s this US side of digital conversations that are being routinely sifted through by domestic law enforcement agencies—all without a warrant.
The SAFE Act, like other reform bills introduced this Congress, attempts to roll back some of this warrantless surveillance. Despite its glaring flaws and omissions, in a Congress as dysfunctional as this one it might be the bill that best privacy-conscious people and organizations can hope for. For instance, it does not do as much as the Government Surveillance Reform Act, which EFF supported in November 2023. But imposing meaningful checks on the Intelligence Community (IC) is an urgent priority, especially because the Intelligence Community has been trying to sneak a "clean" reauthorization of Section 702 into government funding bills, and has even sought to have the renewal happen in secret in the hopes of keeping its favorite mass surveillance law intact. The administration is also reportedly planning to seek another year-long extension of the law without any congressional action. All the while, those advocating for renewing Section 702 have toyed with as many talking points as they can—from cybercrime or human trafficking to drug smuggling, terrorism, oreven solidarity activism in the United States—to see what issue would scare people sufficiently enough to allow for a clean reauthorization of mass surveillance.
So let’s break down the SAFE Act: what’s good, what’s bad, and what aspects of it might actually cause more harm in the future.
What’s Good about the SAFE ActThe SAFE Act would do at least two things that reform advocates have pressured Congress to include in any proposed bill to reauthorize Section 702. This speaks to the growing consensus that some reforms are absolutely necessary if this power is to remain operational.
The first and most important reform the bill would make is to require the government to obtain a warrant before accessing the content of communications for people in the United States. Currently, relying on Section 702, the government vacuums up communications from all over the world, and a huge number of those intercepted communications are to or from US persons. Those communications sit in a massive database. Both intelligence agencies and law enforcement have conducted millions of queries of this database for US-based communications—all without a warrant—in order to investigate both national security concerns and run-of-the-mill criminal investigations. The SAFE Act would prohibit “warrantless access to the communications and other information of United States persons and persons located in the United States.” While this is the bare minimum a reform bill should do, it’s an important step. It is crucial to note, however, that this does not stop the IC or law enforcement from querying to see if the government has collected communications from specific individuals under Section 702—it merely stops them from reading those communications without a warrant.
The second major reform the SAFE Act provides is to close the “data brooker loophole,” which EFF has been calling attention to for years. As one example, mobile apps often collect user data to sell it to advertisers on the open market. The problem is law enforcement and intelligence agencies increasingly buy this private user data, rather than obtain a warrant for it. This bill would largely prohibit the government from purchasing personal data they would otherwise need a warrant to collect. This provision does include a potentially significant exception for situations where the government cannot exclude Americans’ data from larger “compilations” that include foreigners’ data. This speaks not only to the unfair bifurcation of rights between Americans and everyone else under much of our surveillance law, but also to the risks of allowing any large scale acquisition from data brokers at all. The SAFE Act would require the government to minimize collection, search, and use of any Americans’ data in these compilations, but it remains to be seen how effective these prohibitions will be.
What’s Missing from the SAFE ActThe SAFE Act is missing a number of important reforms that we’ve called for—and which the Government Surveillance Reform Act would have addressed. These reforms include ensuring that individuals harmed by warrantless surveillance are able to challenge it in court, both in civil lawsuits like those brought by EFF in the past, and in criminal cases where the government may seek to shield its use of Section 702 from defendants. After nearly 14 years of Section 702 and countless court rulings slamming the courthouse door on such legal challenges, it’s well past time to ensure that those harmed by Section 702 surveillance can have the opportunity to challenge it.
New Problems Potentially Created by the SAFE ActWhile there may often be good reason to protect the secrecy of FISA proceedings, unofficial disclosures about these proceedings has from the very beginning played an indispensable role in reforming uncontested abuses of surveillance authorities. From the Bush administration’s warrantless wiretapping program through the Snowden disclosures up to the present, when reporting about FISA applications appears on the front page of the New York Times, oversight of the intelligence community would be extremely difficult, if not impossible, without these disclosures.
Unfortunately, the SAFE Act contains at least one truly nasty addition to current law: an entirely new crime that makes it a felony to disclose “the existence of an application” for foreign intelligence surveillance or any of the application’s contents. In addition to explicitly adding to the existing penalties in the Espionage Act—itself highly controversial— this new provision seems aimed at discouraging leaks by increasing the potential sentence to eight years in prison. There is no requirement that prosecutors show that the disclosure harmed national security, nor any consideration of the public interest. Under the present climate, there’s simply no reason to give prosecutors even more tools like this one to punish whistleblowers who are seen as going through improper channels.
EFF always aims to tell it like it is. This bill has some real improvements, but it’s nowhere near the surveillance reform we all deserve. On the other hand, the IC and its allies in Congress continue to have significant leverage to push fake reform bills, so the SAFE Act may well be the best we’re going to get. Either way, we’re not giving up the fight.