The agency’s top official told lawmakers that the “vast majority” of calls were answered. New data indicates most people couldn’t get through.

Occidental Petroleum, which is developing the Stratos megaproject, discovered an issue with some of its components.

Ørsted and Equinor reported progress on three projects that the Trump administration has tried to halt.

The latest legislative effort fizzled, in part, because of legal principles established after the catastrophic 2023 wildfires in Maui. Democrats say they will try again.

Gov. Kathy Hochul has said New York is unique in having a statutory emissions reduction requirement, but legal experts and environmental groups disagree.

Eastern wildfires could become more common in the coming years, wildfire ecologists say.

Many local public health researchers are attributing the surge to the recently accelerating effects of climate change.

A deadly outbreak of the rare hantavirus aboard a Dutch ship on a weekslong polar cruise has brought attention to the growing tourism trend.

Lidar systems use pulses of infrared light to measure distance and map a 3D scene with high resolution, allowing autonomous vehicles to rapidly react to obstacles that appear in their path. But traditional lidar sensors are expensive, bulky systems with many moving parts that degrade over time, limiting how the sensors can be deployed.

A new study from MIT researchers could help to enable next-generation lidar sensors that are compact, durable, and have no moving parts. The key advance is a novel design for a silicon-photonics chip, which is a semiconductor device that manipulates light rather than electricity. 

Typically, such silicon-photonics chip-based systems have a restricted field of view, so a silicon-photonics-based lidar would not be able to scan angles in the periphery. Existing workarounds to this problem increase noise and hamper precision.

To avoid these drawbacks, the MIT researchers designed and demonstrated an array of integrated antennas that minimizes unwanted crosstalk between the antennas. Their innovation allows a lidar chip to scan a wider field of view while maintaining low-noise operation compared to other silicon-photonics-based approaches.

This novel demonstration could fuel the development of advanced lidar sensors for demanding applications like autonomous vehicle navigation, aerial surveying, and construction site monitoring.

“The functionality we demonstrated in this work solves a fundamental problem for integrated optical-phased-array technology, enabling future lidar sensors that can achieve significantly higher performance than we could demonstrate previously,” says Jelena Notaros, the Robert J. Shillman Career Development Associate Professor of Electrical Engineering and Computer Science (EECS) at MIT, a member of the Research Laboratory of Electronics, and senior author of a paper on this innovation.

She is joined on the paper by lead author and EECS graduate student Henry Crawford-Eng as well as EECS graduate students Andres Garcia Coleto, Benjamin M. Mazur, Daniel M. DeSantis, and Tal Sneh. The research appears today in Nature Communications.

Adjusting an antenna array

Many traditional lidar systems map a scene using a bulky box that spins to send pulses of light in multiple directions. The light bounces off nearby objects and returns to the sensor, providing data that are used to reconstruct the environment. 

Instead, silicon-photonics-based lidar sensors systematically scan an emitted light beam in multiple directions non-mechanically using a system called an integrated optical phased array (OPA).

Key to an OPA is an array of integrated antennas that have tiny perturbations placed periodically along their length. These corrugations allow the antenna to scatter light from an input source up and out of the photonic chip.

By adjusting the phase of light routed to each antenna, the researchers can change the angle at which the light is emitted out of the array. In this way, they can steer the beam with no moving parts.

But if engineers place the antennas too close together, the antennas will couple with each other and the light they emit will get jumbled. To avoid this, scientists typically space the antennas farther apart, but this also has downsides.

If the antennas are spaced too far apart, the array will emit multiple copies of the light beam at different angles. The researchers can only steer the primary beam so far in either direction until it is undiscernible from its neighboring copies.

“This limits our field of view, so the autonomous vehicle now only knows what is in front of it for a certain angular range,” Garcia Coleto explains.

These beam copies, known as grating lobes, can cause false positives by confusing the sensor. They also waste power.

The MIT researchers solved this problem by designing a set of reduced-crosstalk antennas that can be placed close together without causing a significant coupling effect.

In a standard OPA, all the antennas have the same design, meaning the same arrangement of corrugations. These identical antennas couple very strongly when placed close together.

To address this fundamental roadblock, the MIT researchers designed a set of three antennas with different geometries, varying the width of each antenna and the size and arrangement of corrugations. With varied geometries, each antenna has a different propagation coefficient, which determines how light travels down the antenna.

“Because the antennas have very different propagation coefficients, when we put them close together, essentially each antenna doesn’t ‘see’ the antenna next to it. Therefore, it won’t couple with its neighbor,” Garcia Coleto says. 

A photonic balancing act

But even though the antennas have different propagation coefficients, the researchers still need them to emit light in the same way. 

They achieved this by carefully designing the antennas to meet three parameters. 

First, each antenna must emit the same amount of light. Second, each antenna must emit a beam at the same angle for the same wavelength of light. Third, the emission angle must change uniformly across the array as the researchers steer it.

“We have this challenge where we require the antennas to have different geometries to reduce the crosstalk, but we need to simultaneously design the antennas to have the same emission characteristics. While it is possible to engineer this, it is extremely difficult because, typically, when antennas are designed with different geometries, they tend to behave differently,” Crawford-Eng says.

The researchers first developed the fundamental electromagnetic theory behind how radiative modes couple. They used that theory as a guide to design and simulate their antennas.

Building on those analyses, they fabricated the OPA with reduced-crosstalk antennas spaced significantly closer than they would be in a traditional OPA, then experimentally tested the system.

While a typical OPA would have coupling of about 100 percent in this experiment, their OPA reduced coupling to about 1 percent while generating a single, precise beam. Using this design, they demonstrated accurate beam steering across a wide field of view without any grating lobes. 

In the future, the researchers plan to further improve their technique to enable an even wider field of view. In addition, they are exploring a new potential solution to wide field-of-view functionality that they discovered while developing the underlying theory.

“This work addresses a longstanding challenge in integrated optical phased arrays: simultaneously achieving both a wide field of view, which requires dense antenna spacing, and high beam quality, which requires low crosstalk between neighboring antennas. The authors solve this problem with an elegant antenna design. Their innovation is an important step forward for chip-scale, solid-state beam-steering technology,” says Joyce Poon, professor of electrical and computer engineering at the University of Toronto and director of the Max Planck Institute of Microstructure Physics, who was not involved with this work.

This research was supported, in part, by the Semiconductor Research Corporation, the National Science Foundation, an MIT MathWorks Fellowship, the U.S. Department of War, and the MIT Rolf G. Locher Endowed Fellowship.

When we hear about automation and artificial intelligence replacing jobs, it may seem like a tsunami of technology is going to wipe out workers broadly, in the name of greater efficiency. But a study co-authored by an MIT economist shows markedly different dynamics in the U.S. since 1980. 

Rather than implement automation in pursuit of maximal productivity, firms have often used automation to replace employees who specifically receive a “wage premium,” earning higher salaries than other comparable workers. In practice, that means automation has frequently reduced the earnings of non-college-educated workers who had obtained better salaries than most employees with similar qualifications. 

This finding has at least two big implications. For one thing, automation has affected the growth in U.S. income inequality even more than many observers realize. At the same time, automation has yielded a mediocre productivity boost, plausibly due to the focus of firms on controlling wages rather than finding more tech-driven ways to enhance efficiency and long-term growth.

“There has been an inefficient targeting of automation,” says MIT’s Daron Acemoglu, co-author of a published paper detailing the study’s results. “The higher the wage of the worker in a particular industry or occupation or task, the more attractive automation becomes to firms.” In theory, he notes, firms could automate efficiently. But they have not, by emphasizing it as a tool for shedding salaries, which helps their own internal short-term numbers without building an optimal path for growth.

The study estimates that automation is responsible for 52 percent of the growth in income inequality from 1980 to 2016, and that about 10 percentage points derive specifically from firms replacing workers who had been earning a wage premium. This inefficient targeting of certain employees has offset 60-90 percent of the productivity gains from automation during the time period.

“It’s one of the possible reasons productivity improvements have been relatively muted in the U.S., despite the fact that we’ve had an amazing number of new patents, and an amazing number of new technologies,” Acemoglu says. “Then you look at the productivity statistics, and they are fairly pitiful.”

The paper, “Automation and Rent Dissipation: Implications for Wages, Inequality, and Productivity,” appears in the May print issue of the Quarterly Journal of Economics. The authors are Acemoglu, who is an Institute Professor at MIT; and Pascual Restrepo, an associate professor of economics at Yale University.

Inequality implications

Dating back to the 2010s, Acemoglu and Restrepo have combined to conduct many studies about automation and its effects on employment, wages, productivity, and firm growth. In general, their findings have suggested that the effects of automation on the workforce after 1980 are more significant than many other scholars have believed. 

To conduct the current study, the researchers used data from many sources, including U.S. Census Bureau statistics, data from the bureau’s American Community Survey, industry numbers, and more. Acemoglu and Restrepo analyzed 500 detailed demographic groups, sorted by five levels of education, as well as gender, age, and ethnic background. The study links this information to an analysis of changes in 49 U.S. industries, for a granular look at the way automation affected the workforce. 

Ultimately, the analysis allowed the scholars to estimate not just the overall amount of jobs erased due to automation, but how much of that consisted of firms very specifically trying to remove the wage premium accruing to some of their workers. 

Among other findings, the study shows that within groups of workers affected by automation, the biggest effects occur for workers in the 70th-95th percentile of the salary range, indicating that higher-earning employees bear much of the brunt of this process. 

And as the analysis indicates, about one-fifth of the overall growth in income inequality is attributable to this sole factor.

“I think that is a big number,” says Acemoglu, who shared the 2024 Nobel Prize in economic sciences with his longtime collaborators Simon Johnson of MIT and James Robinson of the University of Chicago.

He adds: “Automation, of course, is an engine of economic growth and we’re going to use it, but it does create very large inequalities between capital and labor, and between different labor groups, and hence it may have been a much bigger contributor to the increase in inequality in the United States over the last several decades.” 

The productivity puzzle

The study also illuminates a basic choice for firm managers, but one that gets overlooked. Imagine a type of automation — call-center technology, for instance — that might actually be inefficient for a business. Even so, firm managers have incentive to adopt it, reduce wages, and oversee a less productive business with increased net profits.

Writ large, some version of this seems to have been happening to the U.S. economy since 1980: Greater profitability is not the same as increased productivity.

“Those two things are different,” says Acemoglu. “You can reduce costs while reducing productivity.” 

Indeed, the current study by Acemoglu and Restrepo calls to mind an observation by the late MIT economist Robert M. Solow, who in 1987 wrote, “You can see the computer age everywhere but in the productivity statistics.” 

In that vein, Acemoglu observes, “If managers can reduce productivity by 1 percent but increase profits, many of them might be happy with that. It depends on their priorities and values. So the other important implication of our paper is that good automation at the margins is being bundled with not-so-good automation.” 

To be clear, the study does not necessarily imply that less automation is always better. Certain types of automation can boost productivity and feed a virtuous cycle in which a firm makes more money and hires more workers. 

But currently, Acemoglu believes, the complexities of automation are not yet recognized clearly enough. Perhaps seeing the broad historical pattern of U.S. automation, since 1980, will help people better grasp the tradeoffs involved — and not just economists, but firm managers, workers, and technologists. 

“The important thing is whether it becomes incorporated into people’s thinking and where we land in terms of the overall holistic assessment of automation, in terms of inequality, productivity and labor market effects,” Acemoglu says. “So we hope this study moves the dial there.”

Or, as he concludes, “We could be missing out on potentially even better productivity gains by calibrating the type and extent of automation more carefully, and in a more productivity-enhancing way. It’s all a choice, 100 percent.”

Last week, we released apkeep version 1.0.0, the latest edition of our command-line Android package downloading software. Rather than indicating major changes for the project, this milestone instead signifies arriving at a relatively stable and mature place after gradual iteration on the project over the course of over four years.

What’s New in 1.0.0

We do have a few fresh features we’ve packed into this latest release, though—all focused on the Google Play Store: 

• You can now download a dex metadata file associated with an app containing a Cloud Profile, which provides information on app performance based on real usage. 
• You can now provide a token generated by the Aurora Store’s dispenser to log in anonymously for app downloads. 
• Users can specify their own device profiles when downloading apps from Google Play, which the store uses to deliver the app variant which works for your particular device specifications. 
• We’ve also fixed an authentication bug introduced by the Play Store API.

In addition to the various Linux, Windows, and Android environments we support, we’re also happy to announce that since the last release in October we’ve been included in Homebrew for macOS users!

How Researchers Use apkeep to Understand the Android App Landscape

Researchers and users contributed most of the features of this release, including downloading dex metadata containing Google’s Cloud Profiles. This feature helps them use the tool in their own research of highlighting how these Android compilation profiles can be a vital source of information for evaluating dynamic testing. Numerous other projects have cited apkeep usage in their own workflows. For example, Exodus Privacy uses it to power the εxodus tool’s downloads when they monitor the privacy properties of apps. Various research teams have noted their own use of the tool in whitepapers, including one team who used the tool to download 21,154 apps in a widespread study of Android evasive malware. We are proud to provide a reliable tool in the toolbox they use to power their work.

What’s in Store for apkeep?

Our goals with apkeep have remained constant: provide a reliable, fast, and safe way to download apps from multiple app providers, not just the Google Play Store. While we’ve focused on it as the major Android app provider of choice across much of the world, we’ve expanded support to other stores as well, such as F-Droid for downloading open source apps. We’d like to continue broadening apkeep’s list of supported providers, to make it easy to do comparative analysis of apps provided in different contexts. For this, we’d love your contributions.

How You Can Help

If you’re using apkeep as part of your own toolbox (whether using it to do malware analysis, auditing apps, or simply using it as an app archiving tool), let us know! And if you like what we do, please consider donating to EFF to support our work.

Since 1998, members of MIT’s BrainTrust club have helped Boston-area residents with brain injuries or other neurological disorders through their buddy program. The organization’s members also visit patients in nursing homes suffering from neurological issues.

BrainTrust is one of the founding chapters of Synapse National, an organization created by MIT alumna Alissa Totman ’13. Synapse’s goal is to provide social support for individuals living with brain injuries and to educate and inspire student leaders in the field of brain injury.

“Learning directly from individuals who had experienced brain injury during my time in BrainTrust gave me an appreciation of the gaps in resources and opportunities for improvement in brain injury care, which ultimately motivated me to pursue a career in brain injury medicine. My experience in BrainTrust continues to shape my approach to patient care and my professional goal of improving access to specialized care for individuals with brain injury by serving as a consulting provider in the acute care hospital, as well as by training the next generation of leaders in the field,” says Totman.

The club’s president, junior Karie Shen, who is pursuing a double major in biology (Course 7) and brain and cognitive science (Course 9), says, “BrainTrust is a student-run service organization that provides support for individuals with brain injury and other neurological disorders. I joined BrainTrust because it seemed like the perfect intersection of community service and neuroscience, and I care about these two things deeply.”

BrainTrust volunteers participate in training and then are paired with a local buddy who has experienced a brain injury. Members can also spend time on the weekends with patients in nursing homes who have dementia, Alzheimer’s disease, or who have had a stroke.

Shen, along with Elizabeth Zhang, president of the MIT Pre-Med Society, recently developed a program that allows BrainTrust members to visit patients in hospice. “It’s an experience that is deeply valuable for students. We work through a third-party organization called Compassus. Because the pairing process is HIPAA-protected, our role as BrainTrust executive members is to recruit students and connect them with the hospice volunteer coordinator for training. We also provide funding for transportation, generously supported by the UA Community Service Committee,” says Shen.

Shen, who plans to go to medical school and specialize in neurology, neuro-oncology, or geriatric medicine when she completes her degree, finds the experience rewarding, at times difficult, but also offers a glimpse into the reality of working with people with brain injuries.

“Visiting the people in hospice or a nursing home is hard. I’ve seen residents cry for no apparent reason that the nurses or I can understand. But I have also come to understand that caring for a patient’s quality of life and dignity is equally important. What I came to realize is that my presence itself mattered. That perspective has shaped how I think about the kind of physician I want to become,” says Shen.

First-year student Jordan Lacsamana heard about the club during Campus Preview Weekend and was immediately interested. Lacsamana, who will major in brain and cognitive sciences, is a volunteer in the Buddy Program and meets with her buddy at least once a month.

“I joined the club because it aligned with my interests academically, but I also wanted to support someone in the Boston community. I’m pre-med, and I’m interested in surgery, possibly neurosurgery or cardiovascular surgery. But I also think it’s nice to have someone outside of MIT to talk with. It’s great to learn more about them and have that one-on-one friendship, which really is the goal,” says Lacsamana.

Lacsamana says she enjoys spending time with Amanda, her buddy, and exploring Boston and Harvard Square, meeting for coffee or meals, and getting as much out of the relationship as Amanda does.

“I see her as a mentor because coming to Boston from Dallas was such a big change, so I’ve also been able to look to her for advice. But I think one of the great things about the program is that you get to learn more about them as an individual, instead of seeing them as just a person with an injury,” says Lacsamana.

“Many of our brain injury buddies simply enjoy being around students, staying connected to what we are learning and doing. Some have been with the club for years, even upwards of a decade, and still keep up with former student members long after they graduate. It is really wonderful to see how BrainTrust has created this web of friendships between people who would otherwise never have met,” says Shen.

“Amanda has stayed in touch with her former buddy since she graduated from MIT and is going to her wedding,” says Lacsamana. “I think it’s a testament to how amazing this program is at forming those connections.”

MIT students who seek real-world opportunities in fields such as cognitive science, health care, medicine, and cognitive/neurological prosthetics, or who want to help a local resident, can join BrainTrust. Email braintrust-exec@mit.edu for more information.

We'd all like the internet to be a better place—for kids and adults alike. But in the name of online safety, governments around the world are racing to impose a dangerous new system of control. Are age gates the silver bullet to the internet's problems they're being promoted as? Or are we being sold a bill of goods? We're answering this question and more in our latest EFFector newsletter.

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For over 35 years, EFFector has been your guide to understanding the intersection of technology, civil liberties, and the law. This latest issue covers an attack on VPNs in Utah, a livestream on how to disenshittify the internet, and California's proposed social media ban that could set a dangerous new precedent for online censorship.

Prefer to listen in? EFFector is now available on all major podcast platforms. This time, we're having a conversation with EFF Legislative Analyst Molly Buckley on why social media bans can't sidestep the U.S. constitution. You can find the episode and subscribe on your podcast platform of choice:

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Want to help push back on these misguided regulations? Sign up for EFF's EFFector newsletter for updates, ways to take action, and new merch drops. You can also fuel the fight for privacy and free speech online when you support EFF today!

The federal SECURE Data Act is not a serious consumer privacy bill, and its provisions—if enacted—would be a retreat from already insufficient state protections.

Republicans on the House Energy and Commerce Committee released a draft of the bill late last month without bipartisan support. The bill is weaker than congressional proposals in prior years, as well as most of the 21 state consumer privacy laws already on the books.

The bill could wipe out hundreds of  state privacy protections.

Most troubling for EFF: the bill would preempt dozens, if not hundreds, of state laws that regulate related topics, and it would not allow consumers to sue to protect their own rights (commonly called a private right of action). And it comes nowhere close to banning online behavioral advertising—a practice that fuels technology companies’ always increasing hunt for personal data.

The bill also suffers from many other flaws including weak opt-out defaults, inadequate data minimization requirements, and large definitional loopholes for companies.

Key Provisions

The bill would give consumers some rights to take action to control their personal data— like access, correction, deletion, and limited portability. These rights have become standard in all data privacy proposals in recent years.

The bill would also require companies to obtain your consent before processing your sensitive data, or using any of your personal data for a previously undisclosed purpose. Absent your consent, a company couldn’t do these things.

Further, the bill would allow you to opt out of (1) targeted third-party advertising, (2) the sale of your personal data, and (3) profiling of you that has a legal, healthcare, housing, or employment effect. Unfortunately, a company could keep doing these invasive things to you, unless you opted out.

The bill would also require data brokers that make at least 50 percent of their profits from the sale of personal data to register in a public database maintained by the Federal Trade Commission (FTC).

Preemption of Too Many State Laws

Federal privacy laws should allow states to build ever stronger rights on top of the federal floor. Many federal privacy laws allow this, including the Health Insurance Portability and Accountability Act, the Video Privacy Protection Act, and the Electronic Communications Privacy Act.

The SECURE Data Act would not do that. Instead, it would wipe out dozens, if not hundreds, of existing state privacy protections. Section 15 of the bill would preempt any “law, rule, regulation, requirement, standard, or other provision [that] relates to the provisions of this Act.” This would kill the 21 state consumer privacy laws passed in the past few years. These state bills aren’t strong enough, but they are still better than this federal proposal. For example, California maintains a data broker deletion tool and requires companies to comply with automatic opt-out signals—including one that is built into EFF’s Privacy Badger.

Because the SECURE Data Act has provisions that relate to data privacy and security, it could preempt all 50 state data breach laws and many others. It could also preempt state laws related to specific pieces of sensitive data, like bans on the sale of biometric or location information. Some states like California have constitutional provisions that protect an individual’s right to privacy, which can be enforced against companies. That constitutional provision, as well as state privacy torts, could also be in danger if this bill passed.

No Private Enforcement, A New Cure Period, and Vague Security Powers

Strong consumer privacy laws should allow consumers to take companies to court to defend their own rights. This is essential because regulators do not have the resources to catch every violation, and federal consumer enforcement agencies have been gutted during the current administration.

The SECURE Data Act does not have a private right of action. The FTC, along with state attorneys general, have primary enforcement authority. The law also gives companies 45 days to “cure” any violation with no penalty after they are caught.

Moreover, Section 8 of the bill creates a vaguely defined self-regulatory scheme in which companies can apply to be audited by an “independent organization” that will apply a “code of conduct.” Following this code of conduct would give companies a presumption that they are complying with the law. This provision is an implicit acknowledgement that the bill does not provide regulators with any new resources to enforce new protections.

Section 9 of the bill would give the Secretary of Commerce broad power to “take any action necessary and appropriate to support the international flow of personal data,” including assessing “security interests of the United States.” The scope of this amorphous provision is unclear, but it likely does not belong in a consumer protection bill.

Weak Privacy Defaults

Your online privacy should not depend on whether you have the time, patience, and knowledge to navigate a website and turn off invasive tracking. Good privacy laws build in data minimization requirements—meaning there should be a default standard that prevents companies from processing your data for purposes that are not needed to provide you with the service you asked for.

The SECURE Data Act puts the burden on you to opt out of invasive company practices, like targeted third-party advertising, the sale of your personal data, and profiling. The bill at least requires companies to obtain your consent before processing your sensitive data (like selling your precise location). These consent requirements, however, are often an invitation for companies to trick you into clicking a button to give away your rights in hard-to-read policies. Indeed, few people would knowingly agree to let a company sell their personal data to a broker who turns around and sells it to the government.

Section 3 of the bill uses the term “data minimization,” but it is done in name only. The provision does not limit a company’s processing of data to only what is necessary to provide the customer with the good or service they asked for. Instead, the provision limits processing of data to only what a company “disclosed to the customer”—meaning if it is in the confusing privacy policy that nobody reads, it is okay.

And the bill would not even allow you to restrict certain uses of your data. As companies seek more data for AI systems, many internet users do not want their private personal data to be used to train those models. However, the bill makes clear that “nothing in this Act may be construed to restrict” a company from collecting, using, or retaining your data to “develop” or “improve” a new technology.

Other Flawed Definitions and Loopholes

The bill has numerous loopholes that technology companies would exploit if the bill were to become law. Below is just a sampling:

• Government contractors: Under Section 13(b)(2), government contractors are exempt from the bill, which could be wrongly interpreted to exempt certain data brokers from sale restrictions when those sales are made to the government. This type of exemption could benefit surveillance companies like Clearview AI, which previously argued it was exempt from Illinois’ strict biometric law using a similar contractor exception. This is likely not the authors’ intention, since the definition of sale includes those made “to a government entity.”
  Sale definition: The definition in Section 16(28) is defined too narrowly. A sale should mean any exchange for monetary “or other valuable” consideration, as in some other privacy laws.
• Biometric information definition: The definition in Section 16(4) excludes data generated from a photo or video, and the definition excludes face scans not meant to “identify a specific individual.” This could be wrongly interpreted to allow biometric identification from security camera footage, or biometric use for sentiment or demographic analysis.
• Personal data definition: The definition in Section 16(21) exempts “de-identified data” from the definition of personal data, which could allow companies to do anything with de-identified data because that data is not protected by the law. The problem with de-identified data is that many times it is not.
• Deletion requests: With regard to data that a company obtained from a third-party, Section 2(d)(5) would treat a consumer’s deletion request merely as an opt-out request. And even if a customer requested deletion, a company might be able to retain the data for research purposes under section 11(a)(9)(A).
• Profiling definition: Under the definition in Section 16(25), companies could profile so long as the profiling is not “solely automated.” The flimsiest human review would exempt highly automated profiling.

Congress is long overdue to enact a strong comprehensive consumer data privacy law, and we have sketched what it should look like. But the SECURE Data Act is woefully inadequate. In fact, it would cause even more corporate surveillance of our personal information, by wiping out state laws that are more protective than this federal bill. Even worse, this bill would block state legislatures from protecting their residents from the privacy threats of tomorrow that are unforeseeable today. 

A new rowhammer attack gives complete control of NVIDIA CPUs.

On Thursday, two research teams, working independently of each other, demonstrated attacks against two cards from Nvidia’s Ampere generation that take GPU rowhammering into new—­and potentially much more consequential—­territory: GDDR bitflips that give adversaries full control of CPU memory, resulting in full system compromise of the host machine. For the attack to work, IOMMU memory management must be disabled, as is the default in BIOS settings.

“Our work shows that Rowhammer, which is well-studied on CPUs, is a serious threat on GPUs as well,” said Andrew Kwong, co-author of one of the papers. “...

The Trump administration is suing Vermont and New York for using novel tactics to curb greenhouse gas emissions.

A plan to postpone the retirement of the Ray Nixon Power Plant comes as Colorado wrestles with its climate targets.

A surge in diesel costs is set to ripple through the U.S. economy, raising prices on everything from groceries to housing and adding new political risk for Republicans.

New research shows that trees are cutting urban temperatures from climate change in half worldwide.

Never implemented amid a spate of legal challenges, the policy required companies to report material risks to their business due to a changing climate, as well as carbon emissions for some firms.