Before the advancement of scientific data storage and collaboration via the cloud, medical investigators seeking health research breakthroughs had to overcome significant obstacles to collaboration and key clinical data gathering. 

Data were siloed and difficult to distribute, so those looking to undertake research had no option but to gather them themselves. This not only made research more expensive, but it was challenging to compare findings across datasets. 

In 1975, researchers studying arrhythmias at MIT and Boston’s Beth Israel Hospital envisioned another way: the team began collecting and digitizing electrocardiogram recordings with the intention of not only studying them, but of also making them available to the wider research community.

The team built their own computers for the process, painstakingly duplicated tapes one by one, and created more than 100,000 annotations for the recordings. The process took years, but by summer 1980, the tapes were finally ready. The team initially thought their tool would reach fewer than a dozen academic and industry groups. But interest kept pouring in. Over the next decade, they went on to mail about 100 copies. 

The data eventually became the first database of the global platform PhysioNet — founded in 1999 at the Harvard-MIT program in Health Sciences and Technology — as a clinical data repository for complex physiological signals. 

At the time, that type of data-sharing, which may seem like the default today, was a near-revolutionary idea. PhysioNet’s “founding was incredibly visionary,” says Thomas Heldt, Richard J. Cohen (1976) Professor in Medicine and Biomedical Physics, associate director of MIT’s Institute for Medical Engineering and Science, and the senior author of a recent paper in Nature Health examining the platform’s impact. 

Eventually, those magnetic tapes sent through the mail became burned CD-ROMs, which then evolved into FTP servers hosted on the newly minted internet. Today, as PhysioNet looks back at over 25 years of operation, the platform hosts hundreds of databases, and has become one of the most comprehensive biomedical and clinical data repositories in existence. Last year, more than 15,000 scientific publications cited PhysioNet, and users from more than 180 countries have registered on the platform. It is widely used by researchers, manufacturers, and clinical decision-makers.

“The research impact is truly significant,” says Heldt, who is also a professor in the MIT Department of Electrical Engineering and Computer Science and a principal investigator at the Research Laboratory of Electronics, “and quite humbling.” 

“It is really beautiful to see that such a vision has proven right and so enabling for so many people.”

Setting a standard 

Around 2009, a PhD student named Tom Pollard was conducting research on critically ill patients at one of London’s leading hospital systems. Although the hospital generated large volumes of valuable clinical data, the infrastructure and processes needed to curate and support their wider research use were still developing. 

“Hospital data were collected primarily to support immediate patient care, with less attention given to how they might be curated and reused for research,” says Pollard, now a research scientist at MIT’s Laboratory for Computational Physiology (LCP), technical director of PhysioNet, and the lead author on the Nature Health paper. 

The problem was not simply privacy. Hospital information systems were built primarily to support patient care and administration, not research. Data were fragmented across systems and rarely curated with future reuse in mind, making it difficult and expensive to turn them into coherent research resources.

But Pollard needed data to complete his dissertation. After poking around on the internet, he eventually discovered the Medical Information Mart for Intensive Care (MIMIC), a database of de-identified electronic health records hosted by PhysioNet. Recognizing its potential, his clinical supervisor, Kevin Fong, organized a visit to Boston. Soon afterward, Fong and Pollard were sitting across the table from Roger Mark, discussing how their teams might collaborate.

Academic incentives have long favored publications and exclusive analyses over the less-visible work involved in preparing data for others to use. That tension persists today. PhysioNet’s founders embraced a different model, believing that sharing research resources could accelerate discovery and ultimately improve human health, he says. MIMIC became central to Pollard’s dissertation, and after completing his PhD, he came to MIT to help build the next generation of the database. 

In the years since PhysioNet was established, the value of sharing research data has gained much wider recognition. The late Roger Mark, MIT’s distinguished professor of health sciences and technology emeritus and one of PhysioNet’s founders, described its purpose as building an “accessible multinational community around data” to “positively impact global health.”

Earlier this year, Mark and the late George Moody, PhysioNet’s co-founder, jointly received the prestigious IEEE Biomedical Engineering Award for their contributions to PhysioNet and biomedical signal processing. IEEE cited their “leadership in ECG signal processing and global dissemination of curated biomedical and clinical databases, thereby accelerating biomedical research worldwide.”

The source code for the platform, like much of its data, is public. According to the Nature piece: “As the platform evolved, PhysioNet’s community broadened substantially beyond its origins in signal processing and cardiovascular health to encompass clinical informatics, critical care and machine learning for health.” People have used that to build their own PhysioNet-esque infrastructure, says Heldt. Pollard points to similar platforms like Health Data Nexus as examples of PhysioNet’s legacy. 

Although there are now more resources out there hosting similar electronic health data, according to Google DeepMind researcher Vivek Natarajan, both PhysioNet and MIMIC “set the standard,” he says, “and it’s still the standard right now.”

That standard, according to those who use the platform, changed how research is conducted. Access to data should not be the determinant for which ideas are possible, according to Ziad Obermeyer, an associate professor at the University of California at Berkeley School of Public Health and the College of Computing, Data Science, and Society. 

“PhysioNet changed how I think about the bottleneck in research. It is often not ideas or talent. It is friction. When access to data is slow, expensive, and hard, the ideas that die first are the high-risk ones, the things that probably will not work, but would be transformative if they did. That is exactly the wrong model if you want real progress,” he says. “PhysioNet lowers the fixed cost of trying ambitious ideas, and that changes what science becomes possible.”

The AI boom

PhysioNet, once a repository mainly for those working in biomedical signal processing and the health-care fields, has evolved in its 25 years. Originally, the holdings consisted solely of cardiovascular ECG data. Now PhysioNet is a largely a source for electronic health records, imaging data, and software and AI models.  

Particularly as artificial intelligence approaches took off, “the community shifted,” Heldt explains. Those in need of signal processing data still use PhysioNet databases, but the pool of users has expanded to encompass staff at large tech companies, teachers, and practitioners in all areas of medicine, as well as researchers in health-related machine learning and AI. Today, that latter group “dominates the user community,” says Heldt. 

The platform hosts the highest-quality datasets available for health-care AI research, according to Natarajan, whose research involves AI, science, and medicine and who has published several papers that used its datasets. 

“It has been an important cornerstone that has catalyzed all the progress in health-care AI over the last decade,” says Natarajan. In addition to using PhysioNet data, he and his colleagues have contributed data to the platform, helping create the self-sustaining ecosystem that typifies PhysioNet. 

Looking toward the coming decades, stewards of the platform like Heldt and Pollard envision continuing to expand its reach with an annual conference. The team is also preparing to pilot a new system that will allow users to annotate data and contribute their own expertise, enriching PhysioNet’s resources for the next phase of the platform.

“The kind of research that people want to do now needs to be interdisciplinary. Statisticians, computer scientists, clinicians, pharmacists, and nurses must all come together and contribute their knowledge to develop algorithms that are useful for people” says Pollard. “The community has broadened, and advances in AI have expanded both the questions researchers can address and what they believe is possible.” 

Microsoft’s Secure Boot has had a serious vulnerability for most of its existence.

An industry-wide standard Microsoft invented to protect Windows, and later Linux, devices from firmware infections has been trivial to bypass for 13 of its 14 years of existence. The discovery was made by researchers at security firm ESET after identifying 11 firmware images, at least one from 2013, that were known to be defective but remained signed by the software company anyway.

The images are known as shims, which were invented to extend Secure Boot to Linux devices and utility software. Using a technique simple enough to be performed by novice hackers, these old, forgotten shims can be used to completely circumvent the protection, which is embedded into the UEFI (Unified Extensible Firmware Interface) of the device’s motherboard. The gaffe is the result of the failure by Microsoft, which oversees the signing of shims, to revoke the publicly available images once vulnerabilities were found in them...

President Donald Trump cast aside bipartisan precedent when he rejected eligible disaster requests from four blue states.

The bills would help the medical and education sectors prepare for the impacts of climate change.

The former Interior secretary’s new memoir calls for unity across the border to reverse Trump administration policies.

Washington state lawmaker April Berg made waves this week when she urged fellow legislators to avoid the bans and write smart regulations.

The People’s Party controls a majority of regional governments and faces flak for failing to prepare for the disaster.

Experts and officials say that climate change has increased the frequency of heat waves and periods of drought, extending periods of high risk for wildfires.

Earlier heat waves this summer showed how prolonged high temperatures tightened Europe’s power market.

The head of a financial services firm said that rising temperatures are now “a source of risk and return in any investment you have."

The government is counting on a new generation of Italians who see nuclear power as a source of low-carbon electricity and a tool to help fight climate change.

There’s new benchmark measuring AI’s ability to perform mathematical cryptanalysis. Anthropic’s frontier model actually found new attacks.

The benchmark: “CryptanalysisBench: Can LLMs do Cryptanalysis?” The idea is to benchmark the ability of LLMs to discover new mathematical cryptanalytic attacks against a series of historical algorithms.

Abstract: Cryptanalysis—the task of finding attacks against cryptographic schemes—its at the intersection of mathematical reasoning and cybersecurity, two areas where LLMs have advanced fastest. Cryptanalysis represents both a clean testbed for frontier reasoning (as practical attacks can be automatically verified) and a domain with unusually high stakes, since the primitives under study underpin our digital security. In this paper we ask whether LLMs can do cryptanalysis, and find that the answer is increasingly yes. We introduce CryptanalysisBench, 191 tasks across six families of cryptographic primitives (block ciphers, hash functions, etc.) drawn primarily from four NIST standardization competitions. Our benchmark consists of three tiers: (i) primitives with known practical breaks; (ii) primitives with no known practical break, evaluated both at full strength and as scaled-down variants; and (iii) a challenge set of production primitives at the frontier of cryptanalysis. Five frontier models (Claude Opus 4.8, Sonnet 5, Mythos 5, GPT-5.5, and the open-weights GLM-5.2) break 65%­86% of Tier 1 schemes, 6­12 Tier-2 schemes at full strength, and 24­61 across all scaled-down variants. Beyond deriving known results, models produce novel cryptanalysis, such as a key-recovery attack that exploits a design flaw in the SpoC AEAD and an error in KINDI’s published CCA-security proof, both to the best of our knowledge not previously known...

The concept of “surveillance pricing” is just one part of a much larger problem and business model: corporations maximizing their profits by invading our privacy. The all-too-common business model is to systematically harvest, collate, and store as much of our personal data as possible, and then monetize it through use and sale. When it comes to surveillance pricing, that looks like corporations offering the same product to two different people at two different prices, based on harvested personal information. That's why EFF supports A.B. 2654, authored by Assemblymember Chris Ward, which bans this harmful practice. 

As an organization based in San Francisco, EFF was proud to learn that the San Francisco Board of Supervisors had also introduced a resolution to similarly support the legislation. However,  we were disappointed to learn the San Francisco Board of Supervisors has since stalled a vote on the resolution stating their own support for A.B. 2654 after receiving an email from the San Francisco Chamber of Commerce criticizing the bill using well-worn and debunked concerns. We’ve sent the Supervisors a letter asking them to reconsider.

Banning surveillance pricing would be good for consumers. The FTC has found that companies will set higher prices based on personal information. “For instance,” the FTC found last year, “if a consumer is profiled as a new parent, the consumer may intentionally be shown higher-priced baby thermometers on the first page of their in-app search results, based on their residential zip code and time of purchase.” Let's say that again: the U.S. government has found that companies may seek to use surveillance pricing to charge parents searching for a thermometer in the middle of the night more money in a time of need.

Privacy is a human right, not something that people should understand as a currency to give away or protect based on how it will impact the price of groceries. EFF has long opposed pay-for-privacy schemes, in which a company charges a higher price to a customer who refuses to submit to processing of their personal data. Surveillance pricing is another version of that practice. You should never have to worry that your privacy rights depend on how much you make.

At a time when prices for everyday goods continue to climb, some surveillance pricing defenders note that using personal information could lead to lower prices for some consumers. Yet some recent studies indicate there will be losers and winners  based on factors such as whether a consumer is willing or able to switch products. Who loses or wins also will turn on the accuracy of the underlying data – yet surveillance pricing is often based on false information.

That said, even if surveillance pricing has the capability to lead to lower prices (which it often doesn't) we oppose it as just another way that corporations try to make customers pay for their privacy.

The San Francisco Chamber of Commerce’s concerns are fully addressed in the text of A.B. 2654. The Chamber raises questions about how businesses will comply with the law. But the bill is quite clear: “a retailer shall not engage in surveillance pricing.” It also has a clear definition of what “surveillance pricing” is. The banned practice is defined as: “[i] a customized price for a good for a specific consumer or group of consumers, [ii] based, in whole or in part, on personally identifiable information collected through electronic surveillance,” including if that information is “acquired from a third party.” In other words, “surveillance pricing” is a customized price based on personal information.

The SF  Chamber’s letter also asks about the bill's “treatment of discounts and loyalty programs.” In this way, too, A.B. 2654 is quite clear. The bill includes three broad carveouts that ensure it doesn't disrupt loyalty programs and discounts:

• First, for price differences “based solely on costs associated with providing the good to different consumers.”
• Second, for a discount offered to a consumer who is taking steps to terminate a service.
• Third, for a discount, conspicuously posted on a retailer’s website, that is uniformly available based on (1) criteria anyone can meet, such as signing up for a mailing list, (2) membership in a broadly defined group, such as seniors, or (3) participation in a loyalty program.

An opt-in senior discount to the movies is not the problem. The systematic collection of all of our personal information to determine whether someone is a senior and if so whether they should pay more or less for that matinee is. 

As we said in our blog post outlining our support for this bill:

Surveillance pricing is very similar to online behavioral advertising, a business practice that EFF urges governments to ban. Both practices incentivize all businesses to collect as much of our personal data as possible, in order to later monetize it. Both practices lead some businesses to collate and store our data into dossiers about us for later use. Both practices use these surveillance-based dossiers to manipulate and limit our economic choices, by altering the advertisements and prices we see online.

We urge the San Francisco Board of Supervisors to join the coalition of groups that support A.B. 2564, and stand against companies mining our personal information to charge us different prices for the same thing. 

You can read our letter to the Supervisors here.

Robert E. Cohen, the Raymond A. (1921) and Helen E. St. Laurent Professor of Chemical Engineering, Emeritus, whose pioneering research helped shape the fields of polymers and soft matter while inspiring generations of students, passed away peacefully on July 9 following a long battle with Parkinson's disease. He was 79.

"Bob Cohen was an innovator in every sense of the word: in his research, his approach to mentorship, and in every aspect of our community at MIT," says Kristala Prather '94, the Arthur D. Little Professor and head of the Department of Chemical Engineering (ChemE). "Bob combined extraordinary intellect with remarkable humility. As a teacher, colleague, advisor, and friend, he had a gift for making people feel respected, valued, and heard. That generosity shaped every part of his work and inspired everyone fortunate enough to know him."

During more than four decades at MIT, Cohen continually reimagined how chemical engineering students should be educated. Recruited for his expertise in polymer science, he brought to MIT the polymer laboratory course he had developed during his postdoctoral work at the University of Oxford, establishing class 10.467 (Polymer Science Laboratory). The rigorous undergraduate course introduced generations of students to polymer synthesis, physical chemistry, and the evaluation of mechanical properties through hands-on experimentation.

In 1986, Cohen founded the Program in Polymer Science and Technology, now known as the Program in Polymers and Soft Matter (PPSM). Recognizing that advances in polymer science require expertise spanning chemistry, physics, engineering, and materials science, he created one of MIT's first truly interdisciplinary graduate programs. PPSM continues to prepare doctoral students to tackle complex challenges across the broad field of polymers and soft materials.

"Bob Cohen is the reason I returned to MIT as a graduate student," says Paula Hammond '84, PhD '93, Institute professor, dean of the School of Engineering, and a PPSM alumna. "His vision for multidisciplinary polymer education was unlike anything I had experienced. I benefited from him as a teacher in the classroom, as a member of my thesis committee, and a life-long mentor. As a department head, I saw firsthand the extraordinary impact he had on generations of students and on the field itself."

Cohen also conceived the unique PhD in chemical engineering practice (PhDCEP) degree, recognizing that future leaders in chemical engineering would benefit from combining advanced research with industrial experience and business education. The first and only program if its kind, the PhDCEP program integrates coursework, MIT's renowned David H. Koch School of Chemical Engineering Practice, doctoral research, and study at the MIT Sloan School of Management. 

Cohen also founded and directed the DuPont/MIT Alliance from 2000 to 2012, creating a highly successful partnership that brought together researchers from MIT and DuPont to develop innovative materials and manufacturing technologies. The collaboration advanced research in bioelectronics, biomimetic materials, alternative energy, and metabolic engineering, while fostering lasting collaborations across disciplines.

Cohen was a prolific collaborator whose pioneering research established him as one of the world's leading chemical engineers. His contributions include omniphobic surfaces, block copolymer nanoreactors for inorganic cluster synthesis, tough-stiff nanocomposites, chain folding in confined geometries, and layer-by-layer assemblies at the biotic-abiotic interface. Yet when asked about his proudest accomplishments, he rarely pointed to his scientific discoveries. Instead, he spoke about his students, and took immense pride in watching many former PhD students go on to become faculty members and leaders at top institutions around the world.

Raised in Oil City, Pennsylvania, Cohen developed an early appreciation for chemical engineering. After earning his master's and doctoral degrees from Caltech and completing a postdoctoral fellowship at the University of Oxford, he joined the MIT faculty in 1973. Over the next four decades, he became internationally recognized as a groundbreaking researcher, educator, entrepreneur, and mentor. 

Cohen was a member of the National Academy of Engineering and the American Academy of Arts and Sciences, as well as a fellow of the American Institute of Chemical Engineers, the Polymer Division of the American Chemical Society, the American Physical Society and the Materials Research Society. Cohen co-founded MatTek Corp., helping translate advances in biomaterials into practical applications.

Although Cohen received many prestigious honors throughout his career, he often said the award that meant the most to him was the inaugural Paul J. Flory Polymer Education Award, presented by the American Chemical Society in 2012. The honor recognized his leadership in building the interdisciplinary PPSM program and transforming undergraduate polymer education. Fittingly, it celebrated what he valued most: helping students discover their potential.

Cohen is survived by his beloved wife, Jane; his son, Eliot Cohen, his wife Jacqueline Aldred Cohen, and their children Ada, Brennan, and Callan; his daughter, Genevieve Cohen, and her daughter Emma; his sister, Nancy Stein, and her husband Herb; sisters-in-law Lee Woodman and Betsy Woodman; brother-in-law Wally Coleman; and many beloved nieces and nephews.

A memorial service is scheduled for Oct. 17 at the MIT Chapel. In lieu of flowers, donations may be made in Cohen’s memory to the Michael J. Fox Foundation.

MIT alumni Yu Deng ’11 and Hong Wang PhD ’19 were among the four young mathematicians awarded Fields Medals on July 23 at the 2026 International Congress of Mathematicians (ICM). The other two honorees were John Pardon and Jacob Tsimerman.

The Fields Medal is awarded once every four years at the ICM, and is regarded as one of the highest honors a mathematician can receive. 

Yu Deng received his BS in mathematics at MIT in 2011, and was a Putnam Fellow in 2010. He earned his Fields Medal for his work in partial differential equations (PDE), including the rigorous derivation of the Boltzmann equation from hard-sphere dynamics for rarefied gases, the derivation of wave kinetic equations from nonlinear dispersive systems, and probabilistic approaches to nonlinear Schrödinger dynamics. His first published paper (in Analysis & PDE) was on the latter topic, and stemmed from summer research conducted at MIT on a problem suggested by Gigliola Staffilani. Deng is currently a professor at the University of Chicago.

Hong Wang received her PhD at MIT in 2019 under the supervision of Larry Guth PhD ’05. She is awarded the Fields Medal for her work in harmonic analysis and geometric measure theory, including applications of multiscale and decoupling techniques to the local smoothing conjecture for the planar wave equation, and other major advances such as the solution of the Kakeya problem in three dimensions (with Joshua Zahl). As a student in the department, she was a graduate mentor in the Summer Program in Undergraduate Research (SPUR) and, alongside her mentee, was awarded the Hartley Rogers Jr. SPUR Prize, presented to the best student-mentor team. Wang, a Silver Professor of Mathematics at New York University and a professor at the Institut des Hautes Études Scientifiques in Paris, is the third woman ever to win a Fields Medal.

“The achievements of Yu Deng and Hong Wang are truly monumental, and we are all elated that they were awarded Fields Medals,” department head and RSA Professor of Mathematics Michel Goemans says. “Their success is a testimony of the amazing mathematical talent we have at all levels at MIT, and the top-quality education, mentorship, and research opportunities we provide to both our large pool of math majors and our PhD students, during their lifelong mathematical journey.” 

Goemans adds, “MIT is a unique and exciting place to learn mathematics, and I am sure we have more future Fields medalists among our students and junior members of the department.”

Recent reports have raised alarm about the use of PatronScan, an ID-checking and face-scanning system, at multiple LGBTQ+ bars in San Francisco’s Castro neighborhood. Much of the attention has focused on reports that the system photographs patrons as they enter venues and questions about whether those images are used for facial recognition.

A broader privacy concern also deserves scrutiny. For years, PatronScan has marketed itself not just as an ID-verification tool, but as a system that allows bars and clubs to identify patrons, keep records about them, and share information across venues. As one news article published in 2019 documented, PatronScan built a network that allowed participating bars to flag patrons and share information about them with other establishments. 

And in California, it’s not at all clear how PatronScan’s business model of scanning IDs and sharing the information from those scans with other bars comports with the law. California’s ID privacy law, which was amended in 2018 to add ID “scans,” states that no businesses shall “retain or use” any information from a scanned ID card except for limited purposes such as to verify age, comply with a legal requirement, or prevent fraud. 

A venue cannot claim to be a safe space while feeding its patrons’ data to a third party database.

Californians should be deeply concerned about businesses that collect information from government-issued IDs and use it to build databases about where people go, whom they associate with, and whether they should be allowed into other public gathering places. That concern is especially strong in LGBTQ+ spaces, which have long served as refuges for people to go without being tracked, monitored, or put on lists. 

We reached out to Patronscan with questions regarding their practices and their views on California ID law. They referred us to their published FAQ question “Is Patronscan privacy compliant in California?” which claims that the use of Patronscan kiosks is legal in California. They also said “Patronscan does not do facial recognition in North America, or any kind of automated analysis of the ID or the live photo image.” 

The California Legislature Has Investigated PatronScan’s Business Model 

In 2018, the California Legislature published bill analyses that went into detail about PatronScan’s business. Reviewing PatronScan's own materials, the California Senate Judiciary Committee found that the company had collected and retained information on 561,087 customers in Sacramento alone during the first five months of 2018—a remarkable figure for a city whose population had only recently topped 500,000.

Lawmakers also found that at that time, PatronScan retained information for at least 90 days or longer in some cases, shared information among participating bars, and maintained bans that lasted an average of more than 19 years. A PatronScan “Public Safety Report” used 10,000 scans collected on a single day to report on “where customers live, how far they have traveled, and how many different venues the customers patronized.” 

This was not simply checking IDs at the door. PatronScan was building a database. 

An immigrants’ rights group, the Coalition for Human Immigrant Rights (CHIRLA), wrote about its concern at the time with these growing ID databases, saying that “placing individuals on a database that labels them a "threat to public safety" has “significant immigration consequences that could lead to deportation, revoking of current status, or denial of future immigration relief.” 

Today, Patronscan states that it retains personal information about all customers for 21 days, and about flagged customers for up to five years. This includes the customer’s name, date of birth, photograph, gender, and zip code. It also includes the dates and times that the customer entered particular bars. Such databases are a grave privacy threat. Personal data is routinely stolen by thieves, misused by a company’s employees, seized by government agencies, and diverted to new purposes by a company’s executives. 

California Law Still Bans ID-Scan Databases, And Bars Should Follow That Law

In 2018, California lawmakers closed what they viewed as a loophole. Existing law already prohibited businesses from retaining or using information obtained when they “swiped” a driver's license, except for the narrow purposes of legal requirements (like a judicial warrant) or “preventing fraud, abuse, or material misrepresentation.” 

After reviewing companies like PatronScan, the Legislature amended the law to make clear that the same restrictions that apply to businesses that “swipe” ID cards also apply when those IDs are “scanned.” PatronScan opposed that change, arguing it wanted to preserve the ability to share information among bars so participating venues could decide whether to admit patrons.

The bill became law anyway. Yet PatronScan continues to market and sell a system that apparently retains information from scanned IDs, and allows participating venues to flag patrons and share information across its network. 

At a minimum, that raises serious questions about how those practices fit with California's existing ID privacy law. Bar and nightlife venue owners who utilize PatronScan should think twice about its effects on their customers, and consider going back to standard, visual ID checks. These physical checks have been effective at keeping underage patrons out of 21-and-over venues for decades, and don’t present the serious privacy dangers of creating a private database of bar patrons. 

For venues serving vulnerable communities like immigrants or the LGBTQ+ community, the stakes of using this technology are even higher. It’s disappointing and alarming to see some of California’s more well-known LGBTQ+ nightlife spots instead lining up as PatronScan’s early adopters. A venue cannot claim to be a safe space while feeding its patrons’ data to a third party database. These businesses should reject PatronScan, return to the standard ID checks that every other bar has been able to utilize, and prove to their customers that their privacy and security still matters. 

Governments are switching, but I’m not sure it makes a difference:

…some municipalities, including Denver, Colorado, are ditching their Flock arrays. But keep in mind that if they’re only switching from Flock to another brand of license-plate readers, like Axon, it’s like a gambling addict trying to kick the habit by switching from FanDuel to DraftKings.

[…]

Despite what you may read on the Flock website, Axon cameras are pretty effective when it comes to hoovering up personal details that can go far beyond your license plate numbers. That means a municipality that opts for Axon cameras instead of Flock units won’t necessarily reduce the amount privacy its citizens lose through their use...

The fossil fuel industry has argued that federal law bars the lawsuit. But local Colorado governments say it’s an appropriate exercise of state power.

Food and housing insecurity, chronic illness, and mental health challenges persist among many families.

The governor’s support signals momentum behind rethinking how the state pays for the cost of natural disasters.