Surveillance technology vendors, federal agencies, and wealthy private donors have long helped provide local law enforcement “free” access to surveillance equipment that bypasses local oversight. The result is predictable: serious accountability gaps and data pipelines to other entities, including Immigration and Customs Enforcement (ICE), that expose millions of people to harm.

The cost of “free” surveillance tools — like automated license plate readers (ALPRs), networked cameras, face recognition, drones, and data aggregation and analysis platforms — is measured not in tax dollars, but in the erosion of civil liberties. 

The cost of “free” surveillance tools is measured not in tax dollars, but in the erosion of civil liberties.

The collection and sharing of our data quietly generates detailed records of people’s movements and associations that can be exposed, hacked, or repurposed without their knowledge or consent. Those records weaken sanctuary and First Amendment protections while facilitating the targeting of vulnerable people.   

Cities can and should use their power to reject federal grants, vendor trials, donations from wealthy individuals, or participation in partnerships that facilitate surveillance and experimentation with spy tech. 

If these projects are greenlit, oversight is imperative. Mechanisms like public hearings, competitive bidding, public records transparency, and city council supervision aid to ensure these acquisitions include basic safeguards — like use policies, audits, and consequences for misuse — to protect the public from abuse and from creeping contracts that grow into whole suites of products. 

Clear policies and oversight mechanisms must be in place before using any surveillance tools, free or not, and communities and their elected officials must be at the center of every decision about whether to bring these tools in at all.

Here are some of the most common methods “free” surveillance tech makes its way into communities.

Trials and Pilots

Police departments are regularly offered free access to surveillance tools and software through trials and pilot programs that often aren’t accompanied by appropriate use policies. In many jurisdictions, trials do not trigger the same requirements to go before decision-makers outside the police department. This means the public may have no idea that a pilot program for surveillance technology is happening in their city. 

The public may have no idea that a pilot program for surveillance technology is happening in their city.  

In Denver, Colorado, the police department is running trials of possible unmanned aerial vehicles (UAVs) for a drone-as-first-responder (DFR) program from two competing drone vendors: Flock Safety Aerodome drones (through August 2026) and drones from the company Skydio, partnering with Axon, the multi-billion dollar police technology company behind tools like Tasers and AI-generated police reports. Drones create unique issues given their vantage for capturing private property and unsuspecting civilians, as well as their capacity to make other technologies, like ALPRs, airborne. 

Functional, Even Without Funding 

We’ve seen cities decide not to fund a tool, or run out of funding for it, only to have a company continue providing it in the hope that money will turn up. This happened in Fall River, Massachusetts, where the police department decided not to fund ShotSpotter’s $90,000 annual cost and its frequent false alarms, but continued using the system when the company provided free access. 

 Police technology companies are developing more features and subscription-based models, so what’s “free” today frequently results in taxpayers footing the bill later.

In May 2025, Denver's city council unanimously rejected a $666,000 contract extension for Flock Safety ALPR cameras after weeks of public outcry over mass surveillance data sharing with federal immigration enforcement. But Mayor Mike Johnston’s office allowed the cameras to keep running through a “task force” review, effectively extending the program even after the contract was voted down. In response, the Denver Taskforce to Reimagine Policing and Public Safety and Transforming Our Communities Alliance launched a grassroots campaign demanding the city “turn Flock cameras off now,” a reminder that when surveillance starts as a pilot or time‑limited contract, communities often have to fight not just to block renewals but to shut the systems off.

 Importantly, police technology companies are developing more features and subscription-based models, so what’s “free” today frequently results in taxpayers footing the bill later. 

Gifts from Police Foundations and Wealthy Donors

Police foundations and the wealthy have pushed surveillance-driven agendas in their local communities by donating equipment and making large monetary gifts, another means of acquiring these tools without public oversight or buy-in.

In Atlanta, the Atlanta Police Foundation (APF) attempted to use its position as a private entity to circumvent transparency. Following a court challenge from the Atlanta Community Press Collective and Lucy Parsons Labs, a Georgia court determined that the APF must comply with public records laws related to some of its actions and purchases on behalf of law enforcement.
In San Francisco, billionaire Chris Larsen has financially supported a supercharging of the city’s surveillance infrastructure, donating $9.4 million to fund the San Francisco Police Department’s (SFPD) Real-Time Investigation Center, where a menu of surveillance technologies and data come together to surveil the city’s residents. This move comes after the billionaire backed a ballot measure, which passed in March 2025, eroding the city’s surveillance technology law and allowing the SFPD free rein to use new surveillance technologies for a full year without oversight.

Free Tech for Federal Data Pipelines

Federal grants and Department of Homeland Security funding are another way surveillance technology appears free to, only to lock municipalities into long‑term data‑sharing and recurring costs. 

Through the Homeland Security Grant Program, which includes the State Homeland Security Program (SHSP) and the Urban Areas Security (UASI) Initiative, and Department of Justice programs like Byrne JAG, the federal government reimburses states and cities for "homeland security" equipment and software, including including law‑enforcement surveillance tools, analytics platforms, and real‑time crime centers. Grant guidance and vendor marketing materials make clear that these funds can be used for automated license plate readers, integrated video surveillance and analytics systems, and centralized command‑center software—in other words, purchases framed as counterterrorism investments but deployed in everyday policing.

Vendors have learned to design products around this federal money, pitching ALPR networks, camera systems, and analytic platforms as "grant-ready" solutions that can be acquired with little or no upfront local cost. Motorola Solutions, for example, advertises how SHSP and UASI dollars can be used for "law enforcement surveillance equipment" and "video surveillance, warning, and access control" systems. Flock Safety, partnering with Lexipol, a company that writes use policies for law enforcement, offers a "License Plate Readers Grant Assistance Program" that helps police departments identify federal and state grants and tailor their applications to fund ALPR projects. 

Grant assistance programs let police chiefs fast‑track new surveillance: the paperwork is outsourced, the grant eats the upfront cost, and even when there is a formal paper trail, the practical checks from residents, councils, and procurement rules often get watered down or bypassed.

On paper, these systems arrive “for free” through a federal grant; in practice, they lock cities into recurring software, subscription, and data‑hosting fees that quietly turn into permanent budget lines—and a lasting surveillance infrastructure—as soon as police and prosecutors start to rely on them. In Santa Cruz, California, the police department explicitly sought to use a DHS-funded SHSP grant to pay for a new citywide network of Flock ALPR cameras at the city's entrances and exits, with local funds covering additional cameras. In Sumner, Washington, a $50,000 grant was used to cover the entire first year of a Flock system — including installation and maintenance — after which the city is on the hook for roughly $39,000 every year in ongoing fees. The free grant money opens the door, but local governments are left with years of financial, political, and permanent surveillance entanglements they never fully vetted.

The most dangerous cost of this "free" funding is not just budgetary; it is the way it ties local systems into federal data pipelines. Since 9/11, DHS has used these grant streams to build a nationwide network of at least 79–80 state and regional fusion centers that integrate and share data from federal, state, local, tribal, and private partners. Research shows that state fusion centers rely heavily on the DHS Homeland Security Grant Program (especially SHSP and UASI) to "mature their capabilities," with some centers reporting that 100 percent of their annual expenditures are covered by these grants. 

Civil rights investigations have documented how this funding architecture creates a backdoor channel for ICE and other federal agencies to access local surveillance data for their own purposes. A recent report by the Surveillance Technology Oversight Project (S.T.O.P.) describes ICE agents using a Philadelphia‑area fusion center to query the city’s ALPR network to track undocumented drivers in a self‑described sanctuary city.

Ultimately, federal grants follow the same script as trials and foundation gifts: what looks “free” ends up costing communities their data, their sanctuary protections, and their power over how local surveillance is used.

Protecting Yourself Against “Free” Technology

The most important protection against "free" surveillance technology is to reject it outright. Cities do not have to accept federal grants, vendor trials, or philanthropic donations. Saying no to "free" tech is not just a policy choice; it is a political power that local governments possess and can exercise. Communities and their elected officials can and should refuse surveillance systems that arrive through federal grants, vendor pilots, or private donations, regardless of how attractive the initial price tag appears. 

For those cities that have already accepted surveillance technology, the imperative is equally clear: shut it down. When a community has rejected use of a spying tool, the capabilities, equipment, and data collected from that tool should be shut off immediately. Full stop.

And for any surveillance technology that remains in operation, even temporarily, there must be clear rules: when and how equipment is used, how that data is retained and shared, who owns data and how companies can access and use it, transparency requirements, and consequences for any misuse and abuse. 

“Free” surveillance technology is never free. Someone profits or gains power from it. Police technology vendors, federal agencies, and wealthy donors do not offer these systems out of generosity; they offer them because surveillance serves their interests, not ours. That is the real cost of “free” surveillance.

I just noticed that the ebook version of Rewriring Democracy is on sale for $5 on Amazon, Apple Books, Barnes & Noble, Books A Million, Google Play, Kobo, and presumably everywhere else in the US. I have no idea how long this will last.

James J. Collins, the Termeer Professor of Medical Engineering and Science at MIT and faculty co-lead of the Abdul Latif Jameel Clinic for Machine Learning in Health, is embarking on a multidisciplinary research project that applies synthetic biology and generative artificial intelligence to the growing global threat of antimicrobial resistance (AMR).

The research project is sponsored by Jameel Research, part of the Abdul Latif Jameel International network. The initial three-year, $3 million research project in MIT’s Department of Biological Engineering and Institute of Medical Engineering and Science focuses on developing and validating programmable antibacterials against key pathogens.

AMR — driven by the overuse and misuse of antibiotics — has accelerated the rise of drug-resistant infections, while the development of new antibacterial tools has slowed. The impact is felt worldwide, especially in low- and middle-income countries, where limited diagnostic infrastructure causes delays or ineffective treatment.

The project centers on developing a new generation of targeted antibacterials using AI to design small proteins to disable specific bacterial functions. These designer molecules would be produced and delivered by engineered microbes, providing a more precise and adaptable approach than traditional antibiotics.

“This project reflects my belief that tackling AMR requires both bold scientific ideas and a pathway to real-world impact,” Collins says. “Jameel Research is keen to address this crisis by supporting innovative, translatable research at MIT.”

Mohammed Abdul Latif Jameel ’78, chair of Abdul Latif Jameel, says, “antimicrobial resistance is one of the most urgent challenges we face today, and addressing it will require ambitious science and sustained collaboration. We are pleased to support this new research, building on our long-standing relationship with MIT and our commitment to advancing research across the world, to strengthen global health and contribute to a more resilient future.”

Interesting research: “CHAI: Command Hijacking Against Embodied AI.”

Abstract: Embodied Artificial Intelligence (AI) promises to handle edge cases in robotic vehicle systems where data is scarce by using common-sense reasoning grounded in perception and action to generalize beyond training distributions and adapt to novel real-world situations. These capabilities, however, also create new security risks. In this paper, we introduce CHAI (Command Hijacking against embodied AI), a new class of prompt-based attacks that exploit the multimodal language interpretation abilities of Large Visual-Language Models (LVLMs). CHAI embeds deceptive natural language instructions, such as misleading signs, in visual input, systematically searches the token space, builds a dictionary of prompts, and guides an attacker model to generate Visual Attack Prompts. We evaluate CHAI on four LVLM agents; drone emergency landing, autonomous driving, and aerial object tracking, and on a real robotic vehicle. Our experiments show that CHAI consistently outperforms state-of-the-art attacks. By exploiting the semantic and multimodal reasoning strengths of next-generation embodied AI systems, CHAI underscores the urgent need for defenses that extend beyond traditional adversarial robustness...

The Department of Energy has identified more than three dozen coal plants that could power military installations, according to one official.

With its plans to revoke the endangerment finding, the administration is betting the Supreme Court will allow it to completely avoid regulating greenhouse gases.

It would be the first time a country attaches carbon reduction numbers to technologies that can pull climate pollution from the sky and seas.

Optimistic projections that minimize climate change are misleading institutional investors and governments, U.K. researchers have found.

The agency would be tasked with investigating suspected “weather modification” under new legislation.

The South American country is hosting an informal climate summit as progress stalls at U.N.-organized conferences.

Glaciers, snow and ice covered in the soot emitted by ships have less ability to reflect the sun.

Peter Liese, the European People's Party's lead on environmental issues, said his group wanted a “balanced” approach to overhauling the emissions cap-and-trade program.

Beekeepers are persisting in the face of floods, more powerful monsoons and extreme heat, as well as development that changes the landscapes bees rely on.

An Apparel Impact Institute report flagged three pressure points: higher carbon prices, rising raw-material costs and more expensive energy.

Nature Climate Change, Published online: 11 February 2026; doi:10.1038/s41558-026-02564-6

Early life stages are particularly critical for human brain development. A large-scale study in China shows that heat exposure in early life is associated with increased risks of delayed neurodevelopment in preschool children.

Nature Climate Change, Published online: 11 February 2026; doi:10.1038/s41558-026-02555-7

National greenhouse gas inventories systematically undercount methane and nitrous oxide emissions from wastewater due to outdated methods and incomplete coverage. Addressing these discrepancies is essential to strengthen transparency in global climate efforts and improving the effectiveness of national mitigation strategies.

Nature Climate Change, Published online: 11 February 2026; doi:10.1038/s41558-025-02540-6

The wastewater sector is a major source of non-CO2 emissions, but accurate emissions accounting remains challenging, despite guidelines for basic inventories provided by the IPCC. This research reveals that national inventories widely omit key sources and apply inconsistent methods, which lead to greatly under-reported emissions.

Nature Climate Change, Published online: 11 February 2026; doi:10.1038/s41558-026-02560-w

The authors use data from over 100,000 children (3–5.5 years old) across 551 Chinese cities, to show that risk of suspected neurodevelopmental delay increases under both prenatal and postnatal heat exposure. Steep increases at high temperatures highlight future potential vulnerability increases.

We are calling on technology companies like Meta and Google to stand up for their users by resisting the Department of Homeland Security's (DHS) lawless administrative subpoenas for user data. 

In the past year, DHS has consistently targeted people engaged in First Amendment activity. Among other things, the agency has issued subpoenas to technology companies to unmask or locate people who have documented ICE's activities in their community, criticized the government, or attended protests.   

These subpoenas are unlawful, and the government knowns it. When a handful of users challenged a few of them in court with the help of ACLU affiliates in Northern California and Pennsylvania, DHS withdrew them rather than waiting for a decision. 

These subpoenas are unlawful, and the government knowns it.

But it is difficult for the average user to fight back on their own. Quashing a subpoena is a fast-moving process that requires lawyers and resources. Not everyone can afford a lawyer on a moment’s notice, and non-profits and pro-bono attorneys have already been stretched to near capacity during the Trump administration.  

 That is why we, joined by the ACLU of Northern California, have asked several large tech platforms to do more to protect their users, including: 

1.  Insist on court intervention and an order before complying with a DHS subpoena, because the agency has already proved that its legal process is often unlawful and unconstitutional;  
2. Give users as much notice as possible when they are the target of a subpoena, so the user can seek help. While many companies have already made this promise, there are high-profile examples of it not happening—ultimately stripping users of their day in court;  
3. Resist gag orders that would prevent companies from notifying their users that they are a target of a subpoena. 

 We sent the letter to Amazon, Apple, Discord, Google, Meta, Microsoft, Reddit, SNAP, TikTok, and X.  

 Recipients are not legally compelled to comply with administrative subpoenas absent a court order 

 An administrative subpoena is an investigative tool available to federal agencies like DHS. Many times, these are sent to technology companies to obtain user data. A subpoena cannot be used to obtain the content of communications, but they have been used to try and obtain some basic subscriber information like name, address, IP address, length of service, and session times.  

Unlike a search warrant, an administrative subpoena is not approved by a judge. If a technology company refuses to comply, an agency’s only recourse is to drop it or go to court and try to convince a judge that the request is lawful. That is what we are asking companies to do—simply require court intervention and not obey in advance. 

It is unclear how many administrative subpoenas DHS has issued in the past year. Subpoenas can come from many places—including civil courts, grand juries, criminal trials, and administrative agencies like DHS. Altogether, Google received 28,622 and Meta received 14,520 subpoenas in the first half of 2025, according to their transparency reports. The numbers are not broken out by type.   

DHS is abusing its authority to issue subpoenas 

In the past year, DHS has used these subpoenas to target protected speech. The following are just a few of the known examples. 

On April 1, 2025, DHS sent a subpoena to Google in an attempt to locate a Cornell PhD student in the United States on a student visa. The student was likely targeted because of his brief attendance at a protest the year before. Google complied with the subpoena without giving the student an opportunity to challenge it. While Google promises to give users prior notice, it sometimes breaks that promise to avoid delay. This must stop.   

In September 2025, DHS sent a subpoena and summons to Meta to try to unmask anonymous users behind Instagram accounts that tracked ICE activity in communities in California and Pennsylvania. The users—with the help of the ACLU and its state affiliates— challenged the subpoenas in court, and DHS withdrew the subpoenas before a court could make a ruling. In the Pennsylvania case, DHS tried to use legal authority that its own inspector general had already criticized in a lengthy report.  

In October 2025, DHS sent Google a subpoena demanding information about a retiree who criticized the agency’s policies. The retiree had sent an email asking the agency to use common sense and decency in a high-profile asylum case. In a shocking turn, federal agents later appeared on that person’s doorstep. The ACLU is currently challenging the subpoena.  

Read the full letter here

The signals that drive many of the brain and body’s most essential functions — consciousness, sleep, breathing, heart rate, and motion — course through bundles of “white matter” fibers in the brainstem, but imaging systems so far have been unable to finely resolve these crucial neural cables. That has left researchers and doctors with little capability to assess how they are affected by trauma or neurodegeneration. 

In a new study, a team of MIT, Harvard University, and Massachusetts General Hospital researchers unveil AI-powered software capable of automatically segmenting eight distinct bundles in any diffusion MRI sequence.

In the open-access study, published Feb. 6 in the Proceedings of the National Academy Sciences, the research team led by MIT graduate student Mark Olchanyi reports that their BrainStem Bundle Tool (BSBT), which they’ve made publicly available, revealed distinct patterns of structural changes in patients with Parkinson’s disease, multiple sclerosis, and traumatic brain injury, and shed light on Alzheimer’s disease as well. Moreover, the study shows, BSBT retrospectively enabled tracking of bundle healing in a coma patient that reflected the patient’s seven-month road to recovery.

“The brainstem is a region of the brain that is essentially not explored because it is tough to image,” says Olchanyi, a doctoral candidate in MIT’s Medical Engineering and Medical Physics Program. “People don't really understand its makeup from an imaging perspective. We need to understand what the organization of the white matter is in humans and how this organization breaks down in certain disorders.”

Adds Professor Emery N. Brown, Olchanyi’s thesis supervisor and co-senior author of the study, “the brainstem is one of the body’s most important control centers. Mark’s algorithms are a significant contribution to imaging research and to our ability to the understand regulation of fundamental physiology. By enhancing our capacity to image the brainstem, he offers us new access to vital physiological functions such as control of the respiratory and cardiovascular systems, temperature regulation, how we stay awake during the day and how sleep at night.”

Brown is the Edward Hood Taplin Professor of Computational Neuroscience and Medical Engineering in The Picower Institute for Learning and Memory, the Institute for Medical Engineering and Science, and the Department of Brain and Cognitive Sciences at MIT. He is also an anesthesiologist at MGH and a professor at Harvard Medical School.

Building the algorithm

Diffusion MRI helps trace the long branches, or “axons,” that neurons extend to communicate with each other. Axons are typically clad in a sheath of fat called myelin, and water diffuses along the axons within the myelin, which is also called the brain’s “white matter.” Diffusion MRI can highlight this very directed displacement of water. But segmenting the distinct bundles of axons in the brainstem has proved challenging, because they are small and masked by flows of brain fluids and the motions produced by breathing and heart beats.

As part of his thesis work to better understand the neural mechanisms that underpin consciousness, Olchanyi wanted to develop an AI algorithm to overcome these obstacles. BSBT works by tracing fiber bundles that plunge into the brainstem from neighboring areas higher in the brain, such as the thalamus and the cerebellum, to produce a “probabilistic fiber map.” An artificial intelligence module called a “convolutional neural network” then combines the map with several channels of imaging information from within the brainstem to distinguish eight individual bundles.

To train the neural network to segment the bundles, Olchanyi “showed” it 30 live diffusion MRI scans from volunteers in the Human Connectome Project (HCP). The scans were manually annotated to teach the neural network how to identify the bundles. Then he validated BSBT by testing its output against “ground truth” dissections of post-mortem human brains where the bundles were well delineated via microscopic inspection or very slow but ultra-high-resolution imaging. After training, BSBT became proficient in automatically identifying the eight distinct fiber bundles in new scans.

In an experiment to test its consistency and reliability, Olchanyi tasked BSBT with finding the bundles in 40 volunteers who underwent separate scans two months apart. In each case, the tool was able to find the same bundles in the same patients in each of their two scans. Olchanyi also tested BSBT with multiple datasets (not just the HCP), and even inspected how each component of the neural network contributed to BSBT’s analysis by hobbling them one by one.

“We put the neural network through the wringer,” Olchanyi says. “We wanted to make sure that it’s actually doing these plausible segmentations and it is leveraging each of its individual components in a way that improves the accuracy.”

Potential novel biomarkers

Once the algorithm was properly trained and validated, the research team moved on to testing whether the ability to segment distinct fiber bundles in diffusion MRI scans could enable tracking of how each bundle’s volume and structure varied with disease or injury, creating a novel kind of biomarker. Although the brainstem has been difficult to examine in detail, many studies show that neurodegenerative diseases affect the brainstem, often early on in their progression.

Olchanyi, Brown and their co-authors applied BSBT to scores of datasets of diffusion MRI scans from patients with Alzheimer’s, Parkinson’s, MS, and traumatic brain injury (TBI). Patients were compared to controls and sometimes to themselves over time. In the scans, the tool measured bundle volume and “fractional anisotropy,” (FA) which tracks how much water is flowing along the myelinated axons versus how much is diffusing in other directions, a proxy for white matter structural integrity.

In each condition, the tool found consistent patterns of changes in the bundles. While only one bundle showed significant decline in Alzheimer’s, in Parkinson’s the tool revealed a reduction in FA in three of the eight bundles. It also revealed volume loss in another bundle in patients between a baseline scan and a two-year follow-up. Patients with MS showed their greatest FA reductions in four bundles and volume loss in three. Meanwhile, TBI patients didn’t show significant volume loss in any bundles, but FA reductions were apparent in the majority of bundles.

Testing in the study showed that BSBT proved more accurate than other classifier methods in discriminating between patients with health conditions versus controls.

BSBT, therefore, can be “a key adjunct that aids current diagnostic imaging methods by providing a fine-grained assessment of brainstem white matter structure and, in some cases, longitudinal information,” the authors wrote.

Finally, in the case of a 29-year-old man who suffered a severe TBI, Olchanyi applied BSBT to a scans taken during the man’s seven-month coma. The tool showed that the man’s brainstem bundles had been displaced, but not cut, and showed that over his coma, the lesions on the nerve bundles decreased by a factor of three in volume. As they healed, the bundles moved back into place as well.

The authors wrote that BSBT “has substantial prognostic potential by identifying preserved brainstem bundles that can facilitate coma recovery.”

The study’s other senior authors are Juan Eugenio Iglesias and Brian Edlow. Other co-authors are David Schreier, Jian Li, Chiara Maffei, Annabel Sorby-Adams, Hannah Kinney, Brian Healy, Holly Freeman, Jared Shless, Christophe Destrieux, and Hendry Tregidgo.

Funding for the study came from the National Institutes of Health, U.S. Department of Defense, James S. McDonnell Foundation, Rappaport Foundation, American SidS Institute, American Brain Foundation, American Academy of Neurology, Center for Integration of Medicine and Innovative Technology, Blueprint for Neuroscience Research, and Massachusetts Life Sciences Center.