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AI Overview
The immense computing power housed in AI data centers is directly driving a massive expansion in global and domestic surveillance. These facilities provide the necessary infrastructure to ingest, process, and analyze vast amounts of data—from facial recognition feeds to location tracking—for law enforcement and government agencies.
How AI Data Centers Power Surveillance
Predictive Policing & Data Brokers: Data centers process massive, warrantless collections of data, such as geolocation and web-browsing information purchased from data brokers. This allows law enforcement agencies to build geospatial heat maps to predict crime trends.
Real-Time Crime Centers: Platforms aggregate feeds from widespread sources (like automatic license plate readers and public CCTV cameras) into searchable, AI-powered networks. Officers can use natural language searches to track specific vehicles, bystanders, or suspects.
Global Monitoring: At a larger scale, AI data center architecture enables widespread public surveillance, such as real-time tracking of dissidents and monitoring of crowds using biometric scanning.
Physical Security Inside the Facilities
Interestingly, these data centers also use AI for their own physical surveillance. Operators use AI-powered cameras with video analytics to secure server racks, prevent unauthorized access (such as "tailgating"), and guide automated emergency responses.
Privacy & Public Concern
Civil rights organizations, including the American Civil Liberties Union, frequently cite "mission creep" regarding this technology. Tools originally justified for specific security applications are now increasingly used to monitor everyday citizens. If left unchecked, privacy advocates warn that these networks could facilitate an unprecedented digital surveillance state.
And:
Data centers play a central role in mass surveillance by serving as the physical infrastructure where vast amounts of personal information are stored, processed, and analyzed. While data centers themselves are neutral facilities designed for general business functions, they can be utilized for surveillance when government agencies or corporations gain legal—or sometimes unauthorized—access to the data housed within them.
How Data Centers Facilitate Surveillance
Mass Storage: Agencies like the NSA use massive facilities, such as the Utah Data Center, to store billions of communications, including emails and text messages, for later analysis.
Legal "Loopholed" Access: Under Section 702 of the Foreign Intelligence Surveillance Act (FISA), the U.S. government can compel providers to hand over data. Recent legislative changes have attempted to broaden the definition of service providers to include almost any business with access to communication equipment, potentially including data center operators.
The Data Broker Loophole: To bypass warrant requirements, some federal agencies simply purchase bulk personal data—such as location history and web browsing habits—from data brokers who store this information in commercial data centers.
AI Supercharging: Advanced AI models running in these centers can now process "unclassified bulk data" to recreate people's movements, associations, and daily habits at an unprecedented scale.
Real-World Examples of Monitoring
Internet Traffic Splitting: Whistleblowers have previously revealed that major telecommunications companies installed hardware at their facilities to provide the NSA with full copies of all fiber-optic internet traffic.
Targeted Programs: Programs like PRISM allow intelligence agencies to collect data directly from the servers of major technology companies.
Corporate Monitoring: Beyond government spying, data centers enable companies to track worker productivity through keystroke monitoring and facial expression analysis, practices that are legal in many states.
Privacy and Policy Responses
Digital rights organizations like the Electronic Frontier Foundation (EFF) and the ACLU frequently advocate for national privacy bills and the closure of data broker loopholes to limit warrantless mass surveillance. They argue that the current "mission creep" of surveillance technology—initially intended for foreign intelligence but increasingly used on domestic citizens—undermines basic civil liberties.
Artificial intelligence (AI) offers many promising applications. Algorithms and machine learning can help develop new drugs and target treatment in effective ways. AI also plays a role in tracking climate change by monitoring weather patterns. Wildlife experts have coupled AI with satellite imagery to monitor how endangered species are faring and where threats are appearing.
But there is a dark side to AI as well, given its potential for nefarious purposes. Concerns around privacy, safety and security have grown as the technology is used to analyze confidential material and amplify false narratives as part of disinformation campaigns. Due to its scalability and capacity to examine large data sets, it can study people’s behavior and act on that information.
Perhaps the starkest example is in China, where AI enables surveillance on a widespread scale. Coupled with social media monitoring, cameras, and facial recognition, the technology enables authorities to track dissidents and government critics and identify their statements and locations. There is infrastructure in place that can integrate information from a variety of sources and analyze it in real time for government authorities.
Concerns over AI surveillance echo the fears surrounding TikTok’s data-sharing practices with Chinese authorities, including the collection of users’ personal details and content interactions. U.S. officials have flagged this as a national security threat, contributing to Congress’ decision to ban TikTok in 2024.
However, AI surveillance may no longer be just a foreign government threat. Reports have surfaced about potential abuses in the U.S., including government contracts that may enable the Department of Homeland Security (DHS) to monitor social media. According to the Politico Digital Future newsletter, “the contractors advertise their ability to scan through millions of posts and use AI to summarize their findings” for their clients. With major agencies, law enforcement, and intelligence services now in the hands of Trump loyalists, this monitoring capability is a particular concern right now when the administration is going after its critics.
DHS later confirmed it is using digital tools to analyze social media posts from individuals applying for visas or green cards. The surveillance software would search for any signs of “extremist” rhetoric or “antisemitic activity.” The announcement raised questions about how these terms would be defined and whether public criticism of certain countries could be used to label applicants as “terrorist sympathizers.”
Other reports suggest that surveillance has already occurred within the Environmental Protection Agency (EPA). According to sources quoted by Reuters, “some EPA managers were told by Trump appointees that Musk’s team is rolling out AI to monitor workers, including looking for language in communications considered hostile to Trump or Musk.” The EPA has denied the report, calling it “categorically false.”
It is not just the American government that is getting into the monitoring act. Some U.S. companies already engage in workplace surveillance of their employees for business purposes. In the absence of a national privacy bill, there are few legal safeguards to limit workplace computer or network surveillance—or even to require that such monitoring be disclosed. Employers can track what workers do on their computers, even if they are using their equipment at home as part of hybrid work. Some firms even go as far as monitoring keystrokes or facial expressions to see what people are doing, who may be underperforming, and whether they are obeying company policies. These digital practices are perfectly legal in many states.
Overall, it is a risky time for AI-based surveillance because we have a combination of advanced digital technologies, high-level computing power, abundant and non-secured data, data brokers who buy and sell information, and a risky political environment. It is the confluence of each of these factors that endanger people’s freedoms and ability to express themselves in an open manner. As AI surveillance grows, individual freedom diminishes, and the risks of government and corporate overreach rise.
A national privacy bill could help mitigate some of these threats by establishing privacy standards and blocking some of the most dangerous practices, but it would not be a comprehensive solution.
Further, U.S. government agencies should be barred from using AI or facial recognition software to spy on individuals or monitor their public statements on social media. Using such tools to track what people say about public officials could cross into undemocratic territory for the United States.
On a Saturday morning, you head to the hardware store. Your neighbors’ Ring cameras film your walk to the car. Your car’s sensors, cameras and microphones record your speed, how you drive, where you’re going, who’s with you, what you say, and biological metrics such as facial expression, weight and heart rate. Your car may also collect text messages and contacts from your connected smartphone.
Meanwhile, your phone continuously senses and records your communications, info about your health, what apps you’re using, and tracks your location via cell towers, GPS satellites and Wi-Fi and Bluetooth.
As you enter the store, its surveillance cameras identify your face and track your movements through the aisles. If you then use Apple or Google Pay to make your purchase, your phone tracks what you bought and how much you paid.
All this data quickly becomes commercially available, bought and sold by data brokers. Aggregated and analyzed by artificial intelligence, the data reveals detailed, sensitive information about you that can be used to predict and manipulate your behavior, including what you buy, feel, think and do.
Companies unilaterally collect data from most of your activities. This “surveillance capitalism” is often unrelated to the services device manufacturers, apps and stores are providing you. For example, Tinder is planning to use AI to scan your entire camera roll. And despite their promises, “opting out” doesn’t actually stop companies’ data collection.
While companies can manipulate you, they cannot put you in jail. But the U.S. government can, and it now purchases massive quantities of your information from commercial data brokers. The government is able to purchase Americans’ sensitive data because the information it buys is not subject to the same restrictions as information it collects directly.
The federal government is also ramping up its abilities to directly collect data through partnerships with private tech companies. These surveillance tech partnerships are becoming entrenched, domestically and abroad, as advances in AI take surveillance to unprecedented levels.
As a privacy, electronic surveillance and tech law attorney, author and legal educator, I have spent years researching, writing and advising about privacy and legal issues related to surveillance and data use. To understand the issues, it is critical to know how these technologies function, who collects what data about you, how that data can be used against you, and why the laws you might think are protecting your data do not apply or are ignored.
Big money for AI-driven tech and more data
Congressional funding is supercharging huge government investments in surveillance tech and data analytics driven by AI, which automates analysis of very large amounts of data. The massive 2025 tax-and-spending law netted the Department of Homeland Security an unprecedented US$165 billion in yearly funding. Immigration and Customs Enforcement, part of DHS, got about $86 billion.
Disclosure of documents allegedly hacked from Homeland Security reveal a massive surveillance web that has all Americans in its scope.
DHS is expanding its AI surveillance capabilities with a surge in contracts to private companies. It is reportedly funding companies that provide more AI-automated surveillance in airports; adapters to convert agents’ phones into biometric scanners; and an AI platform that acquires all 911 call center data to build geospatial heat maps to predict incident trends. Predicting incident trends can be a form of predictive policing, which uses data to anticipate where, when and how crime may occur.
Privacy risks of using AI to collect data
The U.S. Government Accountability Office identified 10 privacy risks in collecting data using systems that include artificial intelligence. The report, published on March 26, 2026, also included a longer list of challenges to preserving privacy while collecting data using AI.
List of 10 items
Data persistence Data may continue to exist in AI systems and be difficult to extract/remove once collected.
Data re-identification AI has the ability to cross-reference multiple data sets from seemingly independent and anonymous outputs to reidentify anonymized data.
Generation of deceptive or inaccurate outputs AI may be used to intentionally or unintentionally generate deceptive outputs (e.g., deepfakes) or inaccurate outputs (e.g., hallucinations) that may result in harm towards individuals.
Improper disclosure AI can reveal and cause improper sharing of individuals’ data when it infers additional sensitive information from raw data.
Increased accessibility to sensitive information AI can make sensitive information more accessible to a wider audience (e.g., data brokers) than intended.
Invasion of privacy from data aggregation AI may combine various pieces of data about a person to make inferences beyond what is explicitly captured in those data (e.g., social scoring), which can invade an individuals’ personal space and solitude by revealing private information (e.g., health-related, financial, location).
Lack of security over data Inadequate AI data requirements and storage practices can result in data breaches and improper access.
Lack of transparency related to data use AI may be used without providing individuals with notice and control over how their data is being used.
Lack of transparency in AI model algorithmic decision-making The workings of AI models could include decisions based on individual data that one is unaware of and that can lead to privacy risks.
Secondary use of data The use of personal data for purposes other than originally intended can be exacerbated by AI’s ability to repurpose data.
DHS has also spent millions on AI-driven software used to detect sentiment and emotion in users’ online posts. Have you been complaining about Immigration and Customs Enforcement policies online? If so, social media companies including Google, Reddit, Discord, and Facebook and Instagram owner Meta may have sent identifying data, such as your name, email address, phone number and activity, to DHS in response to hundreds of DHS subpoenas served on the companies.
Meanwhile, the Trump administration’s national policy framework for artificial intelligence, released on March 20, 2026, urges Congress to use grants and tax incentives to fund “wider deployment of AI tools across American industry” and to allow industry and academia to use federal datasets to train AI.
Using federal datasets this way raises privacy law concerns because they contain a lifetime of sensitive details about you, including biographical, employment and tax information.
Blurring lines and little oversight
In foreign intelligence work, the funding, development and controlled use of certain AI-driven gathering of data makes sense. The CIA’s new acquisition framework to turbocharge collaboration with the private sector may be legal with proper oversight. But the line between collaborating for lawful national security purposes versus unlawful domestic spying is becoming dangerously blurred or ignored.
For example, the Pentagon has declared a contractor, Anthropic, a national security risk because Anthropic insisted that its powerful agentic AI model, Claude, not be used for mass domestic surveillance of Americans or fully autonomous weapons.
On March 18, 2026, FBI Director Kash Patel confirmed to Congress that the FBI is buying Americans’ data from data brokers, including location histories, to track American citizens.
As the federal government accelerates the use of and investment in AI-driven spy tech, it is mandating less oversight around AI technology. In addition to the national AI policy framework, which discourages state regulation of AI, the president has issued executive orders to accelerate federal government adoption of AI systems, remove state law AI regulation barriers and require that the federal government not procure the use of AI models that attempt to adjust for bias. But using advanced AI systems is risky, given reports of AI agents going rogue, exposing sensitive data and becoming a threat, even during routine tasks.
Your data
The surveillance capitalism system requires people to unwittingly participate in a manipulative cycle of group- and self-surveillance. Neighborhood doorbell cameras, Flock license plate readers and hyperlocal social media sites like Nextdoor create a crowdsourced record of all people’s movements in public spaces.
Sensors in phones and wearable devices, such as earbuds and rings, collect ever more sensitive details. These include health data, including your heart rate and heart rate variability, blood oxygen, sweat and stress levels, behavioral patterns, neurological changes and even brain waves. Smartphones can be used to diagnose, assess and treat Parkinson’s disease. Earbuds could be used to monitor brain health.
This data is not protected under HIPAA, which prohibits health care providers and those working with them from disclosing your health information without your permission, because the law does not consider tech companies to be health care providers nor these wearables to be medical devices.
Legal protections
People have little choice when buying devices, using apps or opening accounts but to agree to lengthy terms that include consent for companies to collect and sell their personal data. This “consent” allows their data to end up in the largely unregulated commercial data market.
The government claims it can lawfully purchase this data from data brokers. But in buying your data in bulk on the commercial market, the government is circumventing the Constitution, Supreme Court decisions and federal laws designed to protect your privacy from unwarranted government overreach.
The Fourth Amendment prohibits unreasonable search and seizure by the government. Supreme Court cases require police to get a warrant to search a phone or use cellular or GPS location information to track someone. The Electronic Communications Privacy Act’s Wiretap Act prohibits unauthorized interception of wire, oral and electronic communications.
Despite some efforts, Congress has failed to enact legislation to protect data privacy, the use of sensitive data by AI systems or to restore the intent of the Electronic Communications Privacy Act. Courts have allowed the broad electronic privacy protections in the federal Wiretap Act to be eviscerated by companies claiming consent.
The way to begin to address these problems is to restore the Wiretap Act and related laws to their intended purposes of protecting Americans’ privacy in communications, and for Congress to follow through on its promises and efforts by passing legislation that secures Americans’ data privacy and protects them from AI harms.
A free and democratic society is only as strong as its citizens’ abilities to make informed decisions, which, in turn, are only as strong as their media and digital literacy skills and the quality of information they consume.
Unbeknownst to much of the public, Big Tech exacts heavy tolls on public health, the environment, and democracy. The detrimental combination of an unregulated tech sector, pronounced rise in cyberattacks and data theft, and widespread digital and media illiteracy—as noted in a Dispatch on Big Data’s surveillance complex—is exacerbated by legacy media’s failure to inform the public of these risks. While establishment news outlets cover major security breaches in Big Tech’s troves of personal identifiable information (PII) and their costs to individuals, businesses, and national security, this coverage fails to address the negative impacts of Big Tech on the full health of our political system, civic engagement, and ecosystems.
Marietje Schaake, an AI Policy fellow at Stanford University’s Institute for Human-Centered AI Policy, argues that Big Tech’s unrestrained hand in all three branches of the government, the military, local and national elections, policing, workplace monitoring, and surveillance capitalism undermine American society in ways the public has failed to grasp. Indeed, little in the corporate press helps the public understand exactly how data centers—the facilities that process and store vast amounts of data—do more than endanger PII. Greenlit by the Trump administration, data centers accelerate ecosystem harms through their unmitigated appropriation of natural resources, including water, and the subsequent greenhouse gas emissions that increase ambient pollution and its attendant diseases.
Adding insult to the public’s right to be informed, corporate news rarely sheds light on how an ethical, independent press serves the public good and functions to balance power in a democracy. A 2023 civics poll by the University of Pennsylvania’s Annenberg School found that only a quarter of respondents knew that press freedom is a constitutional right and a counterbalance to the powers of government and capitalism. The gutting of local news in favor of commercial interests has only accelerated this knowledge blackout.
The demand for AI by corporatists, military AI venture capitalists, and consumers—and resultant demand for data centers—is outpacing utilities infrastructure, traditional power grid capabilities, and the renewable energy sector. Big Tech companies, such as Amazon and Meta, strain municipal water systems and regional power grids, reducing the capacity to operate all things residential and local. In Newton County, Georgia, for example, Meta’s $750 million data center, which sucks up approximately 500,000 gallons of water a day, has contaminated local groundwater and caused taps in nearby homes to run dry. What’s more, the AI boom comes at a time when hot wars are flaring and global temperatures are soaring faster than scientists once predicted.
Constant connectivity, algorithms, and AI-generated content delude individual internet and device users into believing that they’re well informed. However, the decline of civics awareness in the United States—compounded by rampant digital and media illiteracy, ubiquitous state and corporate surveillance, and lax news reporting—makes for an easily manipulated citizenry, asserts attorney and privacy expert, Heidi Boghosian. This is especially disconcerting given the creeping spread of authoritarianism, smackdown on civil liberties, and surging demand for AI everything.
Open [but not transparent] AI
While the companies that develop and deploy popular AI-powered tools lionize the wonders of their products and services, they keep hidden the unsustainable impacts on our world. To borrow from Cory Doctorow, the “enshittification” of the online economy traps consumers, vendors, and advertisers in “the organizing principle of US statecraft,” as well as by more mundane capitalist surveillance. Without government oversight or a Fourth Estate to compel these tech corporations to reveal their shadow side, much of the public is not only in the dark but in harm’s way.
At the most basic level, consumers should know that OpenAI, the company that owns ChatGPT, collects private data and chat inputs, regardless of whether users are logged in or not. Any time users visit or interact with ChatGPT, their log data (the Internet Protocol address, browser type and settings, date and time of the site visit, and interaction with the service), usage data (time zone, country, and type of device used), device details (device name and identifiers, operating system, and browser used), location information from the device’s GPS, and cookies, which store the user’s personal information, are saved. Most users have no idea that they can opt out.
OpenAI claims it saves data only for “fine-tuning,” a process of enhancing the performance and capabilities of AI models, and for human review “to identify biases or harmful outputs.” OpenAI also claims not to use data for marketing and advertising purposes or to sell information to third parties without prior consent. Most users, however, are as oblivious to the means of consent as to the means of opting out. This is by design.
In July, the US Court of Appeals for the Eighth Circuit vacated the Federal Trade Commission’s “click-to-cancel” rule, which would have made online unsubscribing easier. The ruling would have covered all forms of negative option marketing—programs that give sellers free reign to interpret customer inaction as “opting in,” consenting to subscriptions and unwittingly accruing charges. Director of litigation at the Electronic Privacy Information Center, John Davisson, commented that the court’s decision was poorly reasoned, and only those with financial or career advancement motives would argue in favor of subscription traps.
Even if OpenAI is actually protective of the private data it stores, it is not above disclosing user data to affiliates, law enforcement, and the government. Moreover, ChatGPT practices are noncompliant with the EU’s General Data Protection Regulation (GDPR), the global gold standard of data privacy protection. Although OpenAI says it strips PII and anonymizes data, its practice of “indefinite retention” does not comply with the GDPR’s stipulation for data storage limitations, nor does OpenAI sufficiently guarantee irreversible data de-identification.
As science and tech reporter Will Knight wrote for Wired, “Once data is baked into an AI model today, extracting it from that model is a bit like trying to recover the eggs from a finished cake.” Whenever a tech company collects and keeps PII, there are security risks. The more data captured and stored by a company, the more likely it will be exposed to a system bug, hack, or breach, such as the ChatGPT breach in March 2023.
OpenAI has said it will comply with the EU’s AI Code of Practice for General-Purpose AI, which aims to foster transparency, information sharing, and best practices for model and risk assessment among tech companies. Microsoft has said that it will likely sign on to compliance, too; while Meta, on the other hand, flatly refuses to comply, much like it refuses to abide by environmental regulations.
To no one’s surprise, the EU code has already become politicized, and the White House has issued its own AI Action Plan to “remove red tape.” The plan also purports to remove “woke Marxist lunacy in the AI models,” eliminating such topics as diversity, equity, and inclusion and climate change. As Trump crusades against regulation and “bias,” the White House-allied Meta decries political concerns over compliance with the EU’s AI code. Meta’s claim is coincidental; British Courts, based on the United Kingdom’s GDPR obligations, ruled that anyone in a country covered by the GDPR has the right to request Meta to stop using their personal data for targeted advertising.
Big Tech’s open secrets
Information on the tech industry’s environmental and health impacts exists, attests artificial intelligence researcher Sasha Luccioni. The public is simply not being informed. This lack of transparency, warns Luccioni, portends significant environmental and health consequences. Too often, industry opaqueness is excused by insiders as “competition” to which they feel entitled, or blamed on the broad scope of artificial intelligence products and services—smart devices, recommender systems, internet searches, autonomous vehicles, machine learning, the list goes on. Allegedly, there’s too much variety to reasonably quantify consequences.
Those consequences are quantifiable, though. While numbers vary and are on the ascent, there are at least 3,900 data centers in the United States and 10,000 worldwide. An average data center houses complex networking equipment, servers, and systems for cooling systems, lighting, security, and storage, all requiring copious rare earth minerals, water, and electricity to operate.
The densest data center area exists in Northern Virginia, just outside the nation’s capital. “Data Center Alley,” also known as the “Data Center Capital of the World,” has the highest concentration of data centers not only in the United States but in the entire world, consuming millions of gallons of water every day. International hydrologist Newsha Ajami has documented how water shortages around the world are being worsened by Big Data. For tech companies, “water is an afterthought.”
Powered by fossil fuels, these data centers pose serious public health implications. According to research in 2024, training one large language model (LLM) with 213 million parameters produced 626,155 pounds of CO2 emissions, “equivalent to the lifetime emissions of five cars, including fuel.” Stated another way, such AI training “can produce air pollutants equivalent to more than 10,000 round trips by car between Los Angeles and New York City.”
Reasoning models generate more “thinking tokens” and use as much as 50 percent more energy than other AI models. Google and Microsoft search features purportedly use smaller models when possible, which, theoretically, can provide quick responses with less energy. It’s unclear when or if smaller models are actually invoked, and the bottom line, explained climate reporter Molly Taft, is that model providers are not informing consumers that speedier AI response times almost always equate to higher energy usage.
Profits over people
AI is rapidly becoming a public utility, profoundly shaping society, surmise Caltech’s Adam Wierman and Shaolei Ren of the University of California, Riverside. In the last few years, AI has outgrown its niche in the tech sector to become integral to digital economies, government, and security. AI has merged more closely with daily life, replacing human jobs and decision-making, and has thus created a reliance on services currently controlled by private corporations. Because other essential services such as water, electricity, and communications are treated as public utilities, there’s growing discussion about whether AI should be regulated under a similar public utility model.
That said, data centers need power grids, most of which depend on fossil fuel-generated electricity that stresses national and global energy stores. Data centers also need backup generators for brownout and blackout periods. With limited clean, reliable backup options, despite the known environmental and health consequences of burning diesel, diesel generators remain the industry’s go-to.
Whether the public realizes it or not, the environment and citizens are being polluted by the actions of private tech firms. Outputs from data centers inject dangerous fine particulate matter and nitrogen oxides (NOx) into the air, immediately worsening cardiovascular conditions, asthma, cancer, and even cognitive decline, caution Wierman and Ren. Contrary to popular belief, air pollutants are not localized to their emission sources. And, although chemically different, carbon (CO2) is not contained by location either.
Of great concern is that in “World Data Capital Virginia,” data centers are incentivized with tax breaks. Worse still, the (misleadingly named) Environmental Protection Agency plans to remove all limits on greenhouse gas emissions from power plants, according to documents obtained by the New York Times. Thus, treating AI and data centers as public utilities presents a double-edged sword. Can a government that slashes regulations to provide more profit to industry while destroying its citizens’ health along with the natural world be trusted to fairly price and equitably distribute access to all? Would said government suddenly start protecting citizens’ privacy and sensitive data?
The larger question, perhaps, asks if the US is truly a democracy. Or is it a technogarchy, or an AI-tocracy? The 2024 AI Global Surveillance (AIGS) Index ranked the United States first for its deployment of advanced AI surveillance tools that “monitor, track, and surveil citizens to accomplish a range of objectives— some lawful, others that violate human rights, and many of which fall into a murky middle ground,” the Carnegie Endowment for International Peace reported.
Surveillance has long been the purview of authoritarian regimes, but in so-called democracies such as the United States, the scale and intensity of AI use is leveraged both globally through military operations and domestically to target and surveil civilians. In cities such as Scarsdale, New York, and Norfolk, Virginia, citizens are beginning to speak out against the systems that are “immensely popularwith politicians and law enforcement, even though they do real and palpable damage to the citizenry.”
Furthermore, tracking civilians to “deter civil disobedience” has never been easier, evidenced in June by the rapid mobilization of boots on the ground amid the peaceful protests of ICE raids in Los Angeles. AI-powered surveillance acts as the government’s “digital scarecrow,” chilling the American tradition and First Amendment right to protest and the Fourth Estate’s right to report.
The public is only just starting to become aware of algorithmic biases in AI training datasets and their prejudicial impact on predictive policing, or profiling, algorithms, and other analytic tools used by law enforcement. City street light and traffic light cameras, facial recognition systems, video monitoring in and around business and government buildings, as well as smart speakers, smart toys, keyless entry locks, automobile intelligent dash displays, and insurance antitheft tracking systems are all embedded with algorithmic biases.
Checking Big Tech’s unchecked power
Given the level and surreptitiousness of surveillance, the media are doubly tasked with treading carefully to avoid being targeted and accurately informing the public’s perception of data collection and data centers. Reporting that glorifies techbros and AI is unscrupulous and antithetical to democracy: In an era where billionaire techbros and wanna-be-kings are wielding every available apparatus of government and capitalism to gatekeep information, the public needs an ethical press committed to seeking truth, reporting it, and critically covering how AI is shifting power.
If people comprehend what’s at stake—their personal privacy and health, the environment, and democracy itself—they may be more inclined to make different decisions about their AI engagement and media consumption. An independent press that prioritizes public enlightenment means that citizens and consumers still have choices, starting with basic data privacy self-controls that resist AI surveillance and stand up for democratic self-governance.
Just as a healthy environment, replete with clean air and water, has been declared a human right by the United Nations, privacy is enshrined in Article 12 of the Universal Declaration of Human Rights. Although human rights are subject to national laws, water, air, and the internet know no national borders. It is, therefore, incumbent upon communities and the press to uphold these rights and to hold power to account.
This spring, residents of Pittsylvania County, Virginia, did just that. Thanks to independent journalism and civic participation, residents pushed back against the corporate advertising meant to convince the county that the fossil fuels powering the region’s data centers are “clean.” Propagandistic campaigns were similarly applied in Memphis, Tennessee, where proponents of Elon Musk’s data center—which has the footprint of thirteen football fields—circulated fliers to residents of nearby, historically Black neighborhoods, proclaiming the super-polluting xAI has low emissions. “Colossus,” Musk’s name for what’s slated to be the world’s biggest supercomputer, powers xAI’s Hitler-loving chatbot Grok.
The Southern Environmental Law Center exposed with satellite and thermal imagery how xAI, which neglected to obtain legally required air permits, brought in at least 35 portable methane gas turbines to help power Colossus. Tennessee reporter Ren Brabenec said that Memphis has become a sacrifice zone and expects the communities there to push back.
Meanwhile, in Pittsylvania, Virginia, residents succeeded in halting the proposed expansion of data centers that would damage the region’s environment and public health. Elizabeth Putfark, attorney with the Southern Environmental Law Center, affirmed that communities, including local journalists, are a formidable force when acting in solidarity for the public welfare.
Best practices
Because AI surveillance is a threat to democracies everywhere, we must each take measures to counter “government use of AI for social control,” contends Abi Olvera, senior fellow with the Council on Strategic Risks. Harlo Holmes, director of digital security at the Freedom of the Press Foundation, told Wired that consumers must make technology choices under the premise that they’re our “last line of defense.” Steps to building that last line of defense include digital and media literacies and digital hygiene, and at least a cursory understanding of how data is stored and its far-reaching impacts.
Best defensive practices employed by media professionals can also serve as best practices for individuals. This means becoming familiar with laws and regulations, taking every precaution to protect personal information on the internet and during online communications, and engaging in responsible civic discourse. A free and democratic society is only as strong as its citizens’ abilities to make informed decisions, which, in turn, are only as strong as their media and digital literacy skills and the quality of information they consume.
Fighting for digital privacy has never been more important. The Trump administration has empowered big tech surveillance companies like Palantir and Babel Street to aggregate Americans' personal data into massive government databases. This includes the collection and sharing of precise location information that makes it easy for police and federal agencies to track people, including at protests and while peacefully observing ICE agents.
Palantir and Babel Street don't only collect and aggregate huge quantities of public and nonpublic information about ordinary Americans. They also apply machine learning algorithms to look for patterns in the information, pull out so-called "suspicious activity"— like criticism of the Trump administration—and automate profiling and surveillance.
According to recent reporting from 404 Media, Palantir’s ICE app, called ELITE, “populates a map with potential deportation targets, brings up a dossier on each person, and provides a ‘confidence score’ on the person’s current address.” The State Department is already using similar technologies as part of its "catch and revoke" program, targeting U.S. visa holders. Secretary of State Marco Rubio has extended these social media surveillance practices to visa applicants, effectively screening immigrants based on their political expression.
That's bad enough.
But it could very quickly get worse, because what the government does to foreigners is often a prelude to what it intends to do to U.S. citizens.
A weaponized federal government prepares to take on U.S. citizens
Indeed, in September 2025, the Trump administration issued National Security Presidential Memorandum 7, instructing the Department of Justice to investigate civil society organizations, activists, and donors, with a particular focus on the political left and pro-democracy organizations. Palantir’s and Babel Street's databases provide the infrastructure to identify, track, and act against these targets.
The Fourth Amendment and state constitutional protections, like Article 14 of the Massachusetts Declaration of Rights, guarantee individuals the right to be free from warrantless government surveillance and tracking. But these constitutional protections are being eroded right in front of our eyes.
The White House ignores the law. And the administration's reckless disregard for civil liberties is given astonishing reach by AI and machine learning technologies that automate surveillance and profiling, enabling the government to track and categorize people at a scale never before possible.
This automation means the government is no longer limited by the number of people it employs. Effortless and pervasive monitoring tracks people on sidewalks, roadways, and even into our private spheres—including the websites we visit, the ideas we express, and the places we spend and donate our money.
The ACLU and other organizations are filing lawsuits to stop Trump's assaults on our civil liberties at the federal level.
We are also hard at work in the states, to ensure state and local government resources are not being used—intentionally or not—to assist with Trump's assaults on the rule of law and our democratic freedoms.
Massachusetts's slide into a digital surveillance state
Mirroring surveillance expansion at the federal level, AI-powered technology is enabling local and state law enforcement to erode our privacy here in Massachusetts. Nearly every part of policing is becoming automated—from warrantless tracking of all drivers on the roads through automatic license plate readers to social media surveillance.
Some of these tools have valid law enforcement purposes when implemented with proper guardrails. The problem is that there are few, if any, guardrails in place today. Even worse, as our work on Flock license plate readers has shown, when state and local police beef up their surveillance apparatus, Trump's agencies are often the beneficiaries.
Law enforcement agencies often justify expansions of surveillance by suggesting that people have no reasonable expectation of privacy in public. But that’s simply not true.
In Commonwealth v. Augustine, Massachusetts' Supreme Judicial Court was among the first courts to recognize that people retain their right to privacy even in public spaces. The Supreme Court has acknowledged this reality as well. In the landmark case Carpenter v. United States, the Supreme Court warned that privacy rights could be eroded by “ever alert” modern surveillance technologies. Both the Augustine and Carpenter cases established that police cannot track people via their cell phone location for extended periods of time without a warrant.
Yet the automation of policing continues to surge, with apparent disregard for our bedrock constitutional rights.
Surveillance technology companies like Axon, Motorola, Flock Safety, and Genetec are rolling out AI-powered predictive policing and "real-time crime center" tools that greatly increase the potential for abuse.
These technology suites gather data from various surveillance devices and sources into a central database bolstered with AI capabilities, including facial recognition. The result: police can follow your every move — tracking where you live, work, worship, protest, get healthcare, and more.
And they can do this not just to one of us, but to all of us, with the mere click of a button.
In Massachusetts, this shift toward AI-driven surveillance is already underway. Here are some of the tools deployed by state and local law enforcement agencies:
Automatic license plate readers
Police departments across Massachusetts are deploying AI-powered automatic license plate readers (LPRs) that transform routine traffic monitoring into comprehensive location tracking tools.
Companies like Flock Safety and Vigilant Solutions provide law enforcement agencies nationwide with access to vast networks of cameras that capture and store license plate data, creating detailed records of people's movements over time. These technologies don't just track people suspected of serious crimes—they monitor everyone on the roads, building massive databases of where ordinary people go about their daily lives.
Today, unrestricted sharing of license plate reader data through Flock and Vigilant's national databases is facilitating ongoing civil immigration enforcement by federal and state authorities, and even helping cops in Texas investigate a woman for terminating her pregnancy.
When combined with cell-site simulators that can track the location of mobile devices, police gain unprecedented ability to follow individuals without a warrant, even though the Supreme Court raised concerns about this practice in Carpenter.
According to documents obtained by the ACLU of Massachusetts in response to public records requests and other publicly available sources, more than 80 police departments across the state have adopted automatic license plate reader systems. No state laws regulate the use of this location tracking technology.
Surveillance cameras, facial recognition technology, and video analytics software
The proliferation of surveillance cameras across Massachusetts cities and towns has created a foundation for AI-powered monitoring that extends far beyond what was previously possible.
The ACLU of Massachusetts obtained the user guide of one common video analytics software, BriefCam. It reveals extensive reliance on facial recognition technology and machine learning to automatically identify and follow individuals across multiple camera feeds. This technology transforms scattered surveillance cameras into an integrated tracking network that can follow the daily movements of countless surveillance targets with minimal human labor.
Facial recognition technology is far from perfect. It has well-documented misidentification issues — including the recent misidentification (twice!) of a woman who was taken into ICE custody. Even famous athletes have been misidentified. The technology’s high error rates reflect a persistent and insidious racial bias that disproportionately harms people of color.
Yet police departments continue to use it.
The Springfield Police Department is among the Massachusetts law enforcement agencies using BriefCam, despite a local ordinance prohibiting City agencies from using face surveillance. The Boston Police Department also has a contract for BriefCam but says it is not currently using the software.
How you can help rein in the surveillance state
We need immediate action at both the state and local level to ensure that law enforcement can continue to use technology to protect the public from true threats — without creating a digital dragnet that sweeps up the data of millions of people suspected of no crime.
The ACLU of Massachusetts’ top priority this legislative session is data privacy protection.
The Senate has passed a strong data privacy bill. The House is now considering similar legislation. This bill will limit the amount of information companies can collect and process about us, and will completely forbid them from selling especially sensitive data like precise geolocation information.
We know ICE is purchasing cellphone location data and using it to hunt down our friends, family, and neighbors. Massachusetts must prohibit the sale of these sensitive data, to ensure agencies like ICE cannot skirt Fourth Amendment warrant requirements simply by cutting a check to a data broker.
Take action to support comprehensive data privacy legislation today.
We are also supporting other important legislation. With your help, they will gain momentum in the coming months. These include:
H.3755 would prohibit the accumulation and sharing of license plate reader data on millions of people not suspected of any wrongdoing, while still allowing law enforcement to use these tools in legitimate criminal investigations, subject to judicial oversight.
H.1946 and S.1053 would establish critical guardrails on the use of facial recognition technology and advanced video analytics software that threaten our privacy and disproportionately harm communities of color.
In addition, you can encourage your municipality to adopt a Community Control Over Police Surveillance (CCOPS) ordinance, which gives local leaders and residents democratic oversight of surveillance tools such as license place readers and facial recognition before they're deployed. CCOPS has already been enacted in Boston, Cambridge, Lawrence, Medford, Northampton, and Somerville.
If your community doesn't yet have a CCOPS ordinance, now is the time to organize and advocate for one—visit the ACLU of Massachusetts CCOPS resources page to learn more.
Protect privacy without compromising safety
AI can multiply the power of individual surveillance tools exponentially, transforming them from limited investigative resources into an omnipresent digital dragnet that monitors everyone, not just people suspected of serious crimes.
The automated nature of these systems means that traditional limitations on police resources—once a vital check on government overreach—have been effectively eliminated, replaced by AI-powered surveillance that never sleeps, never forgets, and constantly watches our every move.
Also:
How AI can enable public surveillance 
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US government ramps up mass surveillance with help of AI tech, data brokers – and your apps and devices
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Hidden Consequences of the Big Data Surveillance Complex
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The federal government is building Big Brother