Entries Tagged "privacy"

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Like Social Media, AI Requires Difficult Choices

In his 2020 book, “Future Politics,” British barrister Jamie Susskind wrote that the dominant question of the 20th century was “How much of our collective life should be determined by the state, and what should be left to the market and civil society?” But in the early decades of this century, Susskind suggested that we face a different question: “To what extent should our lives be directed and controlled by powerful digital systems—and on what terms?”

Artificial intelligence (AI) forces us to confront this question. It is a technology that in theory amplifies the power of its users: A manager, marketer, political campaigner, or opinionated internet user can utter a single instruction, and see their message—whatever it is—instantly written, personalized, and propagated via email, text, social, or other channels to thousands of people within their organization, or millions around the world. It also allows us to individualize solicitations for political donations, elaborate a grievance into a well-articulated policy position, or tailor a persuasive argument to an identity group, or even a single person.

But even as it offers endless potential, AI is a technology that—like the state—gives others new powers to control our lives and experiences.

We’ve seen this play out before. Social media companies made the same sorts of promises 20 years ago: instant communication enabling individual connection at massive scale. Fast-forward to today, and the technology that was supposed to give individuals power and influence ended up controlling us. Today social media dominates our time and attention, assaults our mental health, and—together with its Big Tech parent companies—captures an unfathomable fraction of our economy, even as it poses risks to our democracy.

The novelty and potential of social media was as present then as it is for AI now, which should make us wary of its potential harmful consequences for society and democracy. We legitimately fear artificial voices and manufactured reality drowning out real people on the internet: on social media, in chat rooms, everywhere we might try to connect with others.

It doesn’t have to be that way. Alongside these evident risks, AI has legitimate potential to transform both everyday life and democratic governance in positive ways. In our new book, “Rewiring Democracy,” we chronicle examples from around the globe of democracies using AI to make regulatory enforcement more efficient, catch tax cheats, speed up judicial processes, synthesize input from constituents to legislatures, and much more. Because democracies distribute power across institutions and individuals, making the right choices about how to shape AI and its uses requires both clarity and alignment across society.

To that end, we spotlight four pivotal choices facing private and public actors. These choices are similar to those we faced during the advent of social media, and in retrospect we can see that we made the wrong decisions back then. Our collective choices in 2025—choices made by tech CEOs, politicians, and citizens alike—may dictate whether AI is applied to positive and pro-democratic, or harmful and civically destructive, ends.

A Choice for the Executive and the Judiciary: Playing by the Rules

The Federal Election Commission (FEC) calls it fraud when a candidate hires an actor to impersonate their opponent. More recently, they had to decide whether doing the same thing with an AI deepfake makes it okay. (They concluded it does not.) Although in this case the FEC made the right decision, this is just one example of how AIs could skirt laws that govern people.

Likewise, courts are having to decide if and when it is okay for an AI to reuse creative materials without compensation or attribution, which might constitute plagiarism or copyright infringement if carried out by a human. (The court outcomes so far are mixed.) Courts are also adjudicating whether corporations are responsible for upholding promises made by AI customer service representatives. (In the case of Air Canada, the answer was yes, and insurers have started covering the liability.)

Social media companies faced many of the same hazards decades ago and have largely been shielded by the combination of Section 230 of the Communications Act of 1994 and the safe harbor offered by the Digital Millennium Copyright Act of 1998. Even in the absence of congressional action to strengthen or add rigor to this law, the Federal Communications Commission (FCC) and the Supreme Court could take action to enhance its effects and to clarify which humans are responsible when technology is used, in effect, to bypass existing law.

A Choice for Congress: Privacy

As AI-enabled products increasingly ask Americans to share yet more of their personal information—their “context“—to use digital services like personal assistants, safeguarding the interests of the American consumer should be a bipartisan cause in Congress.

It has been nearly 10 years since Europe adopted comprehensive data privacy regulation. Today, American companies exert massive efforts to limit data collection, acquire consent for use of data, and hold it confidential under significant financial penalties—but only for their customers and users in the EU.

Regardless, a decade later the U.S. has still failed to make progress on any serious attempts at comprehensive federal privacy legislation written for the 21st century, and there are precious few data privacy protections that apply to narrow slices of the economy and population. This inaction comes in spite of scandal after scandal regarding Big Tech corporations’ irresponsible and harmful use of our personal data: Oracle’s data profiling, Facebook and Cambridge Analytica, Google ignoring data privacy opt-out requests, and many more.

Privacy is just one side of the obligations AI companies should have with respect to our data; the other side is portability—that is, the ability for individuals to choose to migrate and share their data between consumer tools and technology systems. To the extent that knowing our personal context really does enable better and more personalized AI services, it’s critical that consumers have the ability to extract and migrate their personal context between AI solutions. Consumers should own their own data, and with that ownership should come explicit control over who and what platforms it is shared with, as well as withheld from. Regulators could mandate this interoperability. Otherwise, users are locked in and lack freedom of choice between competing AI solutions—much like the time invested to build a following on a social network has locked many users to those platforms.

A Choice for States: Taxing AI Companies

It has become increasingly clear that social media is not a town square in the utopian sense of an open and protected public forum where political ideas are distributed and debated in good faith. If anything, social media has coarsened and degraded our public discourse. Meanwhile, the sole act of Congress designed to substantially reign in the social and political effects of social media platforms—the TikTok ban, which aimed to protect the American public from Chinese influence and data collection, citing it as a national security threat—is one it seems to no longer even acknowledge.

While Congress has waffled, regulation in the U.S. is happening at the state level. Several states have limited children’s and teens’ access to social media. With Congress having rejected—for now—a threatened federal moratorium on state-level regulation of AI, California passed a new slate of AI regulations after mollifying a lobbying onslaught from industry opponents. Perhaps most interesting, Maryland has recently become the first in the nation to levy taxes on digital advertising platform companies.

States now face a choice of whether to apply a similar reparative tax to AI companies to recapture a fraction of the costs they externalize on the public to fund affected public services. State legislators concerned with the potential loss of jobs, cheating in schools, and harm to those with mental health concerns caused by AI have options to combat it. They could extract the funding needed to mitigate these harms to support public services—strengthening job training programs and public employment, public schools, public health services, even public media and technology.

A Choice for All of Us: What Products Do We Use, and How?

A pivotal moment in the social media timeline occurred in 2006, when Facebook opened its service to the public after years of catering to students of select universities. Millions quickly signed up for a free service where the only source of monetization was the extraction of their attention and personal data.

Today, about half of Americans are daily users of AI, mostly via free products from Facebook’s parent company Meta and a handful of other familiar Big Tech giants and venture-backed tech firms such as Google, Microsoft, OpenAI, and Anthropic—with every incentive to follow the same path as the social platforms.

But now, as then, there are alternatives. Some nonprofit initiatives are building open-source AI tools that have transparent foundations and can be run locally and under users’ control, like AllenAI and EleutherAI. Some governments, like Singapore, Indonesia, and Switzerland, are building public alternatives to corporate AI that don’t suffer from the perverse incentives introduced by the profit motive of private entities.

Just as social media users have faced platform choices with a range of value propositions and ideological valences—as diverse as X, Bluesky, and Mastodon—the same will increasingly be true of AI. Those of us who use AI products in our everyday lives as people, workers, and citizens may not have the same power as judges, lawmakers, and state officials. But we can play a small role in influencing the broader AI ecosystem by demonstrating interest in and usage of these alternatives to Big AI. If you’re a regular user of commercial AI apps, consider trying the free-to-use service for Switzerland’s public Apertus model.

None of these choices are really new. They were all present almost 20 years ago, as social media moved from niche to mainstream. They were all policy debates we did not have, choosing instead to view these technologies through rose-colored glasses. Today, though, we can choose a different path and realize a different future. It is critical that we intentionally navigate a path to a positive future for societal use of AI—before the consolidation of power renders it too late to do so.

This post was written with Nathan E. Sanders, and originally appeared in Lawfare.

Posted on December 2, 2025 at 7:03 AM • View Comments

Banning VPNs

This is crazy. Lawmakers in several US states are contemplating banning VPNs, because…think of the children!

As of this writing, Wisconsin lawmakers are escalating their war on privacy by targeting VPNs in the name of “protecting children” in A.B. 105/S.B. 130. It’s an age verification bill that requires all websites distributing material that could conceivably be deemed “sexual content” to both implement an age verification system and also to block the access of users connected via VPN. The bill seeks to broadly expand the definition of materials that are “harmful to minors” beyond the type of speech that states can prohibit minors from accessing­ potentially encompassing things like depictions and discussions of human anatomy, sexuality, and reproduction.

The EFF link explains why this is a terrible idea.

Posted on December 1, 2025 at 7:59 AM • View Comments

First Wap: A Surveillance Computer You’ve Never Heard Of

Mother Jones has a long article on surveillance arms manufacturers, their wares, and how they avoid export control laws:

Operating from their base in Jakarta, where permissive export laws have allowed their surveillance business to flourish, First Wap’s European founders and executives have quietly built a phone-tracking empire, with a footprint extending from the Vatican to the Middle East to Silicon Valley.

It calls its proprietary system Altamides, which it describes in promotional materials as “a unified platform to covertly locate the whereabouts of single or multiple suspects in real-time, to detect movement patterns, and to detect whether suspects are in close vicinity with each other.”

Altamides leaves no trace on the phones it targets, unlike spyware such as Pegasus. Nor does it require a target to click on a malicious link or show any of the telltale signs (such as overheating or a short battery life) of remote monitoring.

Its secret is shrewd use of the antiquated telecom language Signaling System No. 7, known as SS7, that phone carriers use to route calls and text messages. Any entity with SS7 access can send queries requesting information about which cell tower a phone subscriber is nearest to, an essential first step to sending a text message or making a call to that subscriber. But First Wap’s technology uses SS7 to zero in on phone numbers and trace the location of their users.

Much more in this Lighthouse Reports analysis.

Posted on October 27, 2025 at 7:08 AM • View Comments

The Trump Administration’s Increased Use of Social Media Surveillance

This chilling paragraph is in a comprehensive Brookings report about the use of tech to deport people from the US:

The administration has also adapted its methods of social media surveillance. Though agencies like the State Department have gathered millions of handles and monitored political discussions online, the Trump administration has been more explicit in who it’s targeting. Secretary of State Marco Rubio announced a new, zero-tolerance “Catch and Revoke” strategy, which uses AI to monitor the public speech of foreign nationals and revoke visas of those who “abuse [the country’s] hospitality.” In a March press conference, Rubio remarked that at least 300 visas, primarily student and visitor visas, had been revoked on the grounds that visitors are engaging in activity contrary to national interest. A State Department cable also announced a new requirement for student visa applicants to set their social media accounts to public—reflecting stricter vetting practices aimed at identifying individuals who “bear hostile attitudes toward our citizens, culture, government, institutions, or founding principles,” among other criteria.

Posted on October 14, 2025 at 7:09 AM • View Comments

Flok License Plate Surveillance

The company Flok is surveilling us as we drive:

A retired veteran named Lee Schmidt wanted to know how often Norfolk, Virginia’s 176 Flock Safety automated license-plate-reader cameras were tracking him. The answer, according to a U.S. District Court lawsuit filed in September, was more than four times a day, or 526 times from mid-February to early July. No, there’s no warrant out for Schmidt’s arrest, nor is there a warrant for Schmidt’s co-plaintiff, Crystal Arrington, whom the system tagged 849 times in roughly the same period.

You might think this sounds like it violates the Fourth Amendment, which protects American citizens from unreasonable searches and seizures without probable cause. Well, so does the American Civil Liberties Union. Norfolk, Virginia Judge Jamilah LeCruise also agrees, and in 2024 she ruled that plate-reader data obtained without a search warrant couldn’t be used against a defendant in a robbery case.

Posted on October 8, 2025 at 12:10 PM • View Comments

Digital Threat Modeling Under Authoritarianism

Today’s world requires us to make complex and nuanced decisions about our digital security. Evaluating when to use a secure messaging app like Signal or WhatsApp, which passwords to store on your smartphone, or what to share on social media requires us to assess risks and make judgments accordingly. Arriving at any conclusion is an exercise in threat modeling.

In security, threat modeling is the process of determining what security measures make sense in your particular situation. It’s a way to think about potential risks, possible defenses, and the costs of both. It’s how experts avoid being distracted by irrelevant risks or overburdened by undue costs.

We threat model all the time. We might decide to walk down one street instead of another, or use an internet VPN when browsing dubious sites. Perhaps we understand the risks in detail, but more likely we are relying on intuition or some trusted authority. But in the U.S. and elsewhere, the average person’s threat model is changing—specifically involving how we protect our personal information. Previously, most concern centered on corporate surveillance; companies like Google and Facebook engaging in digital surveillance to maximize their profit. Increasingly, however, many people are worried about government surveillance and how the government could weaponize personal data.

Since the beginning of this year, the Trump administration’s actions in this area have raised alarm bells: The Department of Government Efficiency (DOGE) took data from federal agencies, Palantir combined disparate streams of government data into a single system, and Immigration and Customs Enforcement (ICE) used social media posts as a reason to deny someone entry into the U.S.

These threats, and others posed by a techno-authoritarian regime, are vastly different from those presented by a corporate monopolistic regime—and different yet again in a society where both are working together. Contending with these new threats requires a different approach to personal digital devices, cloud services, social media, and data in general.

What Data Does the Government Already Have?

For years, most public attention has centered on the risks of tech companies gathering behavioral data. This is an enormous amount of data, generally used to predict and influence consumers’ future behavior—rather than as a means of uncovering our past. Although commercial data is highly intimate—such as knowledge of your precise location over the course of a year, or the contents of every Facebook post you have ever created—it’s not the same thing as tax returns, police records, unemployment insurance applications, or medical history.

The U.S. government holds extensive data about everyone living inside its borders, some of it very sensitive—and there’s not much that can be done about it. This information consists largely of facts that people are legally obligated to tell the government. The IRS has a lot of very sensitive data about personal finances. The Treasury Department has data about any money received from the government. The Office of Personnel Management has an enormous amount of detailed information about government employees—including the very personal form required to get a security clearance. The Census Bureau possesses vast data about everyone living in the U.S., including, for example, a database of real estate ownership in the country. The Department of Defense and the Bureau of Veterans Affairs have data about present and former members of the military, the Department of Homeland Security has travel information, and various agencies possess health records. And so on.

It is safe to assume that the government has—or will soon have—access to all of this government data. This sounds like a tautology, but in the past, the U.S. government largely followed the many laws limiting how those databases were used, especially regarding how they were shared, combined, and correlated. Under the second Trump administration, this no longer seems to be the case.

Augmenting Government Data with Corporate Data

The mechanisms of corporate surveillance haven’t gone away. Compute technology is constantly spying on its users—and that data is being used to influence us. Companies like Google and Meta are vast surveillance machines, and they use that data to fuel advertising. A smartphone is a portable surveillance device, constantly recording things like location and communication. Cars, and many other Internet of Things devices, do the same. Credit card companies, health insurers, internet retailers, and social media sites all have detailed data about you—and there is a vast industry that buys and sells this intimate data.

This isn’t news. What’s different in a techno-authoritarian regime is that this data is also shared with the government, either as a paid service or as demanded by local law. Amazon shares Ring doorbell data with the police. Flock, a company that collects license plate data from cars around the country, shares data with the police as well. And just as Chinese corporations share user data with the government and companies like Verizon shared calling records with the National Security Agency (NSA) after the Sept. 11 terrorist attacks, an authoritarian government will use this data as well.

Personal Targeting Using Data

The government has vast capabilities for targeted surveillance, both technically and legally. If a high-level figure is targeted by name, it is almost certain that the government can access their data. The government will use its investigatory powers to the fullest: It will go through government data, remotely hack phones and computers, spy on communications, and raid a home. It will compel third parties, like banks, cell providers, email providers, cloud storage services, and social media companies, to turn over data. To the extent those companies keep backups, the government will even be able to obtain deleted data.

This data can be used for prosecution—possibly selectively. This has been made evident in recent weeks, as the Trump administration personally targeted perceived enemies for “mortgage fraud.” This was a clear example of weaponization of data. Given all the data the government requires people to divulge, there will be something there to prosecute.

Although alarming, this sort of targeted attack doesn’t scale. As vast as the government’s information is and as powerful as its capabilities are, they are not infinite. They can be deployed against only a limited number of people. And most people will never be that high on the priorities list.

The Risks of Mass Surveillance

Mass surveillance is surveillance without specific targets. For most people, this is where the primary risks lie. Even if we’re not targeted by name, personal data could raise red flags, drawing unwanted scrutiny.

The risks here are twofold. First, mass surveillance could be used to single out people to harass or arrest: when they cross the border, show up at immigration hearings, attend a protest, are stopped by the police for speeding, or just as they’re living their normal lives. Second, mass surveillance could be used to threaten or blackmail. In the first case, the government is using that database to find a plausible excuse for its actions. In the second, it is looking for an actual infraction that it could selectively prosecute—or not.

Mitigating these risks is difficult, because it would require not interacting with either the government or corporations in everyday life—and living in the woods without any electronics isn’t realistic for most of us. Additionally, this strategy protects only future information; it does nothing to protect the information generated in the past. That said, going back and scrubbing social media accounts and cloud storage does have some value. Whether it’s right for you depends on your personal situation.

Opportunistic Use of Data

Beyond data given to third parties—either corporations or the government—there is also data users keep in their possession.This data may be stored on personal devices such as computers and phones or, more likely today, in some cloud service and accessible from those devices. Here, the risks are different: Some authority could confiscate your device and look through it.

This is not just speculative. There are many stories of ICE agents examining people’s phones and computers when they attempt to enter the U.S.: their emails, contact lists, documents, photos, browser history, and social media posts.

There are several different defenses you can deploy, presented from least to most extreme. First, you can scrub devices of potentially incriminating information, either as a matter of course or before entering a higher-risk situation. Second, you could consider deleting—even temporarily—social media and other apps so that someone with access to a device doesn’t get access to those accounts—this includes your contacts list. If a phone is swept up in a government raid, your contacts become their next targets.

Third, you could choose not to carry your device with you at all, opting instead for a burner phone without contacts, email access, and accounts, or go electronics-free entirely. This may sound extreme—and getting it right is hard—but I know many people today who have stripped-down computers and sanitized phones for international travel. At the same time, there are also stories of people being denied entry to the U.S. because they are carrying what is obviously a burner phone—or no phone at all.

Encryption Isn’t a Magic Bullet—But Use It Anyway

Encryption protects your data while it’s not being used, and your devices when they’re turned off. This doesn’t help if a border agent forces you to turn on your phone and computer. And it doesn’t protect metadata, which needs to be unencrypted for the system to function. This metadata can be extremely valuable. For example, Signal, WhatsApp, and iMessage all encrypt the contents of your text messages—the data—but information about who you are texting and when must remain unencrypted.

Also, if the NSA wants access to someone’s phone, it can get it. Encryption is no help against that sort of sophisticated targeted attack. But, again, most of us aren’t that important and even the NSA can target only so many people. What encryption safeguards against is mass surveillance.

I recommend Signal for text messages above all other apps. But if you are in a country where having Signal on a device is in itself incriminating, then use WhatsApp. Signal is better, but everyone has WhatsApp installed on their phones, so it doesn’t raise the same suspicion. Also, it’s a no-brainer to turn on your computer’s built-in encryption: BitLocker for Windows and FileVault for Macs.

On the subject of data and metadata, it’s worth noting that data poisoning doesn’t help nearly as much as you might think. That is, it doesn’t do much good to add hundreds of random strangers to an address book or bogus internet searches to a browser history to hide the real ones. Modern analysis tools can see through all of that.

Shifting Risks of Decentralization

This notion of individual targeting, and the inability of the government to do that at scale, starts to fail as the authoritarian system becomes more decentralized. After all, if repression comes from the top, it affects only senior government officials and people who people in power personally dislike. If it comes from the bottom, it affects everybody. But decentralization looks much like the events playing out with ICE harassing, detaining, and disappearing people—everyone has to fear it.

This can go much further. Imagine there is a government official assigned to your neighborhood, or your block, or your apartment building. It’s worth that person’s time to scrutinize everybody’s social media posts, email, and chat logs. For anyone in that situation, limiting what you do online is the only defense.

Being Innocent Won’t Protect You

This is vital to understand. Surveillance systems and sorting algorithms make mistakes. This is apparent in the fact that we are routinely served advertisements for products that don’t interest us at all. Those mistakes are relatively harmless—who cares about a poorly targeted ad?—but a similar mistake at an immigration hearing can get someone deported.

An authoritarian government doesn’t care. Mistakes are a feature and not a bug of authoritarian surveillance. If ICE targets only people it can go after legally, then everyone knows whether or not they need to fear ICE. If ICE occasionally makes mistakes by arresting Americans and deporting innocents, then everyone has to fear it. This is by design.

Effective Opposition Requires Being Online

For most people, phones are an essential part of daily life. If you leave yours at home when you attend a protest, you won’t be able to film police violence. Or coordinate with your friends and figure out where to meet. Or use a navigation app to get to the protest in the first place.

Threat modeling is all about trade-offs. Understanding yours depends not only on the technology and its capabilities but also on your personal goals. Are you trying to keep your head down and survive—or get out? Are you wanting to protest legally? Are you doing more, maybe throwing sand into the gears of an authoritarian government, or even engaging in active resistance? The more you are doing, the more technology you need—and the more technology will be used against you. There are no simple answers, only choices.

This essay was originally published in Lawfare.

Posted on September 26, 2025 at 7:04 AM • View Comments

Details About Chinese Surveillance and Propaganda Companies

Details from leaked documents:

While people often look at China’s Great Firewall as a single, all-powerful government system unique to China, the actual process of developing and maintaining it works the same way as surveillance technology in the West. Geedge collaborates with academic institutions on research and development, adapts its business strategy to fit different clients’ needs, and even repurposes leftover infrastructure from its competitors.

[…]

The parallels with the West are hard to miss. A number of American surveillance and propaganda firms also started as academic projects before they were spun out into startups and grew by chasing government contracts. The difference is that in China, these companies operate with far less transparency. Their work comes to light only when a trove of documents slips onto the internet.

[…]

It is tempting to think of the Great Firewall or Chinese propaganda as the outcome of a top-down master plan that only the Chinese Communist Party could pull off. But these leaks suggest a more complicated reality. Censorship and propaganda efforts must be marketed, financed, and maintained. They are shaped by the logic of corporate quarterly financial targets and competitive bids as much as by ideology­—except the customers are governments, and the products can control or shape entire societies.

More information about one of the two leaks.

Posted on September 22, 2025 at 7:03 AM • View Comments

How the Solid Protocol Restores Digital Agency

The current state of digital identity is a mess. Your personal information is scattered across hundreds of locations: social media companies, IoT companies, government agencies, websites you have accounts on, and data brokers you’ve never heard of. These entities collect, store, and trade your data, often without your knowledge or consent. It’s both redundant and inconsistent. You have hundreds, maybe thousands, of fragmented digital profiles that often contain contradictory or logically impossible information. Each serves its own purpose, yet there is no central override and control to serve you—as the identity owner.

We’re used to the massive security failures resulting from all of this data under the control of so many different entities. Years of privacy breaches have resulted in a multitude of laws—in US states, in the EU, elsewhere—and calls for even more stringent protections. But while these laws attempt to protect data confidentiality, there is nothing to protect data integrity.

In this context, data integrity refers to its accuracy, consistency, and reliability…throughout its lifecycle. It means ensuring that data is not only accurately recorded but also remains logically consistent across systems, is up-to-date, and can be verified as authentic. When data lacks integrity, it can contain contradictions, errors, or outdated information—problems that can have serious real-world consequences.

Without data integrity, someone could classify you as a teenager while simultaneously attributing to you three teenage children: a biological impossibility. What’s worse, you have no visibility into the data profiles assigned to your identity, no mechanism to correct errors, and no authoritative way to update your information across all platforms where it resides.

Integrity breaches don’t get the same attention that confidentiality breaches do, but the picture isn’t pretty. A 2017 write-up in The Atlantic found error rates exceeding 50% in some categories of personal information. A 2019 audit of data brokers found at least 40% of data broker sourced user attributes are “not at all” accurate. In 2022, the Consumer Financial Protection Bureau documented thousands of cases where consumers were denied housing, employment, or financial services based on logically impossible data combinations in their profiles. Similarly, the National Consumer Law Center report called “Digital Denials” showed inaccuracies in tenant screening data that blocked people from housing.

And integrity breaches can have significant effects on our lives. In one 2024 British case, two companies blamed each other for the faulty debt information that caused catastrophic financial consequences for an innocent victim. Breonna Taylor was killed in 2020 during a police raid on her apartment in Louisville, Kentucky, when officers executed a “no-knock” warrant on the wrong house based on bad data. They had faulty intelligence connecting her address to a suspect who actually lived elsewhere.

In some instances, we have rights to view our data, and in others, rights to correct it, but these sorts of solutions have only limited value. When journalist Julia Angwin attempted to correct her information across major data brokers for her book Dragnet Nation, she found that even after submitting corrections through official channels, a significant number of errors reappeared within six months.

In some instances, we have the right to delete our data, but—again—this only has limited value. Some data processing is legally required, and some is necessary for services we truly want and need.

Our focus needs to shift from the binary choice of either concealing our data entirely or surrendering all control over it. Instead, we need solutions that prioritize integrity in ways that balance privacy with the benefits of data sharing.

It’s not as if we haven’t made progress in better ways to manage online identity. Over the years, numerous trustworthy systems have been developed that could solve many of these problems. For example, imagine digital verification that works like a locked mobile phone—it works when you’re the one who can unlock and use it, but not if someone else grabs it from you. Or consider a storage device that holds all your credentials, like your driver’s license, professional certifications, and healthcare information, and lets you selectively share one without giving away everything at once. Imagine being able to share just a single cell in a table or a specific field in a file. These technologies already exist, and they could let you securely prove specific facts about yourself without surrendering control of your whole identity. This isn’t just theoretically better than traditional usernames and passwords; the technologies represent a fundamental shift in how we think about digital trust and verification.

Standards to do all these things emerged during the Web 2.0 era. We mostly haven’t used them because platform companies have been more interested in building barriers around user data and identity. They’ve used control of user identity as a key to market dominance and monetization. They’ve treated data as a corporate asset, and resisted open standards that would democratize data ownership and access. Closed, proprietary systems have better served their purposes.

There is another way. The Solid protocol, invented by Sir Tim Berners-Lee, represents a radical reimagining of how data operates online. Solid stands for “SOcial LInked Data.” At its core, it decouples data from applications by storing personal information in user-controlled “data wallets”: secure, personal data stores that users can host anywhere they choose. Applications can access specific data within these wallets, but users maintain ownership and control.

Solid is more than distributed data storage. This architecture inverts the current data ownership model. Instead of companies owning user data, users maintain a single source of truth for their personal information. It integrates and extends all those established identity standards and technologies mentioned earlier, and forms a comprehensive stack that places personal identity at the architectural center.

This identity-first paradigm means that every digital interaction begins with the authenticated individual who maintains control over their data. Applications become interchangeable views into user-owned data, rather than data silos themselves. This enables unprecedented interoperability, as services can securely access precisely the information they need while respecting user-defined boundaries.

Solid ensures that user intentions are transparently expressed and reliably enforced across the entire ecosystem. Instead of each application implementing its own custom authorization logic and access controls, Solid establishes a standardized declarative approach where permissions are explicitly defined through control lists or policies attached to resources. Users can specify who has access to what data with granular precision, using simple statements like “Alice can read this document” or “Bob can write to this folder.” These permission rules remain consistent, regardless of which application is accessing the data, eliminating the fragmentation and unpredictability of traditional authorization systems.

This architectural shift decouples applications from data infrastructure. Unlike Web 2.0 platforms like Facebook, which require massive back-end systems to store, process, and monetize user data, Solid applications can be lightweight and focused solely on functionality. Developers no longer need to build and maintain extensive data storage systems, surveillance infrastructure, or analytics pipelines. Instead, they can build specialized tools that request access to specific data in users’ wallets, with the heavy lifting of data storage and access control handled by the protocol itself.

Let’s take healthcare as an example. The current system forces patients to spread pieces of their medical history across countless proprietary databases controlled by insurance companies, hospital networks, and electronic health record vendors. Patients frustratingly become a patchwork rather than a person, because they often can’t access their own complete medical history, let alone correct mistakes. Meanwhile, those third-party databases suffer regular breaches. The Solid protocol enables a fundamentally different approach. Patients maintain their own comprehensive medical record, with data cryptographically signed by trusted providers, in their own data wallet. When visiting a new healthcare provider, patients can arrive with their complete, verifiable medical history rather than starting from zero or waiting for bureaucratic record transfers.

When a patient needs to see a specialist, they can grant temporary, specific access to relevant portions of their medical history. For example, a patient referred to a cardiologist could share only cardiac-related records and essential background information. Or, on the flip side, the patient can share new and rich sources of related data to the specialist, like health and nutrition data. The specialist, in turn, can add their findings and treatment recommendations directly to the patient’s wallet, with a cryptographic signature verifying medical credentials. This process eliminates dangerous information gaps while ensuring that patients maintain an appropriate role in who sees what about them and why.

When a patient—doctor relationship ends, the patient retains all records generated during that relationship—unlike today’s system where changing providers often means losing access to one’s historical records. The departing doctor’s signed contributions remain verifiable parts of the medical history, but they no longer have direct access to the patient’s wallet without explicit permission.

For insurance claims, patients can provide temporary, auditable access to specific information needed for processing—no more and no less. Insurance companies receive verified data directly relevant to claims but should not be expected to have uncontrolled hidden comprehensive profiles or retain information longer than safe under privacy regulations. This approach dramatically reduces unauthorized data use, risk of breaches (privacy and integrity), and administrative costs.

Perhaps most transformatively, this architecture enables patients to selectively participate in medical research while maintaining privacy. They could contribute anonymized or personalized data to studies matching their interests or conditions, with granular control over what information is shared and for how long. Researchers could gain access to larger, more diverse datasets while participants would maintain control over their information—creating a proper ethical model for advancing medical knowledge.

The implications extend far beyond healthcare. In financial services, customers could maintain verified transaction histories and creditworthiness credentials independently of credit bureaus. In education, students could collect verified credentials and portfolios that they truly own rather than relying on institutions’ siloed records. In employment, workers could maintain portable professional histories with verified credentials from past employers. In each case, Solid enables individuals to be the masters of their own data while allowing verification and selective sharing.

The economics of Web 2.0 pushed us toward centralized platforms and surveillance capitalism, but there has always been a better way. Solid brings different pieces together into a cohesive whole that enables the identity-first architecture we should have had all along. The protocol doesn’t just solve technical problems; it corrects the fundamental misalignment of incentives that has made the modern web increasingly hostile to both users and developers.

As we look to a future of increased digitization across all sectors of society, the need for this architectural shift becomes even more apparent. Individuals should be able to maintain and present their own verified digital identity and history, rather than being at the mercy of siloed institutional databases. The Solid protocol makes this future technically possible.

This essay was written with Davi Ottenheimer, and originally appeared on The Inrupt Blog.

Posted on July 24, 2025 at 7:04 AM • View Comments

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Sidebar photo of Bruce Schneier by Joe MacInnis.