Data for Sale

We are trading something more personal than cash, and most of us have never been asked. This is not a deal signed between governments. It is a quiet exchange in which ordinary digital life becomes the currency of a market nobody remembers joining.

The trade needs no ships, no customs and no tariffs, yet it supports some of the largest companies on earth. Oil, gold and electronics still move the world economy. A growing share of the power now sits with whoever can track behaviour, predict choices and nudge what people do next.

Your habits, your location, your messages and even your voice are collected, analysed and sold. The results feed machine-learning systems that shape the ads you see, sometimes the prices you are offered, and sometimes the news that reaches you. The system treats you less as a customer and more as stock to be sold to the highest bidder. Here is what one sale looks like.

Bid request simplified from the industry's OpenRTB standard.2 Bidder names and prices are illustrative.

The scale is hard to hold in your head. In 2022 the Irish Council for Civil Liberties estimated that these auctions broadcast information about the average American 747 times a day, and about the average European 376 times a day, about 178 trillion broadcasts a year across both regions.1

If you live in the United States, your data goes out about 747 times a day. That is 272,655 broadcasts a year, or one every 116 seconds of your life, asleep or awake.

Tech companies have mastered this. The more you use your phone, your smart speaker or your car, the more value you produce for them, usually without noticing. And ads are only the visible part. The same machinery decides what you are shown, what you come to believe and what you buy. The unsettling thing is how normal it now feels.

Your data is not floating around by accident. It is hunted, harvested and sold. Every scroll, search and selfie feeds an economy in which your private life turns into someone else's profit. This paper sets out how that economy works and why it matters more than it seems.

The aim is simple: to show how everyday users are turned into products, to name the systems that profit, and to argue for a digital future built on consent, control and transparency. People deserve to know what they are signing up for.

The paper is organised around four questions. Tap one for the short answer, then follow the link to the evidence.

The method has three parts. First, expose the hidden trackers and markets, using regulators' findings, court cases and published research. Second, explain how auctions, brokers and recommendation systems actually work, with figures you can take apart. Third, set out what a fairer deal between people, platforms and governments could look like. Wherever a number appears, it comes from a cited source. Where a figure uses made-up values to show how something works, it says so.

The early internet promised a kind of utopia: endless information, free expression and open access. Somewhere along the way the platforms we trusted to connect us began to earn money not from what we paid, but from what we did. Every click, scroll, search and pause became a data point, a behavioural breadcrumb, and companies learned to follow the trail.

The Harvard scholar Shoshana Zuboff gave the system a name, surveillance capitalism.3 Industrial capitalism turned raw materials into products. This version turns human experience itself into raw material. Emotions, preferences, relationships, even moments of hesitation are tracked, analysed and turned into money.

What gets sold in the end is prediction. With enough data, companies can model what someone is likely to do next with uncomfortable accuracy, and sell that forecast to advertisers, political campaigns and other brokers who want to influence the decision before it is made. It is not only your data on the market. It is your future.

Single facts rarely give much away. Combinations do. Switch on the sources below and watch what can be worked out when they are joined together.

The best-known example comes from shopping. In 2012 the New York Times Magazine reported that the US retailer Target had built a “pregnancy prediction” score from about 25 ordinary products, so it could reach expectant parents before rival stores did.5 Unscented lotion, certain supplements and extra-large bags of cotton wool say nothing on their own. In the same basket, they said a great deal.

Most of this happens without people knowing. Privacy policies are long and vague by design. Consent is rarely informed. People think they are swapping a little data for a free service. What they are really giving up is a measure of control over their own lives.

This is not a fringe issue. Google, Meta, Amazon and TikTok built their empires less on content than on predicting behaviour. The more time we spend online, the more is extracted, and the sharper the predictions become.

Free has never been cheaper, or more expensive. We have been trained to expect email, maps and entertainment at no cost. But we are paying, just not in money. We pay with attention, with behaviour and with trust.

The money behind that trade grows every year. Meta, which owns Facebook, Instagram and WhatsApp, made $5 billion in 2012. Before you look at the rest, try to draw how you think the line goes.

Spread across its users, Meta earned an average of $49.63 per person in 2024.8 The average internet user spends about two hours and 21 minutes a day on social media,9 and that time is exactly what is being sold. This page carries no ads, but it can still show you what your reading would be worth on one that did.

The business model needs more than data. It needs behaviour to change. Algorithms are trained to keep you scrolling, clicking and reacting. What started as passive watching has become active steering. Recommendations become nudges, nudges become habits, and habits become profit, though not yours.

The model also feeds on outrage. Strong emotions drive engagement, and engagement produces more data, so the loop rewards whatever makes people angriest. It shapes not only what we see but how we think. The activist Eli Pariser called the result the filter bubble:10 echo chambers, and a slow loss of shared reality.

If data is the fuel of the digital economy, then our consent, awareness and rights have to be its brakes.

The consequences are concrete: election manipulation and misinformation, mental-health strain, people exploited as consumers. We handed over our digital selves for convenience, and in doing so let private companies design much of what we experience online, and with it, much of how we see the world.

Every notification sound, every well-timed ad and every endless scroll is built around human psychology. Attention is treated as a scarce resource, because it is one, and once a platform has captured it, it holds on.

Personalised feeds, streaks and surprise rewards work the way a casino does. Instead of coins, the payout is a burst of novelty or approval. The price is time and peace of mind. Pull down on the phone below and feel it for yourself.

Compulsion is only part of the cost. Feeds that run on behavioural data also feed anxiety, fear of missing out and impossible standards of beauty and success. Every like becomes a point on a scoreboard nobody can see, and people start judging themselves by it. We are no longer just consumers. We are characters in a game, scored and sorted by systems we never meet.

Then there is what happens to people who know they are being watched. They behave differently. Researchers call it the chilling effect. When you assume every search is recorded, you take fewer risks, question less and keep unpopular opinions to yourself, even good ones. After the 2013 revelations about mass surveillance, the legal scholar Jonathon Penney found a sudden, lasting fall in visits to Wikipedia pages that people feared might draw attention.13 Freedom of thought rarely disappears in one go. It narrows, quietly, until conformity feels safer than curiosity.

Behind every search, swipe and tap sits a marketplace where your data is the currency. Companies refine what they collect, package it and sell it to advertisers, governments and data brokers, firms most people have never heard of, which buy, merge and resell profiles of millions of people.14

The strangest thing about this market is how quiet it is. You never see a transaction and never sign a contract, yet location pings, purchases and app use can be sold in real time. Location data is the most revealing of all. Drag the clock below through one ordinary day.

That is not a hypothetical worry. In 2022 the US Federal Trade Commission sued Kochava for selling precise location data that could reveal visits to reproductive-health clinics, places of worship and shelters.15 In January 2024 it issued its first order banning a broker, X-Mode Social, from selling sensitive location data.16 Researchers at the Brennan Center have shown how government agencies can simply buy such data instead of asking a judge for a warrant, a gap they call the data broker loophole.17

Advertising is only the start. The same data now feeds credit scores, loan decisions, insurance prices, job screening and political campaigns. Follow it from the apps that collect it to the people who pay for it.

Systems trained on biased or incomplete data can quietly reinforce discrimination and shut people out of opportunities, and the people affected rarely find out why. The deepest cost is trust. As people learn how their data is used, they grow wary of the very platforms they depend on, and it is hard to blame them. When profit depends on surveillance, transparency becomes a threat. This is not just a hidden economy. It is a rigged one.

Every scroll, swipe and tap does more than feed an algorithm. It trains one. A late-night scroll or a quick search for the nearest coffee shop teaches a system what you like, what you fear, when you are most impulsive and what makes you stop. That knowledge is then used to steer what you do next.

The systems that run our feeds, suggest our purchases and filter our news are not neutral. They are tuned to keep people engaged, buying and believing, and the simplest way to do that is to show people more of what they already click on. Here is that logic in miniature.

Beyond what we buy and read, data-driven systems now help decide who is hired, who gets a loan and who is flagged by security checks. Decisions people used to make are partly handed to software that may lack context, empathy or fairness. The bigger danger is opacity. People are rarely told why they were turned down, or which detail tipped the scales.

Signals you would never think about can matter. Studying a German online retailer, Tobias Berg and colleagues found that small details of a customer's “digital footprint”, such as the type of phone, the email provider and the time of day they ordered, predicted whether they would repay as well as a traditional credit score.18 That can help people with no credit history. It also means harmless habits can stand in for income, age or background.

Most of this happens out of sight. No notification, no consent screen, just a slow reshaping of what you are offered by systems you cannot see or question. Data is no longer a record of the past. It is working infrastructure, and the more it learns, the more persuasive it gets.

That gap is not bad luck. It is design. In the attention economy your time is the product, and every extra second is revenue for someone. Infinite scroll, autoplay, streaks and well-timed notifications are all deliberate, and all of them are free.

Aza Raskin, the designer credited with inventing infinite scroll in 2006, later said he regretted how it was used, comparing such features to “behavioural cocaine”.19 Try the experiment below. There is no clock on the screen, on purpose.

The loop feeds itself. More time online produces more data, more data makes the hooks more effective, and every click teaches the system how to pull you back. The goal is not to serve you but to keep you. That is why recommendation engines push extreme content, which gets more reaction, and why ignoring a notification feels uncomfortable. The friction is designed.

Many people know they are being manipulated and still cannot stop, because the system is optimised for compulsion rather than consent. In the attention economy, free means paying with your focus, your habits and your peace of mind.

So what now? Deleting everything and moving to the woods is tempting, but not practical. The better question is how to rebuild trust in a system that profits from our not knowing.

First, transparency by design. No more cookie banners hiding behind legal language. Platforms should show plainly what they collect, where it goes and why, as part of the product rather than in the fine print. Imagine a dashboard that showed, in real time, who was looking at your data. The first step is often the banner itself. Try to refuse tracking on both of these.

Second, regulation has to keep up. Many data laws were written before today's platforms existed. Governments need stronger protections, real enforcement and real rights for users, something like Europe's General Data Protection Regulation, but global and ready for AI.22 The direction is clear. By 2024, 71% of the world's countries had data protection laws, according to UN Trade and Development.23 Ireland's regulator fined Meta a record €1.2 billion in 2023.24 In the United States, where state laws keep multiplying,25 the FTC fined Facebook $5 billion in 2019 after the Cambridge Analytica scandal exposed the data of up to 87 million people.26 India passed its Digital Personal Data Protection Act in 2023 and published draft rules for it in January 2025.27

Laws that rely on people reading privacy policies have a basic problem. A typical policy at a popular website ran to about 2,500 words, around ten minutes of reading, and Aleecia McDonald and Lorrie Faith Cranor put the cost of Americans actually reading them all at around $781 billion a year.28 Work out your own share.

If you accept the terms of 200 websites and apps a year, and each policy runs to 2,500 words, then at 250 words a minute you would spend 33 hours reading them. That is 4.2 working days a year, or 0.9 copies of War and Peace.

Third, ethical design. Products should not be built to exploit weaknesses in human psychology. They should serve people, not trap them. Screen-time warnings, prompts towards more varied content and a little friction before oversharing can restore some balance.

Finally, a change in culture. Privacy is not about hiding. It is about agency. When users care how their data is used, platforms will have to care too. Rebuilding trust is a technical problem, but it is a cultural one as well.

Our identities, choices and digital trails are treated as commodities. Every click feeds a system designed not to understand us but to monetise us. It does not have to stay that way. Technology does not have to be built on surveillance. It can put people first.

Taking back control starts with awareness. We cannot fix what we cannot see. Exposing the pipelines that carry our data, and the money they make, challenges the idea that this is simply how things are. Awareness leads to accountability. Set the four repairs from section 9 and read the paper that comes out tomorrow.

Awareness alone is not enough. We need systems rooted in transparency, privacy and consent: tools that work for us, not on us; governance that values ethics as much as innovation; schools that treat digital literacy like reading and maths. Above all we need a culture in which privacy is seen as strength, not paranoia. Privacy law did not start with the GDPR, though. It has been catching up for more than fifty years.

The hidden economy will not vanish overnight. Change rarely starts with silence. It starts with questions, conversations and a refusal to go along. Your data is not worthless. Your identity is not a product. Your attention is not up for auction. The age of invisible trade has to end, and users get to write what comes next.

Data capitalism has made one thing clear: the old rules no longer work. Consent has shrunk to a box nobody reads. Privacy has become a myth, and digital dignity an afterthought. A better future needs more than tougher regulation or louder protest. It needs a new digital social contract that resets the relationship between people, data and power.30,31

The contract starts with recognition: our data is an extension of ourselves, not a crop to be harvested. Ownership should be the default, not an option.32 People should have the right to know who is collecting their information, why and for how long. Platforms and governments should meet a clear standard of digital ethics. Convenience should never cost surveillance. Decisions made by algorithms should be explainable, open to challenge and fair, and systems should be built around human values, not just engagement or profit.33

The clauses below come from this paper. Pick the ones you would sign, then sign it with your finger or mouse.

Finally, the contract has to be global. Data crosses borders, so the answers must too. What happens on one country's servers can affect people on the other side of the world. That calls for international cooperation, shared rules for data that travels and a common commitment to digital spaces that empower people rather than exploit them.29

A digital world where your data means your rights, not their profits. Not someday. Now.

The trade in personal data is not a side plot of the digital revolution. It is the main story. Every like, tap and voice command feeds a system that does best when it knows more about you than you know about yourself. That quiet exchange has shifted power, tilted markets and changed what consent means. Privacy is not being lost. It is being taken, quietly.

But awareness is growing. People are less willing to swap convenience for surveillance. Lawmakers are asking harder questions. Designers and developers are building tools that put people's autonomy first. The culture is changing, even if the infrastructure is slow to follow.

This paper is meant as more than criticism. It is a signal flare: a reminder that data is not just metadata. It is identity, behaviour and choice written in code, and reclaiming it is a moral question as much as a technical one.

We are at the start of a new kind of digital citizenship, in which people are informed participants rather than passive sources of data. The road will be complicated. With transparency, regulation and ethical design, it is possible to build systems that empower instead of exploit.

The era of invisible trade can end. But only if we make it visible first.

Raj, A. (2025, April). Data for sale: How your digital life fuels an unseen empire. The Build Journal Research Supplement, No. 1. https://abhnv.in/p1/

@article{raj2025dataforsale,
  author  = {Raj, Abhinav},
  title   = {Data for Sale: How Your Digital Life Fuels an Unseen Empire},
  journal = {The Build Journal Research Supplement},
  number  = {1},
  year    = {2025},
  month   = apr,
  url     = {https://abhnv.in/p1/}
}