The digital economy doesn’t offer free services. It offers services whose price is paid in a currency that doesn’t appear on any receipt. That currency is participation: your attention, behavior, identity, and your time. Most of it becomes someone else's capital. This introduction names the structural condition that makes it all possible, establishes the economic framework for measuring it, and argues that the correction required isn’t regulation, redistribution, or resistance. The correction is legal recognition of people as the origin of the value their participation generates. Thirteen papers will follow and all of them measure what the absence of that recognition costs.
Note from the Author: during this series I will be using some of the jargon that these industries apply. Two terms appear throughout and are worth defining at the outset. 'Participation' describes the act of engaging with a digital domain: the attention, behavior, time, and data that people contribute when they use a platform or service. 'Surface' describes the point of contact, the place where a person touches a platform, domain, or industry and where participation begins.
The business model of advertising-supported media isn’t new. Radio offers free services underwritten by advertisers who pay to reach listeners. The listener contributes nothing beyond their time and receives the broadcast in return. The transaction is complete when the program ends. Digital platforms appear to follow the same logic, but they do not. Radio monetized attention while digital platforms monetize the whole person; their behavior, identity, relationships, biological existence, and the complete record of every choice they’ve made since they first went online. The difference between radio and digital platforms isn’t a matter of degree. It’s a difference in what’s being taken, from whom, and whether the person being taken from has any legal standing in the arrangement.
Earlier advertising systems operated within recognized resource constraints; radio broadcasters built private infrastructure but operated on publicly licensed airwaves — the United States Supreme Court confirmed in Red Lion Broadcasting Co. v. FCC, 395 U.S. 367 (1969), that the airwaves belong to the public and that private use of them carries public obligations. The commercial internet operates differently. It measures and monetizes the behavioral participation of billions of individuals while recording the resulting revenue as though the originating participants weren’t part of the transaction.
The commercial internet emerged from two reinforcing pressures: venture capital models that pursued rapid user growth before establishing any revenue structure, and a counter-cultural conviction that information online should be free. Advertising emerged as the resolution to both pressures. These forces met in the late 1990s and early 2000s, producing a default assumption about price that wasn't the result of deliberate economic reasoning. The zero-price idea wasn’t discovered through market competition or arrived at through negotiation between parties with equal information and standing. It was assumed, then institutionalized, and then defended by the interests that had been built upon it. By the time the advertising model matured into the dominant architecture of the commercial internet, the zero-price model had become so entrenched that questioning it required not just a policy argument but a conceptual reframing of what was actually being exchanged. (Arrieta-Ibarra, Goff, Jiménez-Hernández, Lanier, and Weyl, Should We Treat Data as Labor? Moving beyond Free, AEA Papers and Proceedings 108, 2018).
The scale of what that pricing convention now governs is difficult to overstate. Alphabet Incorporated reported total revenues of approximately $350 billion for the fiscal year ended December 31, 2024, of which Google advertising revenue constituted $264.59 billion. The United States accounted for 49% of those revenues, producing approximately $129.6 billion in domestic advertising revenue. Divided across approximately 270 million monthly active U.S. users, that figure represents a realized participation value of approximately $480 per U.S. user per year from Google properties alone. Meta Platforms Inc. reported United States and Canada revenues of $63.21 billion for the same period, against approximately 260 million daily active people in those markets, producing a participation value of approximately $243 per user per year. A U.S. resident active on both platform families generates approximately $723 in participation value annually across these two companies alone. The money those users received for generating it was zero. (Alphabet Inc., Annual Report on Form 10-K, fiscal year ended December 31, 2024; Meta Platforms Inc., Annual Report on Form 10-K, fiscal year ended December 31, 2024).
Origin Economics is the study of value that originates in persons (in their attention, behavior, creativity, relationships, and biological existence), and the structural conditions under which that value is captured by systems that don’t recognize its origin. Where conventional economics asks how markets price goods and services, Origin Economics asks what happens when the primary input to a market is systematically misclassified at its point of origin, and what recognizing that origin would produce. The answer, calculated platform by platform, domain by domain, across thirteen papers and every major surface of digital participation, is the subject of this series. The conceptual framework underlying that calculation — the economic model, the legitimacy variable, the production conditions required for genuine exchange — is developed in the Origin Economics series. The Price of Free applies that framework to the specific domain of digital participation, using the Personal Data Royalty formula as the instrument for quantifying what the legitimacy variable's failure produces in each domain examined.
User-generated data is treated as exhaust: a byproduct of consumption, collected by firms, and never recognized as a contribution deserving compensation. Under this classification, platforms aren’t extracting value from users, they’re collecting ambient information that users produce incidentally while receiving services. The user is a consumer, the data is a byproduct, and the platform is a service provider. The exchange is complete when the service is delivered and the data is collected. No further accounting is required because no productive contribution has been recognized. This classification is convenient, and wrong. It misidentifies the origin of the value platforms capture, and in doing so produces systems optimized around a false input price. The error isn't definitional — it has consequences that run through the entire architecture of the digital economy: through the engagement optimization systems platforms build, the regressive distribution of participation costs across income groups, the legal frameworks that treat participation as a privacy problem rather than a compensation problem, and the AI training infrastructure now crystallizing decades of unrecognized human contribution into systems that will make the misclassification permanent. The Origin Economics framework expresses this condition as
Y = λ · f(H, K, T)
which is, output as a function of human-origin participation, capital, and technology, multiplied by whether the legitimacy conditions of the exchange were satisfied.
• H is human-origin participation — everything a person contributes to economic systems: their time, attention, labor, knowledge, skill, creativity, presence, information, and data.
• K is capital — the money, infrastructure, platforms, and systems built to organize that participation.
• T is technology — the tools that scale what capital organizes.
• Y is output — everything the economy produces from that combination.
• λ is the legitimacy variable — the single question the model asks about every transaction involving human participation: did the person at the origin have genuine legal standing in the arrangement? When λ holds, the exchange was genuine. When λ fails, what occurred was not exchange, it was extraction, and the economy should account for it differently because it’s a different thing.
The distinction between data as capital and data as labor has been made in the peer-reviewed economic literature. Arrieta-lbarra, Goff, Jiménez-Hernåndez, Lanier, and Weyl, writing in the American Economic Association's Papers and Proceedings in 2018, argued directly that user data should be treated as labor rather than as capital — that it’s a user possession that should primarily benefit its owner rather than exhaust from consumption to be collected by firms. The paper documented the monopsony power that technology platforms exercise over data providers, noting that users aren’t aware of the productive value of their data or the role they play in enabling machine learning and behavioral prediction markets. It proposed data labor unions as the countervailing power mechanism through which users could improve their bargaining position.
Origin Economics builds on this foundation and extends it in a direction that the existing literature hasn’t taken. The data labor argument correctly identifies that participation generates value deserving compensation. It doesn’t resolve the prior condition that makes compensation structurally unavailable: users aren’t recognized as the origin of what they contribute. You can’t negotiate compensation for value you’re not acknowledged to have produced. A data labor union assumes legal standing that the framework argues does not yet exist; recognition precedes bargaining. The Personal Data Royalty formula introduced later in this paper operationalizes what recognition would produce if it were established — not as a proposal for what platforms should pay, but as a measure of the gap between value generated and value recognized. (Posner and Weyl, Radical Markets: Uprooting Capitalism and Democracy for a Just Society, Princeton University Press, 2018; reviewed by Isztin, Oeconomia 9(4), 2019).
The extraction that results from misclassification has been documented in a different register by Shoshana Zuboff, whose surveillance capitalism framework describes human experience as the raw material from which behavioral data is extracted, processed into prediction products, and sold in behavioral futures markets whose operation occurs entirely outside the awareness of the people whose behavior is being traded. Origin Economics reaches a similar empirical description of the extraction mechanism but diverges in its analytical framing. Where the surveillance capitalism framework treats the problem primarily as a political and moral crisis requiring resistance and democratic intervention, Origin Economics treats it as a structural misclassification requiring recognition architecture. The concern is not only that extraction violates autonomy — though it does — but that it misclassifies the origin of the value it captures, producing systems that are simultaneously unjust and economically unstable. A moral and political framing produces demands for regulation and resistance. A structural economic framing produces demands for recognition — for the person who generates participation value to be acknowledged as its origin, and for the exchange between participant and platform to be recorded accurately as exchange rather than as collection of ambient byproducts. (Zuboff, The Age of Surveillance Capitalism, PublicAffairs, 2019; as analyzed in Dufva, In Dialogue with The Age of Surveillance Capitalism, Master's thesis, Tampere University, 2022).
The distinction matters because it determines what kind of response is adequate. Regulation can constrain the terms of extraction without resolving the misclassification. Resistance can reduce participation without establishing the legal recognition that would make participation's terms negotiable. Only legal recognition addresses the structural source of the problem — the classification of a productive input as something other than what it is.
Participation isn’t a vague concept in Origin Economics. It’s a precisely defined economic category. Participation is the contribution of attention, behavior, identity, creativity, time, and biological existence to systems that derive productive value from those contributions. It’s distinguished from consumption by its directionality: consumption removes value from a system, participation adds it. When a person searches Google, they’re not only consuming a search result, they’re contributing a behavioral signal — a precisely time-stamped record of intent, attention, and preference — that becomes an input to a production function whose outputs are sold to advertisers. The consumption and the contribution occur simultaneously in every interaction, but only the consumption is recorded in the prevailing economic framework. The contribution disappears.
This simultaneous consumption and contribution are the structural feature that makes digital participation categorically different from the transactions conventional economic frameworks were designed to analyze. When you buy a product, you consume it and the transaction is complete. When you use a free digital service, you consume it and simultaneously generate a productive contribution whose value flows to the platform rather than to you. The transaction isn’t complete when the service is delivered; it’s ongoing, continuous, and cumulative. Every search deepens the behavioral profile, every post extends the social graph, and every purchase signal refines the price sensitivity model. Every hour of engagement adds to the longitudinal record of a person's preferences, decisions, relationships, and identity.
The cumulative nature of participation is what makes its misclassification so consequential. A single search query has modest value. A decade of search queries from a single person is a record of their intellectual, commercial, and personal life whose predictive value is qualitatively different from the sum of its parts. A single social media post has modest value, but a decade of posts, reactions, relationships, and behavioral patterns is a model of a person's social psychology, political identity, and emotional architecture. The value of participation compounds over time in ways that the zero-price model never accounts for, because the zero-price model doesn’t recognize that the compounding is occurring at all.
This compounding is also why the free-to-play gaming economy, examined in Paper Two of this series, represents a particularly acute form of the misclassification. Roblox Corporation reported 82.9 million average daily active users in fiscal year 2024, the majority of whom are minors, generating 73.5 billion hours of annual engagement on a platform that retains approximately 71 cents of every dollar generated by the creator labor that built its content. (Roblox Corporation, Annual Report on Form 1 0-K, fiscal year ended December 31, 2024). The behavioral profiles assembled from children who spend 2.4 hours daily on a platform from the age of eight or nine aren’t equivalent to the behavioral profiles of adult users. They are longitudinal records of preference formation, identity development, and commercial socialization beginning at the point when those processes are most formative and extending across the period when they’re most consequential. The platform acquires this data at zero cost per participant. The participant — a child who cannot legally consent, cannot assess the value of what they are contributing, and cannot negotiate the terms of the exchange — receives entertainment in return. The price was never zero. For children, it was higher than for anyone else.
The structural problem Origin Economics identifies has a historical parallel in the economics of natural resource extraction that illuminates both the nature of the problem and the architecture of the solution. Natural resources have a recognized origin. Oil is in the ground. The ground belongs to someone — a person, a community, a sovereign state. The extraction of oil requires acknowledging where it comes from and compensating the origin through royalties, mineral rights, sovereign wealth funds, and land leases. The entire legal and economic architecture of natural resource extraction is built on the premise that the resource has an origin point that can’t be erased by the act of extracting it. The extractor may be more sophisticated, better capitalized, and better equipped than the origin. The extractor may provide genuine value in the form of infrastructure, technology, and economic development, but none of that eliminates the origin's claim. The resource came from somewhere and that somewhere has rights. Participation data has an origin point too. It originates in a person. Every behavioral signal, every preference record, every social graph connection, every biological marker, every creative contribution originates in a specific human being whose existence and activity produced it. But unlike oil, the legal and economic architecture surrounding participation data doesn’t recognize the source. The extraction occurs without royalty, without mineral rights, and without any of the compensatory infrastructure that natural resource law built over centuries. That infrastructure was built precisely because uncompensated extraction of valuable resources from their origins produces structural injustice. No equivalent architecture exists for participation data.
The grazing of livestock on American public lands offers a second parallel, and in some ways a more precise one. The Taylor Grazing Act of 1934 was intended to end the effective free use of federal rangeland and establish a permit and fee system that reflected the value being extracted. What it produced instead was a fee structure set so far below market value that it functioned as a continued subsidy; ranchers who had been grazing for free had their access institutionalized at nominal cost. The value extracted from it flowed to a smaller group of private commercial operators, despite the fact that public land belongs to everyone. The fee structure was set by the interests that benefited from keeping it low, and reform was resisted on the grounds that raising the price would destroy an industry the broader economy depended on. The commercial internet's zero-price norm follows the same pattern. Participation data originates in the public, in hundreds of millions of individuals whose behavior, identity, and attention generate the resource being extracted. The price of that extraction was set by the platforms that benefit from it. And the argument made against recognizing its value is the same argument the ranchers made: that the system everyone depends on wouldn't survive an honest accounting of what it actually costs.
Resource economics distinguishes between three categories of income: labor income, which is payment for work performed; capital income, which is return on equipment or infrastructure; and resource rent, which is payment for extraction of a naturally occurring input. Behavioral participation behaves economically like resource rent — not labor wages, not platform capital returns, but a third category whose existence the current accounting system doesn’t recognize. The commercial internet treats behavioral data as though it were terra nullius, a resource belonging to no one. But the resource is generated continuously by identifiable individuals. That’s the tension the framework exposes and the misclassification it measures.
The parallel has limits that are worth stating directly. Natural resources are passive; the ground doesn’t generate oil through its own activity. Participation is active; the person continuously generates participation value through their behavior, choices, relationships, and creativity. This makes the origin claim stronger than the natural resource case, not weaker. You can deplete an oil field, but you can’t deplete a person who keeps generating participation value every day they are alive and connected. The resource isn’t finite, it's renewable, cumulative, and increasingly valuable as the systems that process it become more sophisticated. A person whose behavioral data has been collected for twenty years isn’t a depleted resource, they’re an increasingly precise model whose predictive value grows with every additional data point.
The second limit is jurisdictional. Natural resource rights are geographically bounded and legally established across centuries of property law, treaty, and sovereign authority. Participation rights do not yet exist as a legal category in most jurisdictions. The regulatory frameworks that govern digital participation — the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), the Children's Online Privacy Protection Act (COPPA) — treat it as a privacy problem rather than a property or labor problem. They regulate how data is collected and retained. They don’t recognize the person as the origin of participation value or establish a mechanism through which that recognition could produce compensation. The legal architecture that natural resource extraction required centuries to build does not yet exist for participation data. Origin Economics argues that building it begins with recognition — establishing the person as the acknowledged origin of the value their participation generates, before any question of compensation, regulation, or market design can be meaningfully addressed.
The third limit is the most important. Natural resource extraction is zero-sum in a way that participation extraction is not. When oil is extracted, it’s gone. When participation value is extracted, the person who generated it retains their capacity to generate more. This means that recognizing participation's origin doesn’t require stopping the extraction. It requires recording it accurately — establishing that an exchange occurred, that it had a price, and that the person who paid that price is acknowledged as having paid it. The correction Origin Economics proposes isn’t the end of the digital economy as it currently operates, it’s the beginning of an accurate accounting of what that economy actually is.
Origin Economics proposes that the structural condition producing the misclassification can be defined precisely. Participation generates economic value when it is recognized as originating in a person with standing in the system organizing it. That recognition requires four conditions to be simultaneously present.
The first is survivable refusal — the participant must be able to decline participation without immediate consequences to their capacity to function in ordinary economic and social life. Survivable refusal doesn’t require that refusal be costless. It requires that the cost of refusal not extend to the participant's basic capacity to participate in economic and social existence. A person who can choose not to use Facebook without losing access to essential services satisfies the survivable refusal condition for Facebook, even if the social cost of refusal is real. A person who can’t exit the data broker market, the credit scoring infrastructure, the insurance pricing systems, or the healthcare record architecture, regardless of whether they have ever knowingly contributed to any of them, doesn’t satisfy the survivable refusal condition for the participation infrastructure those systems depend on.
The second is recognized standing — the participant must be acknowledged as the origin of what their participation produces rather than as a passive subject whose behavior is ambient to the platform's operations. Recognized standing is the condition whose absence most clearly distinguishes the current structure of digital participation from legitimate exchange. A worker who isn’t recognized as a worker can’t bargain for wages. A producer who isn’t recognized as a producer can’t negotiate for a share of the value their production generates. A person whose participation is classified as the incidental byproduct of consuming a free service, rather than as a productive contribution to a revenue generating system, has no standing from which to demand recognition of that contribution. The absence of recognized standing isn’t an oversight in how digital platforms have been designed. It’s the structural condition that makes the zero-price equilibrium stable. Users who were recognized as producers would immediately face the question of why they’re not financially compensated. Maintaining non-recognition suppresses that question before it can be asked.
The third is transparency of terms — the participant must have sufficient knowledge of what their participation generates to make a meaningful choice about whether to engage. Transparency of terms doesn’t require perfect information; it requires that the participant have access to the information that would materially affect their decision to participate if they had it. A person who doesn’t know that their annual participation on a single platform generates several hundred dollars in advertising revenue for that platform doesn’t have the information required to make a meaningful choice about whether to participate, on what terms, or at what level of engagement. The terms of service documents through which platforms currently purport to disclose their data practices aren’t instruments of meaningful transparency. They’re instruments of legal cover — written to satisfy disclosure requirements rather than to inform participant decision-making.
The fourth is independent jurisdiction — the participant must have recourse outside the organizing system for disputes about how their participation has been treated. Independent jurisdiction doesn’t require that every participant have practical access to litigation. It requires that the participant have access to a decision-making authority that isn’t controlled by the platform whose practices are being disputed. Binding arbitration clauses, which are standard in the terms of service of major digital platforms, do not satisfy this condition. They substitute a platform-selected dispute resolution process for independent judicial or regulatory review. Regulatory frameworks that operate on privacy rather than participation value grounds — GDPR, CCPA — provide partial recourse for specific categories of harm but do not address the foundational misclassification that Origin Economics identifies.
When all four conditions are present, participation functions as voluntary exchange. The platform receives human-origin value. The participant receives a service whose terms are understood and whose exchange is fairly recorded. When any condition is absent, the exchange is mis-recorded. The platform captures value that originated in participation it doesn’t recognize as exchange. The production function operates on misclassified inputs, price signals carry distorted information, and market coordination builds on a false foundation.
The largest platforms have maintained a data-as-capital equilibrium specifically because users aware of the value their data creates would demand compensation, dramatically reducing the share of value platforms could capture as profit. This is monopsony operating not merely at the level of wages but at the level of ontological classification — users aren’t even recognized as producers whose contributions might carry a price. (Arrieta-lbarra, Goff, Jiménez-Hernández, Lanier, and Weyl, Should We Treat Data as Labor? Moving beyond Free, AEA Papers and Proceedings 1 08, 2018).
The Personal Data Royalty (PDR) represents the annual participation value realized by a platform from a specific user, calculated from publicly available revenue data and adjusted for demographic variables that determine participation intensity and value. It’s not a claim for payment. It’s a measure of misclassification — the gap between the value a platform realizes from a user's participation and the price that user receives for generating it. That gap, summed across the U.S. user population of a single platform, produces figures in the hundreds of billions of dollars annually. It represents value that originated in human participation, was realized by platforms, and was never recorded as the exchange it actually constituted.
PDR = PVI × AC × IC × GC × H × BSC
PVI is the Participation Value Index, platform advertising revenue per user derived from published annual reports and estimated active usage figures. It represents the baseline value the platform realizes from an average user's participation, before the demographic coefficients are applied.
AC is the Age Coefficient. Advertising markets don't value all participation equally — a twenty-two-year-old's behavioral data commands higher rates than a fifty-five-year-old's. This differential is documented in published cost-per-thousand-impression data across age segments from digital advertising platforms. The Age Coefficient captures that differential, adjusting the baseline upward for demographics that command premium rates and downward for those that don't.
IC is the Income Coefficient, reflecting the inverse relationship between income and platform dependency. This relationship is documented in Pew Research Center survey data on social media use and platform dependency by income bracket. Lower-income users exhibit higher participation intensity and lower access to paid alternatives, meaning the zero-price model extracts most heavily from those least able to negotiate its terms. A person who can't afford a paid news subscription, a music streaming service without advertising, or a productivity suite without behavioral data collection is more dependent on free platforms and therefore generates more participation value per dollar of income than a higher income user with access to paid alternatives. The Income Coefficient makes this regressive structure visible in the formula.
GC is the Geographic Coefficient, reflecting the premium advertising markets of the U.S. relative to global averages. U.S. users generate disproportionately high advertising revenue relative to their share of global platform populations, reflecting the premium that advertisers pay to reach consumers in the world's largest consumer market. Alphabet's 10-K data confirms that the United States accounts for 49% of total Alphabet revenues while representing approximately 4% of the global population. The Geographic Coefficient captures this premium.
H is annual participation hours, the total time a user spends on a platform's properties in a given year. H is the variable most directly within the platform's control through ‘engagement optimization architecture’*. Platforms that maximize H without constraint — because the input carries no recognized price — produce the engagement optimization problem that runs through every paper in this series. H in the PDR formula is the measurable proxy for the full breadth of what H represents in the Origin Economics framework. Hours are what platform data discloses. What they represent is larger: the attention, behavior, identity, social relationships, and continuous presence that platforms convert into revenue. The formula measures what can be confirmed from primary sources. The framework names what that measurement represents.
* ‘Engagement optimization architecture’: every choice a platform makes about what you see, when you see it, and what comes next is engineered to keep you on the platform as long as possible. The feed, the notifications, the autoplay, the recommended content — none of it is designed around what is good for you. All of it is designed around one question: what keeps this person from leaving the platform.
BSC is the Behavioral Signal Coefficient: the variable that captures the depth and commercial value of what a user's participation reveals, beyond the duration measured by H. Platforms don’t price participation by the hour, they price it by what the hour contains. Two users who spend identical hours on the same platform generate fundamentally different participation value depending on what they do during that time. The Behavioral Signal Coefficient adjusts the PDR baseline upward for participants whose behavioral signals carry premium commercial value. Its components are:
• Purchase signals — active commercial intent expressed through search queries, product comparisons, and transaction history, the most immediately monetizable behavioral signal on any platform;
• Search intent: the specificity, frequency, and commercial orientation of information-seeking behavior;
• Posting behavior: the frequency, topic, sentiment, and engagement generated by a user's expressive participation;
• Social graph influence: the size, density, and commercial reach of a user's relationship network;
• Device integration: the breadth of platform access across a user's devices and daily life, which multiplies the completeness and commercial precision of the behavioral profile;
• Location behavior: physical movement patterns correlated with commercial activity, among the most commercially valuable signals platforms capture.
The precise calibration of BSC will be developed as the series proceeds. It’s introduced here as a defined framework variable. Its full application follows in the domains where behavioral depth is the primary driver of participation value: Healthcare and Wearables, Vehicles, Finance, and Al Training Data.
The formula doesn’t produce a single number for all users. It produces a range of numbers across the demographic distribution of a platform's user base, with the baseline representing the floor below which no user/s participation value can fall and the coefficients adjusting upward for users whose participation generates above-average value. The most significant finding of the formula's application, developed across the thirteen papers of this series, isn’t any individual figure but the aggregate: what a person's total participation is worth annually across every domain of their digital life, and what the cumulative misclassification costs them across a lifetime of participation.
The absence of compensation for behavioral participation isn’t mysterious. The modern platform economy emerged in an environment where the cost of measuring human behavior collapsed while the cost of compensating millions of individuals remained prohibitive. Technology lowered the cost of observing, recording, and trading behavioral data to near zero, it didn’t lower the cost of negotiating micro-royalties with hundreds of millions of users. The result was a system that records the revenue produced by participation with precision while omitting the participants themselves from the accounting. Not through conspiracy, but through the predictable institutional response to cost asymmetry — the transaction was moved inside the firm by removing the counterparty from the ledger entirely. (Coase, The Nature of the Firm, Economica 4(1 6), 1937). What the PDR formula does is convert an unpriced transaction into a calculable input. Once the input is measurable, the counterparty can be restored to the ledger. The formula doesn’t argue that compensation should exist, it shows that the transaction already exists economically. The ledger simply omits one side.
The zero-price model isn’t neutral in its distributional effects. Because lower-income users depend more heavily on free platforms — lacking the financial means to purchase paid alternatives — and because they spend more time on those platforms, they generate proportionally more participation value per dollar of income than higher-income users. The zero-price model therefore functions as a regressive participation subsidy: those with the least resources contribute the most to the value platforms capture, while receiving the same zero-price service as users who contribute less.
This isn’t incidental, it’s structural. A pricing model that extracts most heavily from those least able to negotiate its terms, while providing services they can’t afford to replace, isn’t a free market outcome. It’s the predictable consequence of a misclassified input operating at scale across an economy where digital participation has become the infrastructure of ordinary life. Access to employment, healthcare, education, financial services, social connection, and civic participation now runs substantially through platforms whose revenue model depends on the unrecognized participation of the people accessing those services. The person who uses Google to find a job, Meta to maintain family relationships, and a free educational platform to develop professional skills isn’t a consumer of free services, they’re a producer of participation value whose contribution subsidizes the infrastructure they depend on while receiving nothing in return beyond the service itself. The regressive structure is amplified in the gaming economy, where the free-to-play model specifically targets users who can’t or won’t pay for access, and in the education technology sector examined in Paper Three, where the state compels participation and private platforms extract value from a captive audience that has no survivable refusal option at all. It’s most acute in the healthcare and wearables domain examined in Paper Eight, where the participation being extracted is biological — body data, health behavior, genetic information — and where the consequences of misclassification extend fr om commercial disadvantage to insurance pricing, employment decisions, and legal exposure. The regressive structure is also the answer to the most common objection to the misclassification thesis — that free platforms democratize access to services that would otherwise be available only to those who could afford them. This objection is correct in its premise and wrong in its conclusion. Free platforms do extend access. The extension of access doesn’t eliminate the participation cost of that access. It transfers the cost from a visible monetary payment to an invisible participation contribution, and it distributes that cost regressively — extracting more from those with less, in a system those with less can’t afford to exit.
When a productive input carries no recognized price, rational economic actors organize their systems to maximize extraction of that input without constraint. This isn’t a failure of corporate ethics, it’s the predictable engineering response to a pricing signal. When participation costs nothing to acquire, the incentive to maximize its extraction is unlimited. There’s no cost to the firm from consuming more of it, no mechanism through which the person generating it can signal that they are being over-extracted, and no price that rises to constrain demand as supply is exhausted. The engagement optimization practices, dark patterns, notification architectures, variable-ratio reinforcement schedules, and behavioral modification systems that characterize the attention economy aren’t aberrations from good market behavior. They’re the logical and inevitable consequence of building an economy on an input whose price is classified as zero.
The engagement optimization problem compounds across the series. In Platform Participation, it produces recommendation systems designed to maximize watch time regardless of consequences to user wellbeing or informational quality. In Gaming, it produces loot box mechanics and social entrenchment architectures deployed on children who can’t recognize or resist them. In Education Technology, it produces learning management systems that extract behavioral data from students under compulsion. In The Connected Home, it produces ambient extraction infrastructure that extends the participation surface into the most private spaces of daily life. In Healthcare, it produces wellness platforms that convert biological participation into insurance pricing data. In each domain, the mechanism is the same: a zero-priced input, an optimization system designed to maximize its extraction, and a population of participants who don’t know they are paying.
The engagement optimization problem is also the mechanism through which the misclassification perpetuates itself. Platforms that maximize engagement build user dependency. User dependency reduces the survivability of refusal. Reduced survivability of refusal deepens the structural failure of the legitimacy conditions and deeper legitimacy condition failure makes recognition more difficult to establish. The system is self-reinforcing in the direction of extraction and self-perpetuating against the recognition that would correct it. This isn’t conspiracy. It’s the emergent property of an economy organized around a productive input that is classified as free.
The PDR calculation in this paper rests on disclosed per-user revenue from Google and Meta. It doesn't include the following participation surfaces. These exclusions aren't due to absence of participation, but due to the absence of disclosed, attributable per-user revenue at the level required for calculation.
The categories below are not exhaustive. They are representative of the system.
Search and Intent Formation
Bing, Yahoo, and browser-level search engines operate on the same participation model as Google. Default search agreements and intermediary routing further shape query flow without disclosing per-user revenue attribution.
Social Platforms Beyond Meta
TikTok, X, LinkedIn, Pinterest, Snapchat, Reddit, and Nextdoor all monetize user-generated content, attention, and interaction patterns through advertising, recommendation systems, and data licensing structures without per-user revenue transparency.
Video and Streaming Participation
TikTok video, Twitch, Rumble, and others capture behavioral signals through watch-time, interaction, and creator engagement systems structurally similar to YouTube, without disclosing per-user participation value.
Messaging and Communication Metadata
iMessage, WhatsApp outside Meta-attributed revenue, Telegram, Discord, and Slack in consumer use generate continuous metadata streams (contact graphs, frequency, timing, and behavioral inference) monetized indirectly or integrated into broader commercial ecosystems without per-user disclosure.
Music and Audio
Spotify, Apple Music, Amazon Music, Pandora, and SoundCloud capture listening behavior, mood-correlated consumption patterns, playlist construction, skip rates, and time-of-day audio preferences across hundreds of millions of users. Spotify reported 675 million monthly active users globally in 2024 and operates an advertising business on its free tier, but doesn't disclose per-user revenue at the level required for PDR calculation. The behavioral signals generated through music participation (what a person listens to, when, for how long, and in what emotional or activity context) constitute a continuous, high-resolution participation surface with clear commercial value. They're excluded from the baseline for methodological reasons only.
Maps, Movement, and Location
Apple Maps, Waze, and location data brokers capture continuous physical-world participation (routes, dwell time, and movement patterns) without disclosing attributable per-user revenue.
Email and Communication Infrastructure
Microsoft Outlook, Yahoo Mail, and Apple Mail telemetry operate on the same participation model as Gmail, where behavioral and content-adjacent signals are integrated into broader commercial systems without per-user disclosure.
Browser and Operating System Layer
Chrome, Safari, Edge, iOS, and Android operate as foundational participation layers. Behavioral telemetry at the device and OS level captures cross-application activity, forming the highest-resolution participation surface in the system (beneath and across every platform documented in this paper) without attributable per-user revenue reporting.
News, Content Aggregation, and Push Systems
Apple News, Flipboard, Pocket, and notification delivery systems structure attention flow and content exposure, generating measurable participation without direct per-user revenue attribution.
Productivity and Cloud Environments
Microsoft 365, Google Workspace, and Dropbox capture behavioral participation within document creation, collaboration, and storage environments, integrating that data into broader commercial systems without per-user disclosure.
Default Placement and Distribution Layer
Search default agreements, app store rankings, OEM preloads, and platform-level placement systems determine what users encounter before active choice occurs. These systems shape participation upstream of interaction, before a search is entered, before an app is opened, and before a preference is expressed. They represent a primary control surface for the participation economy without disclosed per-user revenue.
The $480 and $243 baselines established in this paper are derived from the two platforms that disclose per-user revenue with sufficient precision for calculation. They aren't a measure of what platform participation costs per person annually, they're the portion of that cost that has been disclosed. The floor is not the number.
The papers in this series apply the PDR formula across thirteen domains of human participation in the digital economy. Each domain applies the same analytical structure:
• identify the extraction surface
• examine the specific failure of the legitimacy conditions
• calculate the participation value realized by the platform
• apply the demographic adjustment coefficients
• produce the PDR figure for representative user profiles.
Each paper also examines the legal and regulatory exposure that follows from the misclassification it documents.
The series moves from the most visible extraction surfaces — attention platforms, gaming, streaming — through the less visible but more consequential: education, the home, healthcare, vehicles, and the intimate domains of desire and biological identity. It concludes with artificial intelligence (AI), where every extraction documented in the preceding papers converges into systems that perpetuate and scale the underlying misclassification. Al training data is human-origin participation crystallized into model capability — the writers, artists, programmers, and ordinary people whose participation built the systems now replacing them, receiving recognition of zero.
The arc of the series stated plainly:
• Papers One through Four cover what you do.
• Papers Five through Seven cover what you buy and where you go.
• Papers Eight and Nine cover what your body is and who you desire.
• Papers Ten through Twelve cover who you know, what you own, and who you are.
• Paper Thirteen is all of it, forever, at scale.
By Paper Thirteen the reader understands that the extraction of human-origin participation without recognition isn’t a feature of one sector of the digital economy, it’s a complete map of human existence monetized without consent. And the PDR formula running through all thirteen papers produces one number. What are you worth to the systems that have been extracting you your entire digital life? That number is the answer to the question nobody has been allowed to ask.
The series moves from behavior to identity, from the surface of participation to the core of personhood. The argument running through all thirteen papers is the same: Participation originates in persons; the value it generates is real, measurable, and currently captured at scale without recognition of its origin; the correction is not redistribution, it’s recognition. Establishing the person as the acknowledged origin of participation value, and recording the exchange between participant and platform accurately as exchange is the entire purpose of these papers.
The price was never zero. It was always paid. The question the series asks is why the person who paid it has never appeared in the accounting.
Alphabet Inc., Annual Report on Form 10-K for the fiscal year ended December 31, 2024, filed with the United States Securities and Exchange Commission, February 4, 2025.
Meta Platforms Inc., Annual Report on Form 10-K for the fiscal year ended December 31, 2024, filed with the United States Securities and Exchange Commission, January 29, 2025.
Roblox Corporation, Annual Report on Form 10-K for the fiscal year ended December 31, 2024, filed with the United States Securities and Exchange Commission, February 18, 2025.
Imanol Arrieta-lbarra, Leonard Goff, Diego Jiménez-Hernández, Jaron Lanier, and E. Glen Weyl, Should We Treat Data as Labor? Moving beyond Free, AEA Papers and Proceedings 108, 2018, pp. 38-42.
Eric Posner and E. Glen Weyl, Radical Markets: Uprooting Capitalism and Democracy for a Just Society, Princeton University Press, 2018; reviewed by Peter Isztin in Oeconomia 9(4), 2019.
Shoshana Zuboff, The Age of Surveillance Capitalism, PublicAffairs, 2019; as analyzed in Rosa Aaron Dufva, In Dialogue with The Age of Surveillance Capitalism, Master's thesis, Tampere University, 2022.
Ronald Coase, The Nature of the Firm, Economica 4(1 6), 1937, pp. 386-405.
Red Lion Broadcasting co. v. FCC, 395 U.S. 367, 1969.