In 1879, an obscure San Francisco journalist named Henry George published a book that would become, for a time, one of the best-selling works in American history. Progress and Poverty asked a simple question: Why does poverty persist alongside economic growth? His answer was radical in its simplicity. The problem was land.

Not land as dirt, but land as location—the fact that some places are valuable and others aren’t, and that this value comes almost entirely from what the surrounding community does, not from anything the landowner contributes. A vacant lot in downtown Manhattan is worth millions. An identical patch of soil in rural Nevada is worth almost nothing. Same dirt. Different neighbors.

George’s proposal followed logically: tax the unimproved value of land—the location itself, not the buildings or improvements—and use that revenue to replace other taxes. The beauty of the idea was threefold. First, fairness: you’d be capturing value created by the community rather than by the owner. Second, efficiency: landowners couldn’t respond by producing less land (there’s a fixed supply), so the tax wouldn’t distort economic activity the way taxes on labor or production do. Third, it would discourage speculation and encourage productive use.

The land value tax never swept the world as George hoped, though it has devotees to this day and has been implemented in partial forms in places like Singapore and parts of Pennsylvania. But set aside whether George was right about land specifically. The deeper question is whether his logic applies to anything else.

What if there are other things—things that aren’t physical land—that share the same essential properties? Things that exist as a kind of commons, that nobody really “created” in the way you create a product, and that generate enormous value as society learns to use them?

What if there’s land in conceptual space?

The Conceptual Commons

To extend George’s logic, we need to identify what plays the role of “land” in the realm of ideas. Not everything qualifies. A new app isn’t land—someone built it. A patented invention isn’t land—it’s the product of deliberate R&D. We’re looking for something more fundamental: the conceptual equivalent of location, the underlying territory that gains value as civilization develops around it.

The candidates are things like mathematical principles, foundational algorithms, basic frameworks for understanding the world. Things that are discovered or derived rather than invented. Things that are, in principle, public goods—non-rivalrous (my use doesn’t diminish yours) and non-excludable (once known, you can’t really prevent people from knowing them).

An Example: Compound Interest

Compound interest isn’t an invention. It’s a mathematical fact about exponential growth. Nobody owns it. You can’t patent the idea that reinvested returns generate returns of their own. It’s part of the shared inheritance of human knowledge, sitting there in the public domain, free for anyone to understand and apply.

And yet the value generated through compound interest is almost incomprehensibly large. Every mortgage, every bond, every retirement account, every corporate loan, every savings product—all of them run on compound interest. The entire architecture of modern finance is built on this one principle. When you hear that the U.S. federal government pays hundreds of billions of dollars a year in interest on its debt, that’s compound interest at work. When pension funds grow over decades to support retirees, that’s compound interest. When credit card debt spirals out of control, that’s also compound interest.

The principle itself is ancient—Babylonian clay tablets from 2000 BCE show calculations of compound interest. But the value it generates has grown enormously as financial systems have become more sophisticated, as more people have access to banking, as capital markets have deepened. Just as a plot of land becomes more valuable when the city grows around it, compound interest becomes more “valuable”—in the sense of generating more total economic activity—as the financial system becomes more complex.

The land is the principle. The rent is the value generated by applying it.

A Second Example: The Fourier Transform

Lest this seem like a story only about finance, consider the Fourier transform—a principle that has nothing to do with money and yet is responsible for an almost incomprehensible amount of economic value.

In the early 19th century, Joseph Fourier discovered that any complex signal—a sound wave, an image, a time series—can be decomposed into a combination of simple sine waves. This wasn’t an invention; it was a mathematical truth waiting to be understood. Fourier was studying heat flow. He had no idea what his insight would eventually make possible.

Today, the Fourier transform is everywhere. When your phone compresses an image to send over text, it’s using Fourier-related mathematics. When an MRI machine constructs an image of your brain, it’s applying Fourier transforms to raw signal data. When Spotify streams music or when Netflix compresses video, Fourier analysis is at work. When seismologists interpret earthquake data, when astronomers process signals from distant stars, when engineers design noise-canceling headphones—all of it depends on this one 200-year-old mathematical principle.

The value generated is incalculable. Billions of devices, trillions of transactions, entire industries—medical imaging, telecommunications, audio processing, data compression—built on a foundation that nobody owns and everyone can use. Fourier’s insight is conceptual land in the purest sense, and modern civilization has built a city on top of it.

This is what a public good looks like. Non-rivalrous: my use of the Fourier transform doesn’t diminish yours. Non-excludable: once it’s understood, you can’t prevent people from applying it. And yet it generates staggering economic value—value that, if George’s logic were extended and a virtual land value tax were somehow possible, could in principle be partially captured and reinvested in the conceptual commons. That’s not feasible in practice, and probably not palatable politically. But the underlying logic holds: here is shared territory that we all build on, and the question of who tends it—who discovers the next Fourier transform, who validates it, documents it, makes it accessible, helps people apply it well—is not one we’ve answered institutionally.

The Thought Experiment: A Virtual Land Value Tax

Here’s where George’s logic gets interesting. If we can identify the conceptual equivalent of land—foundational principles that generate massive value—then we can at least imagine the conceptual equivalent of a land value tax.

Call it a Virtual Land Value Tax, or VLVT. The idea would be to apply an ultra-small levy on the economic value generated through certain public-domain principles, and use that revenue to fund the discovery, validation, and deployment of more such principles.

How small? Think thousandths of a percent. A 0.001% skim on the trillions of dollars of interest-related value flowing through the financial system would generate billions per year—not hundreds of billions, but enough to fund a serious institution. For reference, the U.S. Patent and Trademark Office operates on a budget of around $4 billion annually.

The mechanism would be something like this: built-in micropayment infrastructure that takes an imperceptibly small cut from transactions that derive value from certain tagged, public-domain conceptual assets. This only becomes technically imaginable in a digital economy. You couldn’t do it with paper ledgers. But with modern payment rails, the granularity exists to levy charges of fractions of a cent and aggregate them into meaningful sums.

The revenue would then fund what we might call a Civilian Innovation Corp—an institution dedicated to finding, validating, and operationalizing high-value ideas, then releasing them openly for broad benefit.

Let me be honest: this specific mechanism is probably not feasible.

The implementation would require knowing when particular principles or algorithms are being used, which raises immediate problems. How do you detect when a transaction involves compound interest versus some other financial structure? How do you tag algorithmic usage at scale? The answer involves deep visibility into financial systems and code—something that starts to look like systemic surveillance. And whatever its technical merits, a system that monitors which concepts people are applying in their economic activity is not politically palatable and raises serious questions about privacy and autonomy that are paramount.

So the VLVT as described is likely a thought experiment rather than a policy proposal. But the thought experiment clarifies something important: there’s a real gap in our institutional landscape. We have robust mechanisms for funding and protecting private innovation—patents, venture capital, trade secrets, corporate R&D. We have much weaker mechanisms for cultivating the conceptual commons.

The value of the thought experiment is not the specific funding mechanism. It’s the question it forces us to ask: what would it look like to have a serious, well-resourced institution whose job is to find, validate, cultivate, and operationalize ideas that benefit everyone?

Who Does This Now?

The honest answer is: various organizations try, but each has limitations.

DARPA (the Defense Advanced Research Projects Agency) is often cited as a model for high-impact public R&D. It funded the early internet, GPS, and countless other technologies that became foundational. But DARPA’s mission is defense, which shapes what it funds and how. Technologies developed there often remain classified or controlled for years. The goal is national security advantage, not open public benefit.

Academic research institutions produce enormous quantities of basic research, some of which becomes foundational. But academia’s incentives favor publication and citation over operationalization. A brilliant paper might sit in a journal for decades before anyone figures out how to apply it. The gap between “published” and “practically deployable” is vast, and academia has little institutional interest in closing it.

Philanthropic efforts like the Gates Foundation, Open Philanthropy, and various research-focused nonprofits fund valuable work. But philanthropic priorities are set by donors, which introduces its own biases. The work tends to focus on causes that appeal to wealthy individuals—which is not necessarily the same as “ideas with the highest leverage for public benefit.” There’s also a legitimacy question: do we want the conceptual commons shaped by the preferences of billionaires?

Think tanks produce policy ideas and frameworks, but most have ideological commitments that shape their output. They’re often funded by parties with interests in particular conclusions. And their focus is usually on advocacy rather than rigorous validation and operationalization.

Open source foundations (Mozilla, Apache, Linux Foundation, etc.) maintain crucial shared infrastructure, but primarily in software. They’re a good model for what collaborative maintenance of commons can look like, but their scope is narrow—code, not concepts more broadly.

Private R&D labs like Bell Labs in its heyday produced extraordinary foundational work. But Bell Labs existed because AT&T had a regulated monopoly and could afford to fund pure research. Modern corporate R&D is more tightly coupled to product development. When Google or Microsoft fund basic research, the goal is ultimately competitive advantage, and much of what they learn stays proprietary.

Government science agencies (NSF, NIH, etc.) fund basic research, but with important constraints. They’re subject to political pressures. Funding is often tied to existing academic structures. The path from “funded research” to “operationalized tool that policymakers or citizens can actually use” is long and poorly supported.

Each of these institutions does valuable work. None of them has, as its primary mission, the task of finding high-leverage ideas wherever they emerge, rigorously validating them, and shepherding them into forms that are practically useful—and then releasing them openly, for anyone to use. That’s the gap.

The Civilian Innovation Corp

Imagine an institution designed specifically to fill that gap.

Call it the Civilian Innovation Corp—a deliberate echo of the Civilian Conservation Corps, the New Deal program that mobilized unemployed young people to build parks, trails, and public infrastructure during the Great Depression. The CCC built things we still use today. The trails in national parks, the lodges, the fire roads—much of it is CCC work, maintained ever since through park fees and public funding.

The Civilian Innovation Corp would build conceptual infrastructure. Its mission would be to find, validate, cultivate, and operationalize ideas that benefit large swaths of society—and to do so openly. Not products to sell, but frameworks, tools, and principles to deploy in the commons.

The work would proceed in phases:

Search and scout. The Corps would actively look for promising ideas—not just in academic journals, but in industry practice, open-source communities, government agencies, international contexts. What frameworks are people using that seem to work well? What principles have been validated in one domain but not yet applied elsewhere? What patterns keep appearing across different fields?

Validate and test. Promising ideas would be treated like minimum viable products in the conceptual domain. Subject them to stress tests—empirical, theoretical, across different contexts. Does this framework actually work? Under what conditions? What are its limits? What happens when it’s applied at scale?

Refine into general-purpose tools. Ideas that survive validation would be developed into what we might call “maximally viable principles”—clear documentation, guidelines for effective use, model implementations, case studies of successful and unsuccessful applications. The goal is to transform a good idea into a deployable tool.

Operationalize and disseminate. The final phase would package these tools for actual use. Toolkits for policymakers. Training programs for practitioners. Reference implementations that organizations can adapt. The gap between “knowing about an idea” and “being able to apply it well” is where most good ideas die. The Corps would specialize in bridging that gap.

The model would be something like a venture capital fund, but oriented toward ideas for the commons rather than startups seeking exits. Back a portfolio of conceptual projects. Expect most of them to be niche or not scale. But the ones that work—the ones that get adopted widely and generate value across many contexts—would justify the entire effort.

The Human Element

Where would the people come from?

There is, right now, an enormous amount of talent that wants to work on things that matter but doesn’t have clear pathways to do so. People in academia who are frustrated by the gap between research and impact. People in industry who want to contribute to something beyond shareholder value. People in government who see opportunities that bureaucracies can’t act on. People early in their careers who want to build things that last.

The original CCC gave people a place to direct their energy toward shared benefit. It provided structure, resources, and purpose. The Civilian Innovation Corp would do the same for a different kind of work.

This isn’t about creating a new class of technocratic experts who decide what’s good for everyone else. It’s about building capacity for a particular kind of work: the disciplined, rigorous process of taking ideas from “promising” to “practically useful”—and doing it in the open, for everyone’s benefit. That work requires diverse perspectives—people who understand implementation challenges, people who understand politics, people who understand how things fail in practice, not just how they succeed in theory.

The Race Between Private and Open Innovation

Right now, there’s a strong gravitational pull toward private innovation. If you have a good idea, the most obvious path is to start a company, patent it, raise venture capital, and try to capture the value yourself. This is fine. It produces useful things. It funds further innovation. But it also means that ideas get locked up—protected by intellectual property, kept secret as trade advantages, optimized for private returns rather than broad benefit.

What a Civilian Innovation Corp would introduce is a parallel track. A place where the explicit goal is to push ideas into the commons—to make them open, documented, and deployable by anyone. Not instead of private innovation, but alongside it.

This sets up a healthy tension. Some ideas will be better suited to private development, where the profit motive drives rapid iteration and scaling. Other ideas will be better suited to open development, where the goal is broad access and the work doesn’t need to generate returns for investors. And some ideas might be developed in both tracks, with private implementations competing alongside open ones.

The point is to have a real alternative. Right now, if you discover something valuable, the default is to try to own it. A well-functioning Civilian Innovation Corp would offer another option: contribute it to the commons, with institutional support to make sure it actually gets used.

The Funding Question

Here’s the honest problem: we don’t know what funding model will sustain this kind of effort.

The challenge is structural. An institution dedicated to finding, validating, and giving away high-leverage ideas doesn’t have a natural revenue stream. We give away the output. That’s the point. But it means we can’t guarantee that value flows back to sustain the work.

Patenting is one option—develop ideas, license them, use the revenue to fund further development. But this sits uneasily with the mission. Once you’re optimizing for licensable intellectual property, you’ve changed what you’re looking for. You start favoring ideas that can be owned over ideas that are most useful. The incentives drift.

The virtual land value tax described earlier is another option, and perhaps the most elegant in principle—the value generated by the conceptual commons funds the maintenance and expansion of that commons. But as discussed, the implementation challenges are severe. Detecting algorithmic usage at scale, tagging conceptual principles, building the micropayment infrastructure—it’s technically imaginable but probably not feasible, almost certainly not politically palatable, and possibly a violation of privacy rights.

Government funding is the obvious alternative, but it comes with its own problems. Government-funded efforts are subject to political pressure. Priorities shift with administrations. There’s a tendency toward risk-aversion and bureaucratic caution. And there’s a legitimacy question: an institution designed to identify and propagate high-leverage ideas for everyone should probably not be controlled by any particular government.

Philanthropy has the issues we’ve already discussed. Philanthropic priorities reflect donor preferences, which introduces bias. The causes that appeal to wealthy individuals are not necessarily the ideas with the highest leverage for broad benefit. And dependence on philanthropic goodwill is precarious—funding can disappear when donors shift interests.

So where does that leave us?

The ideal—the aspiration—would be an institution that can sustain itself while giving away everything it produces. If we could guarantee operational sustainability, we would give away every idea, every framework, every tool, with no strings attached. That’s the goal.

But until we can guarantee sustainability, we need to be pragmatic. We need funding, and we should look for sources that are most aligned with what we’re trying to do. That might mean a mix: some earned revenue from consulting or training, some philanthropic support from donors who genuinely share the mission, some government grants for specific projects where alignment is clear. It might mean experimenting with models that don’t exist yet.

What we shouldn’t do is pretend this is solved. The funding question is open. It’s one of the hard problems. And being honest about that is better than papering over it with optimistic assumptions.

We’re not averse to making money. We’re not averse to supporting ourselves. The goal isn’t purity; it’s impact. If some revenue-generating activity helps sustain the larger mission of finding and sharing high-leverage ideas, that’s fine. The test is whether the funding source distorts the work—whether it pulls us toward ideas that benefit funders rather than ideas that benefit everyone.

That’s the question to keep asking: where are the funding sources most aligned with what we’re trying to do? And how do we structure things so that alignment is preserved as we grow?

The Question We Should Be Asking

Here’s the question that sits underneath all of this:

Who is responsible for finding, validating, cultivating, and operationalizing good ideas for broad benefit?

Right now, the answer is mostly: private industry. And private industry does this well for ideas that can be monetized. That’s valuable. But it leaves a gap—a large gap—for ideas that are high-leverage but don’t fit neatly into a business model. Foundational principles. Frameworks for collective decision-making. Tools for thinking that benefit everyone but that no one can own.

We’re going to share it anyway. That’s the nature of knowledge. Ideas spread. Principles, once understood, become part of the common inheritance. The Fourier transform didn’t stay locked in a French journal; it became infrastructure for the modern world. Compound interest didn’t remain a Babylonian secret; it became the foundation of global finance.

The question is whether we leave the discovery and development of such ideas to chance and private initiative alone—or whether we build institutions that make it a deliberate, resourced, ongoing effort.

Henry George looked at land and saw something everyone had missed: that the community’s contribution to value deserved recognition. In the 21st century, the “land” we build on is increasingly conceptual. The principles, frameworks, and algorithms that underlie modern life are a commons—and like any commons, they require stewardship.

A Civilian Innovation Corp wouldn’t just tend that commons. It would expand it. And in doing so, it would give private innovation a run for its money—not by competing with it, but by offering a genuine alternative. A place where the goal is not to capture value, but to create it and give it away.

We’re going to share the good ideas eventually. We might as well get organized about it.

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The radar chart presented here evaluates the post-growth policy toolkit through this lens of implementability. Each policy has been assessed on a scale from 1 to 5, with higher scores indicating greater potential for real-world adoption. While some policies—like direct economic downscaling—face steep political resistance despite their ecological importance, others—like green public investment and resource efficiency measures—show promising implementability. By mapping these scores across four categories of post-growth policies, we gain insight into strategic pathways for transformation that balance urgency with practicality.

This visualization serves as both diagnostic tool and strategic guide. It helps identify which policies might serve as entry points into post-growth thinking, building momentum for more challenging reforms as cultural values shift. Like the Doughnut itself, this assessment reminds us that meeting humanity's needs within planetary boundaries requires working at the intersection of the possible and the necessary—finding ways to expand what's politically feasible while respecting what's ecologically essential.

Implementability Evaluation

In the following section, we provide an initial assessment of many of the policy tools throughout the literature on degrowth and post-growth literature. We categorize the policy tools mentioned into overarching tool kits, provide a brief description, a preliminary implentability assessment, and provide a score for the tool to be rated on our radar graph.

Toolkit 1: Reducing Production & Consumption (Degrowth Agenda)

Direct Downscaling of Economic Production (2.0/5.0 - Grade D) This policy calls for deliberately reducing production in environmentally harmful sectors like fast fashion, SUVs, and industrial meat. While ecologically necessary, it receives our lowest implementability score because it directly challenges the growth paradigm and faces resistance from powerful economic interests, cultural norms around consumption, and political fear of recession-like conditions. Few politicians are willing to advocate for deliberately shrinking any economic sector.

Bold Investment in Ecological Transformation (4.0/5.0 - Grade B) This policy suite involves significant public investment in renewable energy, ecological restoration, and green infrastructure. It earns a high implementability score because it creates visible jobs, aligns with existing climate action frameworks, and focuses on building rather than restricting. The "Green New Deal" framing has gained traction across multiple countries, showing that ecological investment can win political support when tied to economic opportunity.

Tax & Fiscal Overhaul (3.0/5.0 - Grade C) This includes carbon taxes, resource extraction fees, wealth taxes, and maximum income proposals. It receives a moderate score because while tax reform is a standard policy tool, these specific proposals face resistance from wealthy interests and face significant political messaging challenges. However, growing concerns about inequality and climate change are creating new openings for discussion.

Promoting Resource Efficiency & Sufficiency (4.0/5.0 - Grade B) This encompasses right-to-repair laws, anti-planned obsolescence regulations, and design standards for durability. Its high score reflects growing consumer frustration with disposable products and bipartisan appeal—conservatives appreciate traditional values of thrift and self-reliance, while progressives support environmental benefits. The EU's emerging regulations show political viability.

Phasing Out Environmentally Harmful Subsidies (3.0/5.0 - Grade C) This means ending government support for fossil fuels, industrial agriculture, and other environmentally damaging sectors. It receives a moderate score because while the economic and environmental case is strong, these subsidies create powerful beneficiaries who resist change. However, fiscal conservatives and environmentalists can find common ground on ending these "perverse subsidies."

Urban Planning for Reduction (4.0/5.0 - Grade B) This includes transit-oriented development, walkable cities, and shared resource infrastructure. Its high implementability score reflects growing urban popularity of these approaches, which improve quality of life while reducing consumption. Many cities are already implementing such policies, providing proof of concept and political momentum.

Overall Toolkit Grade: C (3.3/5.0) The degrowth agenda faces significant challenges but contains several implementable elements when framed around investment, efficiency, and improved urban living.

Toolkit 2: Enhancing Social Well-being & Equity

Universal Basic Income or Carbon Dividends (3.0/5.0 - Grade C) These policies provide direct cash payments to citizens, either unconditionally or funded by carbon pricing. They receive a moderate implementability score because while they have intuitive appeal and successful pilots, they face resistance based on cost concerns and work ethic arguments. However, the COVID-19 stimulus payments demonstrated the feasibility of direct cash transfers at scale. (The Case for Degrowth, Decoupling Debunked)

Strengthening the Commons & Social Economy (3.0/5.0 - Grade C) This includes supporting cooperatives, community land trusts, and public facilities for collective use. It receives a moderate score because these models already exist successfully in many communities but scaling them nationally would require significant cultural and legal shifts. However, their proven benefits make them a promising avenue for building alternative economic models.

Reducing Working Hours Without Pay Loss (2.5/5.0 - Grade D+) This policy proposes shorter workweeks or workdays without reducing wages. It receives a low-moderate score because despite worker popularity, employer resistance is strong, and implementation would require significant labor market restructuring. However, successful examples in countries like Iceland show potential pathways. (The Case for Degrowth)

Robust Public Services (4.0/5.0 - Grade B) This means expanded healthcare, education, childcare, and elder care provided as public goods. Its high implementability score reflects widespread support for these services in many countries and their proven ability to improve well-being while reducing private consumption. Even in the U.S., where resistance is stronger, significant portions of the public support expanded services. (Accelerationism and De-Growth)

Overall Toolkit Grade: C (3.1/5.0) Social well-being policies show moderate implementability, with public services offering the most promising avenue for near-term progress.

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Toolkit 3: Measurement & Target Setting

Adopting the Doughnut Framework (3.5/5.0 - Grade C+) This means using the Doughnut's social-ecological boundaries as planning tools for cities, regions, and nations. It receives a moderate-high score because it's already being adopted by cities like Amsterdam and organizations like C40, proving its practical value. However, national-level adoption faces institutional inertia and resistance to rethinking economic goals. (Savini, Post Growth)

Replacing GDP with Well-being Indicators (3.0/5.0 - Grade C) This involves shifting government focus from GDP growth to measures of ecological health and human flourishing. It receives a moderate score because while theoretically sound and gaining traction in places like New Zealand, Scotland, and Iceland, it faces resistance from economic orthodoxy and financial markets that remain focused on traditional growth metrics. (Savini, Post Growth)

Overall Toolkit Grade: C+ (3.3/5.0) Measurement tools offer important symbolic and practical benefits with moderate implementation challenges.

Toolkit 4: Systemic & Governance Changes

Democratizing Control Over Technology (2.5/5.0 - Grade D+) This includes public direction of research priorities, technology assessment, and limitations on corporate power in tech development. It receives a low-moderate score because it challenges powerful corporate interests and techno-optimism narratives. However, growing concern about tech monopolies and AI risks is creating new openings for democratic oversight. (Accelerationism and De-Growth)

Participatory Governance (3.5/5.0 - Grade C+) This encompasses citizens' assemblies, participatory budgeting, and community decision-making. It receives a moderate-high score because these methods have proven successful at local levels and appeal to democratic values across the political spectrum. Scaling these approaches remains challenging but feasible with institutional support. (The Case for Degrowth)

Challenging the Ideology of Growth (2.5/5.0 - Grade D+) This means education, media, and cultural work to shift societal values away from growth fixation. It receives a low-moderate score because changing deeply held cultural values is slow and difficult. However, young people's growing concern about climate change suggests generational shifts may be occurring. (Accelerationism and De-Growth)

Overall Toolkit Grade: C- (2.8/5.0) Systemic changes face significant challenges but are foundational for long-term transformation.

Grading of Toolkits as a Whole:

Finding the Sweet Spot Through Strategic Policy Pairing

Our radar chart reveals a critical dilemma: policies currently fall into two camps—those with high implementability but limited efficacy, and those with high efficacy but limited implementability. Neither category alone will create the transformation needed to stay within planetary boundaries while ensuring social wellbeing.

The sweet spot lies not in choosing between these extremes, but in strategic pairing of complementary policies. When "building" policies (like green investment and public services) are explicitly linked with more restrictive but necessary measures (like reducing harmful production), they can create a balanced approach that's both implementable and effective.

For example, substantial investment in public transportation becomes more politically viable when paired with gradual reduction of parking spaces and car infrastructure. Robust public healthcare makes working hour reduction more feasible. Resource efficiency regulations gain traction when matched with support for community repair initiatives.

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These pairings allow the more politically palatable "building" policies to create constituencies and momentum for the more challenging but necessary "restrictive" policies. They acknowledge that implementation and efficacy must be balanced—we cannot sacrifice one for the other if we hope to achieve the post-growth vision reflected in the Doughnut framework.

The path forward requires this careful orchestration of policy combinations that can collectively occupy the sweet spot between implementability and efficacy. By designing these strategic pairings, we can move beyond the current impasse and create momentum for meaningful transformation that respects both political realities and ecological necessities.

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Thought of and written by Logan Jensen, Sudo-Intellectual Candidate

Edited and Enhanced by Claude, Artificial General Intelligence Candidate

Protecting our Public, Private, and Secret Lives

Gabriel García Márquez, who is one of my favorite authors and who had significant influence developing my magical-realist approach to policy, once wrote, "Every man has three lives: a public life, a private life, and a secret life." Regarding the privacy of our data and our control over how private and public actors use it, we seem to have mixed all three lives and come away with nothing at all. Frameworks like GDPR stifle the use of private data in Europe, ostensibly to protect our private and secret lives, while in reality creating road blocks to making productive use of it. On the Other Hand, the Data Wild West permits data exploitation by private and public actors in the US and across the globe with relatively little scrutiny. With the level of privacy we already cede to use essential digital services, there are very few secrets that aren’t already known or at least predicted by someone somewhere as soon as someone thinks them up.

What if the next evolution in privacy didn't come from building higher and thicker walls around our data but from flipping the script on privacy entirely and focusing how to design the channels our data flows through and which lakes store it? In an age where the Patriot Act enables distinctly unpatriotic invasions of our digital lives, I propose the intentionally ironic Pseudo-Dissident Act as a framework for privacy protection and data utilization. The pseudo-governmental agency this act creates wouldn't merely resist invasive surveillance with privacy protection backstopped by the Fourth Amendment protection against searches and seizures, but transform our privacy paradigm by basing it on the consent-backed protection against quartering soldiers found in the nearly defunct Third Amendment.

Rather than biasing toward complete protection like GDPR or maximum personal data exploitation like the US, this framework would provide a third way of protecting privacy by flipping the script on what privacy and data protection are. This new script would, allow more overt and approved personal and private data access while ensuring transparency and control over personal data sharing preferences in a way that citizens benefit from its consensual utilization through mutually beneficial, consensual, and transparent process.

A Cautionary Tale About Privacy in George Orwell's 1984

In Orwell's 1984, privacy invasion is the backbone of totalitarian control. Winston Smith's world is defined by constant surveillance through telescreens, facial monitoring for "facecrime," and the weaponization of intimate personal information. His attempt to create privacy by writing in a diary is considered thoughtcrime. At the same time, his false sanctuary with Julia is revealed as a trap when a hidden telescreen exposes their rebellion. Perhaps most chilling is how the Party uses data against their citizens. Winston's neighbor is reported by his seven-year-old daughter for sleep-talking against Big Brother while Winston receives personalized torture based on surveillance data, using Winston's specific fear of rats against him in Room 101.

These fictional horrors parallel today's digital privacy debates with unsettling clarity. Just as the Party collected intimate knowledge to control Winston, modern data harvesters often gather our preferences, habits, and fears without receiving meaningful consent. This "false sanctuary" mirrors our illusion of private digital spaces that are constantly monitored. While we don't have children reporting parents to authorities, we have devices in our homes listening for keywords and algorithms analyzing our communications. The key difference is that in our world, this surveillance is primarily conducted by corporations rather than governments, although the line increasingly blurs as data is shared across sectors. Unlike Winston, we still have the opportunity to shape how our data is used, but only if we recognize the parallels before our digital panopticon becomes complete.

The Pseudo-Dissident Act: Constitutional Foundations for Digital Privacy

The "Pseudo-Dissident Act" is deliberately provocative in its naming, transforming the irony of the Patriot Act's unpatriotic surveillance into a framework that genuinely empowers citizens to own and control their data. This Act affirms a fundamental principle: individuals own the data they generate and should control its use on their terms. Unlike current regulations that either restrict data use (GDPR) or permit unchecked exploitation (US practices), the Dissident Act creates a legal basis for data "invaluation" – converting personal data from an exploited resource into a valuable asset under its owner’s control.

America's current privacy paradigm relies primarily on Fourth Amendment protections against "unreasonable searches and seizures," but this framework has proven inadequate in the digital age. Courts struggle to apply concepts like "reasonable expectation of privacy" to information shared with third parties, creating a constitutional blind spot that enables mass surveillance without meaningful consent. The stewards of our data have it, but promise not to use it without either a secret warrant from a secret court or a secret client willing to pay a secret price.

The Third Amendment—prohibiting the quartering of soldiers in private homes without owner consent—offers a surprisingly relevant alternative. Though rarely invoked, its core principle is powerful: The government cannot occupy private space without explicit permission. Applied to digital contexts, The Third Amendment’s "consent-first" approach recognizes personal data as an extension of the private domain and can only be be bought and sold according to the owner’s express consent. While no individual piece of data seems valuable enough, the total market for data is estimated at around $500 Billion, with very little of that ever making it back to the rightful owner of the brokered data.

The Pseudo-National Sensorship Agency (pNSA) would serve as the mechanism for implementing this vision, functioning as a the people’s data broker that connects the people's data with opportunities that benefit them. "Sensorship" plays on "censorship" but in this context means quite the opposite. Censorship is sensing, by whatever means, when your data has value and helping you capitalize on it. Through a single comprehensive preference interface, citizens could set their data-sharing parameters once instead of navigating endless website permissions and make a few tenths or hundreths of a percent every time their data is accessed. When a valuable opportunity arises outside of their allowed preferences– perhaps a medical researcher needs genetic information from people with specific characteristics – the pNSA would either automatically facilitate the exchange based on pre-established permissions or notify the user with options like: "Researcher offers $75 plus study results for your anonymized genetic markers. Accept/Decline/Negotiate?" to present a an opportunity to allow an exception with the details of who wants the data and why presented clearly and openly.

This isn't a radical departure from constitutional principles but their logical extension into the digital realm. By framing data access as a form of "digital quartering" requiring explicit permission and fair compensation, the Act creates a coherent legal basis for protecting personal information while enabling its valuable use. While it may be weird to imagine 18th century soldiers entering your quarters and eating all your data, the principal of stopping modern data brokers from doing so is at least holds prima facie. The framework creates a transparent, balanced ecosystem where data flows based on mutual value creation rather than extraction and recognizes that our founding document's protections must evolve to preserve liberty in contexts the Framers could never have imagined but would undoubtedly have sought to protect.

Proof of Concept in Estonia’s E-Government Framework

Estonia's journey toward digital governance emerged from necessity rather than luxury. Following a massive 2007 Russian cyberattack that crippled banks, media outlets, and government services, Estonia transformed crisis into opportunity by building a digital infrastructure designed for resilience, transparency, and citizen control. Today, this Baltic nation of just 1.3 million people offers a working proof-of-concept for robust digital citizenship that balances security with usability and privacy with functionality.

The lynchpin of Estonia's system is X-Road, a decentralized data exchange layer that enables secure communication between different information systems. Unlike traditional approaches that consolidate information in vulnerable central repositories, X-Road connects disparate databases while keeping data at its source. When a doctor needs medical records or a tax official requires income verification, they access this information directly through authenticated channels rather than duplicate databases. Every instance of data access is logged and visible to citizens in a way that creates accountability through transparency. This architecture demonstrates that efficient government services don't require either surrendering privacy or or centralizing control.

Estonia's digital identity system starkly contrasts America's fragmented approach. While U.S. citizens navigate a patchwork of state IDs and repurposed Social Security numbers (with Real ID adding complex e-epicycles rather than coherence), Estonians possess a unified digital identity with robust security features. Their ID cards contain encrypted certificates enabling legally binding digital signatures, secure authentication, and transparent access logs. This foundation of trust allows Estonians to vote online, bank securely, sign contracts digitally, and access medical services seamlessly—all while maintaining visibility into who accesses their information and why.

Perhaps Estonia's most transformative innovation is its "once-only" principle, which fundamentally reimagines the citizen-government relationship. Rather than requiring individuals to repeatedly provide the same information across agencies (with all the attendant inefficiency and error potential), Estonian citizens provide information once, which is then shared across systems with explicit consent. When registering a business, for example, an entrepreneur's information automatically populates forms across tax authorities, business registries, and social security systems—dramatically reducing bureaucratic friction while maintaining consent and transparency.

Estonia didn’t build its system by ignoring privacy concerns but by addressing them directly through architectural choices. By designing for transparency, consent, and citizen control, Estonia achieved what many consider impossible: a digital government infrastructure that citizens trust. Their success challenges the false dichotomy between efficient governance and privacy protection, proving that adequately designed systems can enhance both simultaneously. This working model provides the foundation for extending these principles beyond government services into a broader framework for consensual data sharing. This framework could inform the development of a citizen-centric data agency that serves rather than surveils.

The pNSA: A Citizen-Owned Data Sovereignty Framework

The Pseudo-National Sensorship Agency would represent a fundamental shift in managing personal data founded on the Third Amendment principle of consent. Just as the Third Amendment prevents the government from quartering soldiers in private homes without owner consent, the pNSA would avoid exploitation of personal data without explicit permission and compensation. Unlike government agencies (which lack public trust currently) and private companies (which have inherent profit conflicts), the pNSA would use a public benefit corporation structure with the citizens that have opted in using the data governance framwork as its owners. This ownership structure ensures that profits generated from data exchanges flow back to the data creators after covering operational costs.

Adapting Estonia's successful X-Road architecture, the pNSA would function as a consent-based data exchange platform rather than a centralized data repository. Personal information would remain stored at its sources, with the pNSA providing secure, authenticated access channels only when authorized by the data owner. Every query would be logged, visible to the citizen, and governed by their pre-established consent parameters. Citizens could set default sharing preferences, minimum compensation requirements, and purpose limitations through a single comprehensive dashboard – eliminating the need to manage hundreds of different privacy policies across services. Or even, if they want to be less involved in the decision making sequence, set a privacy slider on the continuum from locked in a privacy vault to producing value openly.

Operationally, the pNSA would function as both guardian and broker. When an organization seeks specific data, whether it’s a researcher seeking health information, a company wanting consumer insights, or a government agency needing verification – they submit a request specifying the data sought, intended use, compensation offered, and usage limitations. The pNSA would match these requests against citizen preferences, facilitating automatic exchanges when pre-authorized or sending notification requests when manual approval is needed. For example: "City Planning Department requests anonymized location data to optimize bus routes. Compensation: $15 + early access to improved schedules. Accept/Decline/Negotiate?" This system transforms data from an exploited resource into a fairly valued asset, creating a sustainable ecosystem that benefits all participants while maintaining individual sovereignty over personal information.

Implementation Road Map: A Phased Approach to Data Sovereignty

The Pseudo-National Sensorship Agency wouldn't emerge overnight as a fully-formed entity—its development would follow a careful, iterative process designed to build trust while demonstrating value. Initially, a state-level pilot program in a privacy-forward jurisdiction like California would establish proof-of-concept. Leveraging California's existing Data Privacy Rights Act as a foundation, this limited trial would recruit diverse volunteers to test core functionality with real-world data while carefully measuring outcomes and identifying operational challenges.

Trust-building would be central to implementation, with safeguards baked into the system architecture rather than added as afterthoughts. An independent oversight board with binding authority, mandatory third-party audits, absolute data deletion rights, and state-of-the-art encryption would provide foundational protections. Equally important would be transparent incentive structures—clearly showing how value flows back to data creators through multiple compensation options, establishing minimum value guidelines for different data types, and implementing independent dispute resolution processes.

As the pilot results demonstrate both privacy protection and tangible benefits, the model could expand through an opt-in approach that allows growth proportional to proven value. This bootstrapped scaling strategy lets the system evolve organically based on actual user experiences rather than theoretical promises. Throughout this process, robust public education would showcase concrete success stories, provide transparent performance metrics, and explain the comparative advantages over exploitative models. This educational interaction would help citizens understand how the system works and why it represents a fundamental improvement in valuing and protecting personal information.

Legally, there are virtually no barriers to setting up a data brokerage owned by its members and operated for the public benefit. I could start one tomorrow if I wanted to. The problem is reaching scale and while traditional data brokers provide the data they have at the lowest price, we would be unlikely to match the price, maintain data-owner control, and return profits to the owners.

To make a new data brokerage that cuts the data owners in on the value produced by their data, we would likely need to bring legal challenges to data brokers that cannot, under the Third Ammendment, demonstrate that the data they have was collected under informed consent. If these challenges are successful and turn our wacky idea into precedent, the Pseudo-National Sensorship Agency would be best positioned to thrive in the new legal environment. If it fails, the publicity will allow for increased gradual adoption as publish which services sign up for our mutually beneficial and consent based data access with us.

Stepping into a Sudo-Intellectual's 1985

Let us imagine 1985, the mirror image of 1984, where the Ministry of Sensorship surveils Winston, stewards his data footprint, follows him (on social media), and interacts with him about his data-sharing preferences. All while Winston profits from the data those activities generate. In this world, Winston has opted for maximum transparency and maximum benefit (both efficiency and monetary) from his data.

This access to data enables "Little Brother" (a distributed network of peers rather than Big Brother's centralized eye) to identify Winston's unique skillset as a nuclear non-proliferation expert, compensate him through the Ministry of Sensorship for valuable data and reporting he produces, and connect him with like-minded supporters of a denuclearized world. Eventually, during a period of escalating nuclear tensions where the President's cabinet is at a loss for what to do, they reach out to the Ministry of Sensorship to request a query for a leading nuclear non-proliferation expert to weigh in on the situation.

The query returns Winston's name, and the cabinet official put in a bid for $100,000 for his immediate attention and continued assistance with the crisis. Winston then gets an emergency notification on his phone with a button to immediately call an aide who patches him into the cabinet meeting. He gives an initial unclassified assessment of the situation on the way to the chopper landing zone that will take him to room 010, where he'll work under extreme conditions to make the contribution of a lifetime to society as the expert in avoiding nuclear war and for which he receives a handsome reward. Rather than being broken by torture Room 101, Winston finds the culmination of his life purpose in Room 010, where sensorship experts rapidly plugged him into something bigger than himself enabled by being open with information rather than keeping it locked down in a steel safe.

Is this utopian thinking? 100%. But it's no more dystopian than our current reality where data brokerages and corporations harvest our most intimate data without meaningful consent or compensation. We live in a world where surveillance is just as complete and all encompassing as Winston’s Oceania, but it’s conducted by corporations who face even less accountability than governments. Is this more appropriate as a movie script than a real-life interaction? Absolutely, but the principle of needing to find a better model, whether the one we propose or not, for handling data privacy in the digital age. If the government can make a privacy expectation to stop a bad guy, under what conditions should we allow it to make an exception for good.

Just What Exactly Am I Dreaming up Here?

The technology to implement this vision already exists. Estonia's digital governance system demonstrates that government-led data stewardship can be effective when built on trust and citizen control. However, given the low trust in government and technology companies in the US in the United States, we are likely not in a place to implement a national system of a similar scale as Estonia. However, building out a small pilot program and scaling over time is absolutely possible.

The powers and structures currently deployed to combat "evil" through the Patriot Act could easily be leveraged to produce good if the government wanted to and the people trusted them. Big ifs, I know. Something like the pNSA could repurpose national surveillance architecture to enable coincidental connections that create value for everyone if we build a system that creates and maintains high trust between its users, itself, and its clients. The systems that now track us could become systems that match us with people with similar interests, projects, and aspirations if only we can flip the lever of power from stopping bad to doing good.

The Privacy-Niks aren't wrong to be cautious since history gives them plenty of reasons. However, focusing solely on building higher and thicker walls may lead to missing the opportunity to build better bridges that connect and employ our data for good. The Pseudo-Dissident offers a third path: neither naive trust nor paranoid isolation, but rather a framework for negotiated, compensated, and purposeful data sharing that respects individual autonomy while enabling collective benefits.

While this whole-of-society approach to complex problem solving is ambitious and likely cannot be carried out logistically by any private entity or trusted by any government entity, its usefulness is so massive that creating it as a quasi-institution of a pseudo-state is worth dreaming about, at the very least. The only thing standing in the way is a little pure imagination and a lot of learning to trust and verify.

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Point of Contact

I hope you'll send me your criticism, feedback, and suggestions to either refine this idea or point me to a more fruitful area for addressing the root causes of our data privacy conundrum. As a sudo-intellectual, I certainly don't have the expertise to make the best and most comprehensive plan for something like this, but I can come up with radically new ideas that have at least some basis in reality. As Brené Brown says, "Vulnerability is the birthplace of innovation, creativity, and change." It's up to you whether or not to build on the vulnerabilities inherent to our system. Let me know if you decide to build on it, and I’ll gladly incorporate your feedback.

Logan Jensen
sudo.intellectual.01@gmail.com
‪(909) 913-4589‬

A Sudo-Intellectual Production