INTRODUCTION

Several years ago, I began developing an idea that would eventually lead to me writing a short essay on the idea of a Bifurcated Economy. At the time, the core argument was straightforward…modern societies are headed toward a two-circuit economic structure. One circuit is driven by markets and profit, while the other is driven by civic participation and public goods. The first is measured and optimized by GDP, wages, capital flows, etc. The second is unpriced, invisible, and is continuously undervalued by traditional economic metrics. That essay was more of a conceptual map than a deep exploration with narrative potential.  It was a way of naming something that was already happening but lacked the language and visibility.

While transforming collective action through decentralized coordination or slowly eroding the functions of government through the use of dPAN’s is a compelling enough narrative, these transformations are supplemental to the broader and more significant transformation posited by the idea of a public-sector economy.    

Since writing it, I’ve witnessed a broader context begin to take shape around this idea. Artificial intelligence has evolved from a speculative technology to a destabilizing macroeconomic force. It was very difficult for me to grasp completely at the time.  

But now, robotics continues to eat into physical labor markets. Even knowledge work, which for decades was considered immune to automation, now faces steady encroachment from generative models that are capable of satisfying many service functions at negligible marginal cost. 

All of this challenges the wage labor paradigm that has structured modern life since the Industrial Revolution. 

At the same time, attempts to imagine the post-work economy often center around Universal Basic Income or some techno-optimistic retraining pipeline without grappling with the psychological and civic dimensions of human purpose.

This series, When Work Ends, is an attempt to delve deeper on the diagnosis, the underlying mechanics, ethical architecture, and institutional implications of a world in which civic-labor becomes legible and economically recognized. I believe that a currency backed by civic-labor is not only feasible, but necessary. We don’t need alternative currencies for ideological reasons, but we do need new economic instruments that are capable of facilitating how society may actually function when wage labor becomes scarce and insufficiently distributed.

These writings are not an argument against markets or capital. They are an argument that societies produce value in more ways than markets can account for, and that ignoring the civic dimension of value becomes dangerous in an age of automation. What follows is an exploration of why the wage economy is unraveling, why existing policy responses are incomplete, why the value generated through civic-labor is both real and quantifiable, and how a currency backed by civic-labor can serve as a stabilizing mechanism in a post-AI world. 

In order to properly understand why I believe the concept of a currency backed by civic-labor matters, we need to start with the institution it threatens to supplement in wage labor. For more than a century, the wage system has served as the core distribution mechanism for both value and purpose in industrial societies. Individuals sell their labor to firms in exchange for wages, and those wages allow them to purchase goods, pay rent, raise children, and participate in a social world. Since the late 19th century, wage labor became so ubiquitous that it formed the basis of our statistical and moral frameworks. Employment statistics became proxies for economic health. Unemployment became a political emergency. GDP became the benchmark for national progress. The entire architecture assumed that most adults would be continuously employed for most of their lives.

The wage system did not emerge spontaneously. It emerged together with industrial capitalism and mass production. Factories needed vast numbers of workers. Workers needed money to purchase food and shelter in cities where they no longer grew their own crops. This mutual dependency created a virtuous cycle where firms needed workers, workers needed wages, and states needed both to maintain their political legitimacy. Because of this, wage labor served as the mediating device between market economies and civic life. The social contract implicitly stated that if you work, you eat, and if you work diligently, you could even ascend socially.

And the wage system did more than just distribute income, it actually integrated individuals into civic life. Workplaces were where people learned norms, formed social ties, encountered diversity, joined unions, etc. Employers withheld taxes which then funded public goods. Unions mediated conflicts and built a political consciousness. 

Professional identities connected individuals to all types of interpersonal associations. Through these pathways, wage labor served as part of our civic infrastructure that linked private effort to some sort of abstract public consequence. In addition to receiving a paycheck, we all occupy some type of recognized position within the civic fabric of society that holds both responsibilities and expectations.

This type of civic integration creates a powerful form of legitimacy. A society built around wage labor allowed us to distinguish between those who “contribute” and those who do not, and from there, we began shaping moral narratives about deservingness and what it means to be a citizen. Participation in the labor market is a proxy for participation in society. The wage functioned as both economic proof of work done and civic proof of worthiness. 

Even political participation was heavily mediated by employment. Unemployed individuals vote less and experience higher levels of social isolation. The wage system doubled as a participation gate where economic inclusion enabled civic inclusion.  It is our bridge into a civic life.  

There are several structural shifts that began eroding this contract long before AI models appeared on the scene. Globalization shifted manufacturing to countries with cheaper labor pools, hollowing out industrial employment in most developed economies. Software automated clerical and routine office work. The financial sector expanded dramatically, concentrating wealth in capital assets rather than labor income. Economists often mark the late 1970s as the beginning of the divergence between productivity growth and wage growth. Yet even these trends did not fundamentally threaten the idea that humans produce value through work.

Artificial intelligence does.

To understand why the wage system now faces a systemic crisis rather than a cyclical one, we need to examine how artificial intelligence and robotics differ from previous waves of mechanization. There is a common argument that technological disruption is simply part of capitalism’s natural evolution. In this telling, every major economic shift destroys old jobs while creating new ones, and societies eventually adjust. 

The transition from horses to automobiles displaced blacksmiths, saddle makers, and carriage drivers, but created mechanics, auto workers, truckers, etc. The shift from agriculture to industry displaced millions of farmers, but created vast industrial workforces. The rise of computers eliminated typists and filing clerks, but created IT professionals and software developers. This narrative often concludes with a reassuring mantra that “technology always creates more jobs than it destroys,” and therefore the future of work will somehow sort itself out.

But this interpretation confuses pattern recognition with inevitability. It assumes that because something happened several times in the past, it must happen again in the future, without interrogating the underlying conditions that made those adjustments possible. The key enabling condition of past transitions was that humans remained more productive than machines at some important category of labor. 

When tractors displaced farmers, humans remained essential for industrial labor. When assembly lines displaced muscle, humans remained essential for office work, customer service, logistics, and coordination. When software eliminated clerical tasks, humans remained essential for complex problem-solving, judgment, creativity, and interpersonal mediation. At every stage, labor markets reabsorbed displaced workers because there were still domains where human labor had a comparative advantage.

Artificial intelligence challenges that advantage at its root. Machine learning models are not just labor saving devices, but competence extracting systems. They learn from a massive corpus of human-generated data, internalized patterns, and then replicate outputs at scale. A single generative model can write marketing copy, draft legal briefs, summarize research papers, analyze financial statements, respond to customer service inquiries, and produce code. Robotics adds a physical dimension, automating warehouse fulfillment, surgical assistance, agricultural harvesting, and industrial assembly. When cognitive automation layers on top of physical automation, the scope of human labor that remains both necessary and economically valuable begins to shrink.

This shift does not mean that humans will stop working altogether, but instead, implies that the structure of work will change in ways that the wage system is poorly suited to absorb. There are several key discontinuities worth examining between AI and past transitions.

The first discontinuity is speed. Previous technological transitions unfolded over decades, giving institutions time to adapt. AI diffusion can occur in months, rather than decades. A chatbot implemented in a customer support pipeline instantly displaces dozens or hundreds of agents. A document processing model integrated into a law firm’s workflow instantly displaces paralegal hours. A code generation model embedded in developer tools instantly displaces programmer time. When technological substitution occurs at that pace, retraining and reskilling become reactive rather than proactive, and labor markets cannot adapt smoothly.

The second discontinuity is scope. AI automates tasks across many different occupations simultaneously. This is unprecedented. The mechanization of agriculture did not eliminate jobs in finance, law, business, or healthcare. The computer revolution elevated knowledge work even as it eliminated clerical work. AI, by contrast, touches every vertical from legal analysis to medical imaging to graphic design to elementary education. That breadth matters because labor markets depend on possessing a diversity of absorptive capacity. If automation hits one sector, displaced workers can migrate to others. If automation hits many sectors at once, migration pathways narrow.

The third discontinuity is task decomposition. AI does not eliminate entire jobs at once, but strips away tasks within jobs, leaving fragmented remnants of work behind. A software engineer might still be employed, but they now spend less time writing boilerplate code and more time integrating machine outputs. A financial analyst might still work, but now spends less time building spreadsheets and more time interpreting summaries. The result is a slow erosion of hours, and not a sudden elimination of roles. This creates a structural underemployment problem where people stay employed but earn fewer hours, earn less income, and will probably engage in less meaningful work.

The fourth discontinuity is substitutability.  In earlier eras, technology often complemented human labor, making workers more productive and increasing demand for their skills. AI increasingly substitutes for human labor outright. For example, when generative models reduce the need for copywriters, the value of copywriting skills declines, and there is no complementary surge in demand elsewhere. When large language models can draft legal memos, they do not make junior associates more valuable…they make them less essential. This dynamic weakens the wage system’s core promise that productivity leads to income.

If we zoom out, a clearer picture begins to emerge in labor markets. The issue is not mass unemployment in the classical sense, but mismatched agency. People will still want to contribute, but the formal economy will not be able to compensate for that contribution with livable wages for everyone. We have slowly started to ask ourselves, “what will jobs become, or how will we survive if there are no jobs?”. But every time I hear someone pontificate endlessly on the immediate perils of the labor market due to technology, I’m met with crickets when it comes to a discussion of what we should do next.

In response to these questions, most policymakers and representatives frequently invoke retraining pipelines, STEM education, and entrepreneurial incentives. These are valid efforts but insufficient for many structural reasons. Retraining assumes there will be enough new labor categories to absorb displaced workers. STEM pipelines assume cognitive labor will remain scarce. Entrepreneurial incentives assume individuals will self-create value in competitive markets. All three assume the wage economy will remain dominant. None of these assumptions is guaranteed.

Alongside these proposals sits the more radical idea of Universal Basic Income. UBI has become the most widely recognized policy response to the prospect of widespread automation. The structure of the argument is elegant in its simplicity: if machines generate unprecedented economic abundance but require fewer workers to operate, then society can decouple survival from employment by providing every individual with a guaranteed income floor. This would ensure that no one falls through the cracks as wage labor becomes less accessible. UBI advocates often cite the possibility of a “post-scarcity” economy in which human creativity, curiosity, and self-directed learning replace toil and drudgery.

And at first glance, UBI seems almost tailor-made for the crisis of automation. If the problem is that people may no longer be employable in sufficient numbers, then providing unconditional income appears to solve the economic side of the problem. Pilot programs have demonstrated positive outcomes. Finland’s experiment showed improvements in mental health, stress reduction, and life satisfaction, even though employment effects remained moderate. Kenya’s income trials demonstrated improvements in nutrition, housing stabilization, and household savings. Stockton, California’s experiment found that recipients experienced less income volatility and greater psychological well-being. These are not trivial results. Economic insecurity creates cognitive load, chronic stress, and intergenerational trauma. Any policy that mitigates these effects deserves serious attention.

However, the UBI discourse often jumps from these positive findings to the conclusion that UBI is THE solution to the end of work. This is where the mirage begins. UBI is a powerful tool for stabilizing consumption, but it does not address the deeper issue around the erosion of economic identity and social participation. Humans are not only consumers who need money to survive, but contributors to a society who need recognition, agency, and some sense of belonging. UBI solves for the former while leaving the latter unaddressed.

To validate this, consider the structure of contemporary welfare states. Unemployment insurance, disability support, retirement pensions, childcare subsidies, food assistance, and housing vouchers all exist to ensure survival and mitigate poverty. They are essential, but they do not constitute participation in society.

No one derives identity from being a welfare recipient. To build a life around receiving money rather than contributing to a shared purpose is not inherently dignifying. The political rhetoric surrounding welfare illustrates this clearly. Welfare is framed as charity and dependency, and not contribution and participation. UBI removes the stigma by making everyone a recipient, but it does not change the fundamental dynamic that money without contribution is survival, not belonging.

The UBI model also assumes that money is the bottleneck in the post-automation economy. This is only partially true. Money is a bottleneck in the current system because survival is tied to wages, and wages are tied to jobs. Remove jobs, and money becomes scarce. UBI fixes that.

But in a fully automated economy, money may become abundant. What becomes scarce instead is meaningful work, structured participation, and visible contribution. A society can have infinite goods at zero marginal cost and still suffer catastrophic social decay if its citizens lack purpose.

Another limitation of UBI emerges when considering fiscal and political feasibility. A universal income set high enough to sustain dignified living would require significant taxation, political consensus, and administrative competence. In a world where electoral politics is polarized and fiscal conservatives dominate budgetary discourse, the odds of a robust national UBI passing and persisting are extremely low.

In addition to the financial constraints, welfare programs are politically fragile because they can be retrenched or defunded by future governments. UBI is not inherently immune to these dynamics. It may begin as universal and unconditional but devolve into conditionality or austerity during fiscal crises.

Even if we wish away the political obstacles, UBI remains conceptually incomplete. It treats citizens as consumers rather than co-creators of society. To their credit, UBI advocates often argue that removing the compulsion to work will free people to pursue creative or civic projects. 

In other words, they assume that once survival is guaranteed, people will naturally gravitate toward contribution. This is optimistic anthropology. While some individuals might start community gardens or form artist collectives, many will not. Not because they are lazy or unmotivated, but because human beings require structure, norms, and incentives to convert intention into behavior. If we believe people will spontaneously devote themselves to civic improvement once freed from wage labor, we are confusing possibility with probability.

The deeper flaw in the UBI framework is that it asks the wrong question. UBI asks, “How do we ensure people can consume without employment?”. The correct question in a post-automation society is, “How do we ensure people can contribute without employment?”. Because consumption without contribution may satisfy basic needs, but it will not satisfy the human need for agency, identity, status, and belonging.

Status in industrial societies has always been tied directly to occupation. We always ask children what they want to “be,” and their answer is always some awesome profession. When adults meet for the first time, they ask, “So what do you do?”.  This language reveals how deeply our culture ties identity to wage labor. If wage labor disappears, the identity infrastructure collapses, and UBI does not rebuild it.

None of this is to say that UBI is useless. On the contrary, I suspect that UBI or UBI-like policies will be necessary components of a post-work welfare architecture. But UBI cannot be the architecture itself. It can ensure survival but it cannot ensure meaning. 

If we want a future in which automation enhances human flourishing rather than eroding it, we need to move beyond the paradigm of distribution and begin designing systems of recognition. We need institutions capable of recognizing and compensating the forms of labor that markets cannot price. But what is that labor?

I think the answer exists in the vast domain of civic-labor that sustains our communities but falls outside of traditional economic metrics. I look at this as a “value blind spot” in modern capitalism, and to explore its potential, we should reexamine the underlying assumptions for what counts as work, who counts as a worker, and how we can begin to quantify the value of this work? 

All of this matters for a simple reason. If wage labor collapses, the system that distributed collective purpose will collapse with it. The wage was never just about getting paid, but society’s way of living a collective life. Automation threatens that mechanism by eliminating jobs and hollowing out the categories of labor that wages were designed to reward. 

When the market can no longer reliably assign value to human effort, we should look elsewhere. Civic-labor is the most obvious and overlooked candidate because it has always been present and fundamentally resistant to automation. The unraveling of wage based value will force us to confront a domain of value that industrial capitalism has continuously failed to recognize as legitimate. 

Chapter 2 - Revealing Civic-Labor

INTRODUCTION

Several years ago, I began developing an idea that would eventually lead to me writing a short essay on the idea of a Bifurcated Economy. At the time, the core argument was straightforward…modern societies are headed toward a two-circuit economic structure. One circuit is driven by markets and profit, while the other is driven by civic participation and public goods. The first is measured and optimized by GDP, wages, capital flows, etc. The second is unpriced, invisible, and is continuously undervalued by traditional economic metrics. That essay was more of a conceptual map than a deep exploration with narrative potential.  It was a way of naming something that was already happening but lacked the language and visibility.

While transforming collective action through decentralized coordination or slowly eroding the functions of government through the use of dPAN’s is a compelling enough narrative, these transformations are supplemental to the broader and more significant transformation posited by the idea of a public-sector economy.    

Since writing it, I’ve witnessed a broader context begin to take shape around this idea. Artificial intelligence has evolved from a speculative technology to a destabilizing macroeconomic force. It was very difficult for me to grasp completely at the time.  

But now, robotics continues to eat into physical labor markets. Even knowledge work, which for decades was considered immune to automation, now faces steady encroachment from generative models that are capable of satisfying many service functions at negligible marginal cost. 

All of this challenges the wage labor paradigm that has structured modern life since the Industrial Revolution. 

At the same time, attempts to imagine the post-work economy often center around Universal Basic Income or some techno-optimistic retraining pipeline without grappling with the psychological and civic dimensions of human purpose.

This series, When Work Ends, is an attempt to delve deeper on the diagnosis, the underlying mechanics, ethical architecture, and institutional implications of a world in which civic-labor becomes legible and economically recognized. I believe that a currency backed by civic-labor is not only feasible, but necessary. We don’t need alternative currencies for ideological reasons, but we do need new economic instruments that are capable of facilitating how society may actually function when wage labor becomes scarce and insufficiently distributed.

These writings are not an argument against markets or capital. They are an argument that societies produce value in more ways than markets can account for, and that ignoring the civic dimension of value becomes dangerous in an age of automation. What follows is an exploration of why the wage economy is unraveling, why existing policy responses are incomplete, why the value generated through civic-labor is both real and quantifiable, and how a currency backed by civic-labor can serve as a stabilizing mechanism in a post-AI world. 

In order to properly understand why I believe the concept of a currency backed by civic-labor matters, we need to start with the institution it threatens to supplement in wage labor. For more than a century, the wage system has served as the core distribution mechanism for both value and purpose in industrial societies. Individuals sell their labor to firms in exchange for wages, and those wages allow them to purchase goods, pay rent, raise children, and participate in a social world. Since the late 19th century, wage labor became so ubiquitous that it formed the basis of our statistical and moral frameworks. Employment statistics became proxies for economic health. Unemployment became a political emergency. GDP became the benchmark for national progress. The entire architecture assumed that most adults would be continuously employed for most of their lives.

The wage system did not emerge spontaneously. It emerged together with industrial capitalism and mass production. Factories needed vast numbers of workers. Workers needed money to purchase food and shelter in cities where they no longer grew their own crops. This mutual dependency created a virtuous cycle where firms needed workers, workers needed wages, and states needed both to maintain their political legitimacy. Because of this, wage labor served as the mediating device between market economies and civic life. The social contract implicitly stated that if you work, you eat, and if you work diligently, you could even ascend socially.

And the wage system did more than just distribute income, it actually integrated individuals into civic life. Workplaces were where people learned norms, formed social ties, encountered diversity, joined unions, etc. Employers withheld taxes which then funded public goods. Unions mediated conflicts and built a political consciousness. 

Professional identities connected individuals to all types of interpersonal associations. Through these pathways, wage labor served as part of our civic infrastructure that linked private effort to some sort of abstract public consequence. In addition to receiving a paycheck, we all occupy some type of recognized position within the civic fabric of society that holds both responsibilities and expectations.

This type of civic integration creates a powerful form of legitimacy. A society built around wage labor allowed us to distinguish between those who “contribute” and those who do not, and from there, we began shaping moral narratives about deservingness and what it means to be a citizen. Participation in the labor market is a proxy for participation in society. The wage functioned as both economic proof of work done and civic proof of worthiness. 

Even political participation was heavily mediated by employment. Unemployed individuals vote less and experience higher levels of social isolation. The wage system doubled as a participation gate where economic inclusion enabled civic inclusion.  It is our bridge into a civic life.  

There are several structural shifts that began eroding this contract long before AI models appeared on the scene. Globalization shifted manufacturing to countries with cheaper labor pools, hollowing out industrial employment in most developed economies. Software automated clerical and routine office work. The financial sector expanded dramatically, concentrating wealth in capital assets rather than labor income. Economists often mark the late 1970s as the beginning of the divergence between productivity growth and wage growth. Yet even these trends did not fundamentally threaten the idea that humans produce value through work.

Artificial intelligence does.

To understand why the wage system now faces a systemic crisis rather than a cyclical one, we need to examine how artificial intelligence and robotics differ from previous waves of mechanization. There is a common argument that technological disruption is simply part of capitalism’s natural evolution. In this telling, every major economic shift destroys old jobs while creating new ones, and societies eventually adjust. 

The transition from horses to automobiles displaced blacksmiths, saddle makers, and carriage drivers, but created mechanics, auto workers, truckers, etc. The shift from agriculture to industry displaced millions of farmers, but created vast industrial workforces. The rise of computers eliminated typists and filing clerks, but created IT professionals and software developers. This narrative often concludes with a reassuring mantra that “technology always creates more jobs than it destroys,” and therefore the future of work will somehow sort itself out.

But this interpretation confuses pattern recognition with inevitability. It assumes that because something happened several times in the past, it must happen again in the future, without interrogating the underlying conditions that made those adjustments possible. The key enabling condition of past transitions was that humans remained more productive than machines at some important category of labor. 

When tractors displaced farmers, humans remained essential for industrial labor. When assembly lines displaced muscle, humans remained essential for office work, customer service, logistics, and coordination. When software eliminated clerical tasks, humans remained essential for complex problem-solving, judgment, creativity, and interpersonal mediation. At every stage, labor markets reabsorbed displaced workers because there were still domains where human labor had a comparative advantage.

Artificial intelligence challenges that advantage at its root. Machine learning models are not just labor saving devices, but competence extracting systems. They learn from a massive corpus of human-generated data, internalized patterns, and then replicate outputs at scale. A single generative model can write marketing copy, draft legal briefs, summarize research papers, analyze financial statements, respond to customer service inquiries, and produce code. Robotics adds a physical dimension, automating warehouse fulfillment, surgical assistance, agricultural harvesting, and industrial assembly. When cognitive automation layers on top of physical automation, the scope of human labor that remains both necessary and economically valuable begins to shrink.

This shift does not mean that humans will stop working altogether, but instead, implies that the structure of work will change in ways that the wage system is poorly suited to absorb. There are several key discontinuities worth examining between AI and past transitions.

The first discontinuity is speed. Previous technological transitions unfolded over decades, giving institutions time to adapt. AI diffusion can occur in months, rather than decades. A chatbot implemented in a customer support pipeline instantly displaces dozens or hundreds of agents. A document processing model integrated into a law firm’s workflow instantly displaces paralegal hours. A code generation model embedded in developer tools instantly displaces programmer time. When technological substitution occurs at that pace, retraining and reskilling become reactive rather than proactive, and labor markets cannot adapt smoothly.

The second discontinuity is scope. AI automates tasks across many different occupations simultaneously. This is unprecedented. The mechanization of agriculture did not eliminate jobs in finance, law, business, or healthcare. The computer revolution elevated knowledge work even as it eliminated clerical work. AI, by contrast, touches every vertical from legal analysis to medical imaging to graphic design to elementary education. That breadth matters because labor markets depend on possessing a diversity of absorptive capacity. If automation hits one sector, displaced workers can migrate to others. If automation hits many sectors at once, migration pathways narrow.

The third discontinuity is task decomposition. AI does not eliminate entire jobs at once, but strips away tasks within jobs, leaving fragmented remnants of work behind. A software engineer might still be employed, but they now spend less time writing boilerplate code and more time integrating machine outputs. A financial analyst might still work, but now spends less time building spreadsheets and more time interpreting summaries. The result is a slow erosion of hours, and not a sudden elimination of roles. This creates a structural underemployment problem where people stay employed but earn fewer hours, earn less income, and will probably engage in less meaningful work.

The fourth discontinuity is substitutability.  In earlier eras, technology often complemented human labor, making workers more productive and increasing demand for their skills. AI increasingly substitutes for human labor outright. For example, when generative models reduce the need for copywriters, the value of copywriting skills declines, and there is no complementary surge in demand elsewhere. When large language models can draft legal memos, they do not make junior associates more valuable…they make them less essential. This dynamic weakens the wage system’s core promise that productivity leads to income.

If we zoom out, a clearer picture begins to emerge in labor markets. The issue is not mass unemployment in the classical sense, but mismatched agency. People will still want to contribute, but the formal economy will not be able to compensate for that contribution with livable wages for everyone. We have slowly started to ask ourselves, “what will jobs become, or how will we survive if there are no jobs?”. But every time I hear someone pontificate endlessly on the immediate perils of the labor market due to technology, I’m met with crickets when it comes to a discussion of what we should do next.

In response to these questions, most policymakers and representatives frequently invoke retraining pipelines, STEM education, and entrepreneurial incentives. These are valid efforts but insufficient for many structural reasons. Retraining assumes there will be enough new labor categories to absorb displaced workers. STEM pipelines assume cognitive labor will remain scarce. Entrepreneurial incentives assume individuals will self-create value in competitive markets. All three assume the wage economy will remain dominant. None of these assumptions is guaranteed.

Alongside these proposals sits the more radical idea of Universal Basic Income. UBI has become the most widely recognized policy response to the prospect of widespread automation. The structure of the argument is elegant in its simplicity: if machines generate unprecedented economic abundance but require fewer workers to operate, then society can decouple survival from employment by providing every individual with a guaranteed income floor. This would ensure that no one falls through the cracks as wage labor becomes less accessible. UBI advocates often cite the possibility of a “post-scarcity” economy in which human creativity, curiosity, and self-directed learning replace toil and drudgery.

And at first glance, UBI seems almost tailor-made for the crisis of automation. If the problem is that people may no longer be employable in sufficient numbers, then providing unconditional income appears to solve the economic side of the problem. Pilot programs have demonstrated positive outcomes. Finland’s experiment showed improvements in mental health, stress reduction, and life satisfaction, even though employment effects remained moderate. Kenya’s income trials demonstrated improvements in nutrition, housing stabilization, and household savings. Stockton, California’s experiment found that recipients experienced less income volatility and greater psychological well-being. These are not trivial results. Economic insecurity creates cognitive load, chronic stress, and intergenerational trauma. Any policy that mitigates these effects deserves serious attention.

However, the UBI discourse often jumps from these positive findings to the conclusion that UBI is THE solution to the end of work. This is where the mirage begins. UBI is a powerful tool for stabilizing consumption, but it does not address the deeper issue around the erosion of economic identity and social participation. Humans are not only consumers who need money to survive, but contributors to a society who need recognition, agency, and some sense of belonging. UBI solves for the former while leaving the latter unaddressed.

To validate this, consider the structure of contemporary welfare states. Unemployment insurance, disability support, retirement pensions, childcare subsidies, food assistance, and housing vouchers all exist to ensure survival and mitigate poverty. They are essential, but they do not constitute participation in society.

No one derives identity from being a welfare recipient. To build a life around receiving money rather than contributing to a shared purpose is not inherently dignifying. The political rhetoric surrounding welfare illustrates this clearly. Welfare is framed as charity and dependency, and not contribution and participation. UBI removes the stigma by making everyone a recipient, but it does not change the fundamental dynamic that money without contribution is survival, not belonging.

The UBI model also assumes that money is the bottleneck in the post-automation economy. This is only partially true. Money is a bottleneck in the current system because survival is tied to wages, and wages are tied to jobs. Remove jobs, and money becomes scarce. UBI fixes that.

But in a fully automated economy, money may become abundant. What becomes scarce instead is meaningful work, structured participation, and visible contribution. A society can have infinite goods at zero marginal cost and still suffer catastrophic social decay if its citizens lack purpose.

Another limitation of UBI emerges when considering fiscal and political feasibility. A universal income set high enough to sustain dignified living would require significant taxation, political consensus, and administrative competence. In a world where electoral politics is polarized and fiscal conservatives dominate budgetary discourse, the odds of a robust national UBI passing and persisting are extremely low.

In addition to the financial constraints, welfare programs are politically fragile because they can be retrenched or defunded by future governments. UBI is not inherently immune to these dynamics. It may begin as universal and unconditional but devolve into conditionality or austerity during fiscal crises.

Even if we wish away the political obstacles, UBI remains conceptually incomplete. It treats citizens as consumers rather than co-creators of society. To their credit, UBI advocates often argue that removing the compulsion to work will free people to pursue creative or civic projects. 

In other words, they assume that once survival is guaranteed, people will naturally gravitate toward contribution. This is optimistic anthropology. While some individuals might start community gardens or form artist collectives, many will not. Not because they are lazy or unmotivated, but because human beings require structure, norms, and incentives to convert intention into behavior. If we believe people will spontaneously devote themselves to civic improvement once freed from wage labor, we are confusing possibility with probability.

The deeper flaw in the UBI framework is that it asks the wrong question. UBI asks, “How do we ensure people can consume without employment?”. The correct question in a post-automation society is, “How do we ensure people can contribute without employment?”. Because consumption without contribution may satisfy basic needs, but it will not satisfy the human need for agency, identity, status, and belonging.

Status in industrial societies has always been tied directly to occupation. We always ask children what they want to “be,” and their answer is always some awesome profession. When adults meet for the first time, they ask, “So what do you do?”.  This language reveals how deeply our culture ties identity to wage labor. If wage labor disappears, the identity infrastructure collapses, and UBI does not rebuild it.

None of this is to say that UBI is useless. On the contrary, I suspect that UBI or UBI-like policies will be necessary components of a post-work welfare architecture. But UBI cannot be the architecture itself. It can ensure survival but it cannot ensure meaning. 

If we want a future in which automation enhances human flourishing rather than eroding it, we need to move beyond the paradigm of distribution and begin designing systems of recognition. We need institutions capable of recognizing and compensating the forms of labor that markets cannot price. But what is that labor?

I think the answer exists in the vast domain of civic-labor that sustains our communities but falls outside of traditional economic metrics. I look at this as a “value blind spot” in modern capitalism, and to explore its potential, we should reexamine the underlying assumptions for what counts as work, who counts as a worker, and how we can begin to quantify the value of this work? 

All of this matters for a simple reason. If wage labor collapses, the system that distributed collective purpose will collapse with it. The wage was never just about getting paid, but society’s way of living a collective life. Automation threatens that mechanism by eliminating jobs and hollowing out the categories of labor that wages were designed to reward. 

When the market can no longer reliably assign value to human effort, we should look elsewhere. Civic-labor is the most obvious and overlooked candidate because it has always been present and fundamentally resistant to automation. The unraveling of wage based value will force us to confront a domain of value that industrial capitalism has continuously failed to recognize as legitimate. 

Chapter 2 - Revealing Civic-Labor