Navigating the L.A.C. Economy: From Income Floors to a Stake in Our Automated Future

by | Sep 5, 2025 | Post Labor Economics

The Dawn of the L.A.C. Economy: A Paradigm Shift in Production and Prosperity

The global economy is undergoing a structural transformation, entering a new phase defined by the intricate and evolving relationship between Labor, Automation, and Capital—the L.A.C. Economy. This era is distinguished from previous technological revolutions by a fundamental change in the nature of automation itself. While the First Machine Age augmented and replaced human physical labor, the current wave of innovation, powered by artificial intelligence (AI), is increasingly capable of performing complex cognitive tasks. This development is altering the historical dynamic between human workers and productive capital, shifting it from one of general complementarity toward one of direct substitution.

Defining the “Second Machine Age”

The framework for understanding this shift was articulated by Erik Brynjolfsson and Andrew McAfee, who describe the current era as a “Second Machine Age”.1 In this new age, digital technologies, with their core of hardware, software, and networks, are automating cognitive tasks once considered uniquely human. This makes human labor and software-driven machines potential substitutes in a widening array of fields, a stark contrast to the Industrial Revolution, where machines primarily amplified human physical capabilities, creating a complementary relationship.1

The tangible effects of this cognitive automation are already visible. AI-powered software can now grade student essays with a consistency that can exceed human evaluators, generate corporate earnings reports for news outlets without human intervention, conduct sophisticated legal research, and assist in medical diagnoses. This transition from automating physical and routine clerical work to automating non-routine cognitive work is the defining feature of the L.A.C. Economy.

The Nature of Modern Automation

Generative AI, in particular, represents a profound leap in this technological evolution, reshaping not only the nature of work but also human cognition itself.4 Unlike previous tools such as calculators or search engines, which served as extensions of human cognitive abilities, generative AI can independently synthesize vast amounts of information to create novel ideas and construct complex arguments.5 This raises a dual potential: while AI can augment human intellect by handling menial cognitive tasks and offering new insights, an over-reliance on it for direct answers—a form of “passive cognitive offloading”—risks eroding critical thinking and reasoning skills.4 Studies have shown that while students perform better on tasks

with AI assistance, their performance can decline when the tool is removed, suggesting a dependency that bypasses the mental practice necessary for skill development.5

Accelerating Adoption and Investment

The transition to the L.A.C. Economy is not a distant prospect; it is an accelerating reality, propelled by massive and sustained investment. The global factory automation market reached approximately $215 billion in 2023 and is projected to grow at a compound annual growth rate (CAGR) of 9.8% through 2030.6 Indicating widespread adoption, over 70% of global manufacturers have already implemented some form of automation in their operations.6 This trend extends beyond the factory floor into office work, with the Business Process Automation (BPA) software market expected to grow from $13 billion in 2024 to nearly $24 billion by 2029.7 As of 2024, two-thirds of all businesses have automated at least one process, a figure anticipated to reach 85% by 2029.7 This rapid integration is fueled by record-breaking venture capital and corporate investment into foundational AI, robotics, and the specialized semiconductors required to power them.8

The Task-Based Framework: Displacement and Reinstatement

To properly analyze the economic consequences of this shift, traditional models that view technology as simply “capital-augmenting” are insufficient. A more precise framework, developed by economists Daron Acemoglu and Pascual Restrepo, models the economy as a collection of tasks that can be allocated to either capital or labor.9 This task-based approach reveals two opposing forces that shape the labor market:

  1. The Displacement Effect: Automation allows capital (in the form of machines, robots, or AI) to take over tasks previously performed by humans. This displacement inherently shifts the task content of production against labor, reducing labor’s share of national income and potentially depressing overall labor demand.11 The critical development in the L.A.C. Economy is that this displacement is now occurring across a wide range of routine
    and non-routine cognitive tasks, affecting both blue-collar and white-collar professions.12
  2. The Reinstatement Effect: This is the countervailing force whereby technological innovation creates entirely new tasks, industries, and job roles in which human labor holds a comparative advantage.11 Historically, the creation of new, often more complex, jobs—from factory managers during the Industrial Revolution to software developers during the computer revolution—has been powerful enough to offset displacement and prevent mass, long-term technological unemployment.13

The central economic question of the L.A.C. Economy is whether the reinstatement effect can continue to keep pace with an exponentially accelerating displacement effect. The very nature of modern AI, which substitutes for the human cognitive abilities that were once the foundation of new task creation, casts doubt on this historical balance. Indeed, Acemoglu and Restrepo’s analysis of recent decades suggests that the displacement effect has already begun to accelerate while the reinstatement effect has weakened, setting the stage for profound economic disruption.11

The Twin Crises: Decoupling of Wages from Productivity and the Threat to Aggregate Demand

The paradigm shift described in the L.A.C. Economy is not a future hypothetical; its foundational pressures are already manifesting as two distinct but deeply interconnected economic crises. First, a multi-decade “great decoupling” has severed the historical link between overall economic growth and the financial well-being of the typical worker. Second, this decoupling, when amplified by the prospect of mass automation, creates a severe threat to macroeconomic stability through the potential collapse of aggregate demand.

The Great Decoupling

For decades, two fundamental trends have been reshaping the distribution of economic rewards in the United States, creating a fertile ground for the disruptions of the L.A.C. Economy.

The Productivity-Pay Gap

From the end of World War II until the late 1970s, the wages of typical American workers grew in lockstep with rising economy-wide productivity. This link ensured that the benefits of economic growth were broadly shared. However, since 1979, this relationship has fractured. Analysis from the Economic Policy Institute shows that while productivity has continued its upward climb, the compensation for the vast majority of the workforce (the bottom 80%) has stagnated.15 Between 1979 and 2025, productivity grew 2.7 times as much as the pay of a typical worker.15 This divergence is not an inevitable outcome of market forces but a consequence of a series of policy choices that systematically suppressed wage growth, including the toleration of higher levels of unemployment, the erosion of the real value of the federal minimum wage, the weakening of unions, and deregulation that shifted bargaining power from labor to capital.15

The Declining Labor Share of Income

Mirroring the productivity-pay gap is a more fundamental shift in the structure of the national economy: the decline in the labor share of income. This metric represents the portion of total GDP that is paid out to workers in the form of wages, salaries, and benefits. After decades of relative stability, the U.S. labor share began a secular decline in the 1980s, a trend that has accelerated since 2000, ultimately reaching its lowest level since the Great Depression.16

A McKinsey Global Institute report quantifies this shift, finding a 5.4 percentage point decline in the U.S. private business sector’s labor share between the 1998–2002 and 2012–2016 periods.18 This seemingly abstract percentage has profound real-world consequences: without this decline, the average American worker’s annual pay would be approximately $3,000 higher.18 Research from the International Monetary Fund (IMF) confirms this is a broad-based phenomenon, with the decline occurring across most states and industries, and identifies technology—specifically the automation of routine tasks—as the dominant driver, accounting for roughly half of the decline.19

The following table provides a stark visualization of this economic divergence.

PeriodAverage Annual Net Productivity Growth (%)Average Annual Real Median Compensation Growth (%)Average Labor Share of Income (%)
The Coupled Era (1948–1979)2.52.1~64
The Decoupling Era (1979–2025)1.40.6~58

Data Sources: Economic Policy Institute 15; Bureau of Labor Statistics and Brookings Institution.16

The Keynesian Nightmare: Automation and the Aggregate Demand Crisis

This structural shift of income from labor to capital is not merely an issue of fairness or inequality; it poses a fundamental threat to macroeconomic stability. The logic of this threat is rooted in a century-old debate between two competing economic laws. Say’s Law, a pillar of classical economics, posits that “supply creates its own demand,” suggesting that the act of producing goods generates the income necessary to purchase them, making a general glut of unsold goods impossible. In contrast, Keynes’ Law, formulated during the Great Depression, argues that “demand creates its own supply” and that an economy can become stuck in an equilibrium of high unemployment if aggregate demand—the total spending by consumers, businesses, and government—is insufficient.20

The L.A.C. Economy presents a scenario that is a textbook Keynesian problem. If automation displaces labor on a mass scale, it will concentrate income in the hands of capital owners, leading to a collapse in the purchasing power of the broad consumer base. As economist Nouriel Roubini warns, the result is that “vanishing jobs will strain consumer demand”.22 This could trigger a vicious cycle: falling consumer spending leads to lower business revenues and profits, which in turn leads to further layoffs and investment cuts, further depressing demand and spiraling the economy downward.20

The engine of this potential crisis is a well-documented economic behavior known as the marginal propensity to consume (MPC)—the fraction of an additional dollar of income that a household spends rather than saves. Crucially, the MPC is not uniform across the population. Numerous studies confirm that lower-income and lower-wealth households have a significantly higher MPC than their wealthier counterparts. A household struggling to meet basic needs will spend nearly all of any extra dollar it receives, while a wealthy household, whose needs are already met, will save a much larger portion.

Data from a study using the Panel Study of Income Dynamics illustrates this disparity vividly: the MPC for low-wealth households is ten times larger than for wealthy households.24 Another analysis found that households in the bottom wealth quintile have an MPC of 0.37 (spending 37 cents of an extra dollar), while those in the top quintile have an MPC of just 0.10.25

This heterogeneity in spending behavior is the mechanism that transforms the declining labor share from a distributional issue into a macroeconomic threat. As national income is systematically reallocated from labor (composed largely of high-MPC households) to capital owners (overwhelmingly low-MPC households), the economy’s overall “average” MPC falls. Each dollar shifted from wages to profits results in less total spending, creating a structural drag on aggregate demand and a headwind against economic growth. Mass automation threatens to accelerate this process to a breaking point, creating a world of immense productive capacity but with too few consumers able to afford its output.

Reimagining the Social Contract: Income Floors and Direct Cash Transfers

In the face of an economic paradigm that threatens to decouple human labor from income, the most direct policy response is to establish a non-labor source of income for citizens. Such an income floor serves a dual purpose: it provides essential economic security for individuals and families in a turbulent labor market, and it acts as a powerful macroeconomic stabilizer by supporting aggregate demand. The two most prominent proposals for achieving this are Universal Basic Income (UBI) and Citizen Dividends.

Universal Basic Income (UBI) as a Keynesian Stabilizer

UBI is a policy wherein all citizens of a country regularly receive an unconditional sum of money from the government. In the context of the L.A.C. Economy, its primary macroeconomic function is as a direct Keynesian stimulus. By injecting purchasing power directly into the hands of households—particularly those with the highest marginal propensity to consume—UBI aims to bolster aggregate demand and prevent the deflationary spiral of mass unemployment.

The potential macroeconomic impact of UBI is, however, a subject of intense debate, with outcomes depending entirely on the underlying assumptions of the economic models used.

  • The Roosevelt Institute/Levy Model: This analysis, rooted in a Keynesian framework, assumes the economy is primarily constrained by insufficient demand.26 In this view, a UBI acts as a powerful stimulant. The model projects that a debt-financed UBI of $1,000 per month for all adults would expand the U.S. economy by a remarkable 12.56% above the baseline forecast after eight years.26 Even when fully financed by taxes, the model predicts positive GDP growth. This occurs because the policy effectively redistributes income from high-income households (with a low MPC) to low- and middle-income households (with a high MPC), resulting in a net increase in total spending.26
  • The Penn Wharton Budget Model (PWBM): In stark contrast, the PWBM, which operates on neoclassical assumptions, views the economy as being constrained by the supply of labor and capital.28 From this perspective, a UBI is contractionary. The model projects that the same debt-financed UBI would
    reduce GDP by 6.1% by 2027.28 This negative outcome is driven by two main factors: a labor supply effect, where the unconditional income disincentivizes work, and a “crowding out” effect, where increased government borrowing raises interest rates and displaces private investment.28

This stark divergence reveals that the debate over UBI is not merely technical but ideological. It hinges on whether one believes the primary economic challenge of the coming decades will be insufficient demand (the Keynesian view) or insufficient supply (the neoclassical view). The evidence of a declining labor share and its effect on consumption strongly suggests that the demand-side constraints modeled by the Roosevelt/Levy framework are more relevant to the specific problems posed by the L.A.C. Economy.

A central concern surrounding UBI is its potential to cause runaway inflation. Critics argue that a large-scale injection of demand, if not met by a corresponding increase in the supply of goods and services, will simply cause prices to rise, eroding the value of the cash transfer and creating a “new zero”.30 Proponents counter that this fear is overstated, particularly if the UBI is funded through the redistribution of existing money rather than the creation of new money. They point to real-world evidence, such as the experience in Alaska, where the introduction of a statewide dividend was followed by a period of

lower inflation relative to the rest of the U.S.. Furthermore, by providing a stable financial floor, a UBI could stimulate entrepreneurship and small business formation, thereby increasing competition and supply, which would exert downward pressure on prices.30

Citizen Dividends: The Alaska Permanent Fund (APF) Case Study

While UBI remains largely theoretical, the world’s longest-running and most robust example of a universal cash payment provides invaluable empirical data: the Alaska Permanent Fund (APF).33 Established in 1976, the APF is a state-owned investment fund capitalized by revenues from Alaska’s oil wealth. A portion of the fund’s annual investment earnings is distributed to every resident—man, woman, and child—in the form of a citizen dividend.33

The APF is a crucial case study because it differs from a tax-funded UBI in a fundamental way: it is a return on the collective ownership of a shared asset. This framing has given the dividend immense political durability, as Alaskans view it not as a government handout but as their rightful share of the state’s natural resource wealth.35

The observed economic impacts of the APF directly challenge some of the primary criticisms leveled against UBI:

  • Impact on Employment: A landmark 2018 study published by the National Bureau of Economic Research found that the dividend had no effect on aggregate employment.36 While it did lead to a modest increase in part-time work, it did not cause the large-scale exit from the labor force predicted by models like the PWBM.
  • Impact on Poverty and Inequality: The dividend has had a profound effect on economic well-being. It is credited with helping Alaska achieve the highest level of economic equality among all U.S. states and has been shown to reduce poverty rates by as much as 20%–40%, with particularly strong positive effects for rural Indigenous communities.33
  • Impact on Social Well-being: Beyond purely economic metrics, universal cash transfer programs have demonstrated significant positive effects on health and well-being. The UBI experiment in Stockton, California, for example, led to clinically significant improvements in the mental health of recipients, reducing anxiety and depression.31

The Alaska Permanent Fund serves as a powerful proof of concept. It demonstrates that a universal, unconditional cash payment can be administered for decades without cratering the labor market or causing hyperinflation. More importantly, its structure as a dividend from collective capital ownership provides a conceptual blueprint for addressing the core challenge of the L.A.C. Economy: ensuring that the returns from the new, automated forms of capital are broadly shared.

Beyond Income – New Models of Ownership in an Automated Age

While income floors like UBI and citizen dividends are essential tools for providing economic security and stabilizing aggregate demand, they primarily address the symptoms of the L.A.C. Economy—namely, insufficient income for displaced workers. A more fundamental and durable solution must address the root cause: the hyper-concentration of ownership of the new, immensely productive automated capital. This requires moving beyond redistribution (taxing and transferring income after it has been generated) toward “predistribution”—shaping the initial distribution of wealth and market power so that the gains from automation are shared more broadly from the outset.37

Social Wealth Funds (SWFs): An “AI Dividend” for All

The most direct way to ensure the public benefits from the productivity of AI is for the public to own a stake in it. This can be achieved through the creation of a Social Wealth Fund (SWF), a state-owned investment vehicle that would acquire equity in the foundational technologies of the L.A.C. Economy.38

  • Concept and Funding: Unlike traditional SWFs, which are typically capitalized by revenue from nonrenewable resources like oil 39, an “AI Fund” would be capitalized by the wealth generated by automation itself. This could be accomplished through several innovative mechanisms:
  • Requiring foundational AI companies to contribute a portion of their equity to the fund as a condition of their corporate charter or operating license—an “equity tax.”
  • Direct government investment, treating AI infrastructure as a public good.
  • Levies on key inputs to AI development, such as massive-scale computational resources or energy consumption by data centers.38
  • Distribution as an “AI Dividend”: The returns generated by the SWF’s investments would be distributed periodically to all citizens as a universal dividend.38 This mechanism would directly counteract the declining labor share of income by creating a new, rising “citizen’s capital share.” It would transform every citizen into a shareholder in the automated economy, directly linking their prosperity to the productivity gains of AI and robotics. This model reframes the payment not as a welfare transfer but as a legitimate return on collective investment, mirroring the politically durable structure of the Alaska Permanent Fund.
  • Challenges and Governance: The implementation of such a fund faces formidable challenges. Chief among them are governance risks, including the potential for the fund to be used for political patronage or captured by elite interests, thereby undermining its public benefit.38 To be successful, an SWF would require an ironclad mandate to serve the public benefit, radical transparency in its operations, and independent oversight insulated from short-term political pressures. There is also the risk that state investment could stifle private innovation or escalate geopolitical rivalries over technological dominance.38

Data as a New Form of Labor and Property

A second, more radical approach to predistribution involves rethinking the very inputs of the AI economy. The generative AI models that are driving the current wave of automation are not created from nothing; they are trained on vast datasets of text, images, and code generated by billions of human beings. This data is the indispensable raw material without which the AI capital would be worthless. This perspective allows for a powerful reframing: the creation of this data is a form of productive, yet currently uncompensated, labor.

  • The Legal and Technical Hurdles: The current legal landscape is a significant barrier to this concept. Data is generally not treated as property that can be “owned” by an individual. Instead, legal frameworks like the EU’s General Data Protection Regulation (GDPR) treat personal data as an access right, focusing on privacy and consent rather than ownership and compensation.43 The technical challenge is also immense: tracing the provenance of every piece of data in a trillion-parameter model and assigning a value to its contribution is a problem of staggering complexity.44
  • Emerging Frameworks for Data Stewardship: Despite these hurdles, new models are being proposed to grant individuals a collective stake in the value their data creates.
  • Data Trusts: These are legal entities wherein a trustee would hold and manage the data rights of a large group of individuals (the beneficiaries).45 This fiduciary would have a legal duty to act in the beneficiaries’ best interests, negotiating with AI companies on their behalf for the terms of data use and for collective compensation. This model moves beyond individual consent, which is often meaningless in the face of complex terms of service, to create a form of collective bargaining power for data creators.45
  • Data as Labor and Data Dividends: This concept seeks to establish new economic and legal institutions to recognize data creation as a form of labor deserving of remuneration. This could involve creating mechanisms to track data usage and distribute micropayments or “data dividends” back to the individuals whose collective knowledge and creativity power the AI economy.

Establishing ownership and compensation rights for data is the 21st-century equivalent of the 20th-century struggles for the eight-hour workday, the minimum wage, and workplace safety. It is a fundamental question of whether the value created by a new form of labor will be shared with those who perform it or captured entirely by the owners of capital.

Conclusion – Forging a Human-Centric L.A.C. Economy

The emergence of the Labor, Automation, and Capital (L.A.C.) Economy represents a fundamental inflection point in economic history. The capacity of artificial intelligence to automate cognitive tasks threatens to upend the centuries-old relationship between technology, labor, and prosperity. Inaction in the face of this structural shift risks a future of deepening inequality, macroeconomic instability, and profound social dislocation. However, this outcome is not predetermined. The challenges posed by automation are significant, but they are amenable to bold and forward-thinking policy solutions that can steer the immense productivity gains of AI toward a future of broadly shared prosperity.

Synthesizing the Solutions: A Portfolio for Prosperity

Navigating the L.A.C. Economy requires a multi-faceted approach that combines immediate support for individuals with long-term structural reform. The proposed solutions—income floors and new models of ownership—are not mutually exclusive alternatives but are complementary and synergistic components of a renewed and resilient social contract.

  • Income Floors as a Stabilizing Bridge: Universal Basic Income and Citizen Dividends serve as the most direct and effective tools for addressing the immediate threats of the L.A.C. Economy. By providing a reliable income floor, they act as a powerful macroeconomic stabilizer, ensuring a baseline of aggregate demand to counteract the deflationary pressures of mass labor displacement. They provide critical economic security for individuals and families, enabling them to navigate a period of intense and unpredictable labor market transition.
  • Ownership Models as a Structural Foundation: Social Wealth Funds and new frameworks for data ownership represent a more fundamental, long-term solution. They address the root cause of the L.A.C. Economy’s central imbalance: the concentration of capital ownership. By creating mechanisms for universal ownership of automated capital and the data that fuels it, these models ensure that the wealth generated by these new productive forces is broadly distributed as a direct return on that ownership. This “predistributive” approach is more sustainable and politically durable than a system reliant solely on redistribution through taxes and transfers.

An optimal strategy would treat these approaches as a portfolio. Income floors can act as a crucial bridge, stabilizing the economy and supporting citizens during the transition, while Social Wealth Funds are capitalized and scaled over time. Eventually, the dividends from collective ownership could grow to provide a sustainable and substantial income floor, reducing the need for purely tax-funded transfers and creating a more equitable and dynamic form of stakeholder capitalism.

The Human-Centric Imperative

Ultimately, the policy choices before us are not merely a technical response to technological change but a normative decision about the kind of society we wish to build. The goal should not be to halt the advance of automation but to harness its power to create a more human-centric economy. This involves actively designing and incentivizing technologies that augment, rather than simply replace, human capabilities. The “Centaur” model of human-AI collaboration, which pairs human intuition, creativity, and ethical judgment with AI’s computational power, offers a compelling vision for the future of work.47 As scholars like David Autor argue, whether AI is used to empower workers or to de-skill and displace them is a design choice, one that can be shaped by public policy and institutional priorities.48

The Socio-Political Stakes

The imperative to act is not solely economic. The same forces of automation and globalization that are driving economic inequality are also fueling social and political instability. Research increasingly links the economic anxieties, feelings of marginalization, and status decline associated with job displacement to the rise of right-wing populism, the intensification of cultural grievances, and the erosion of social cohesion. The failure to build a new, inclusive social contract for the L.A.C. Economy risks not only economic stagnation but also the fracturing of our republics institutions. The solutions outlined in this chapter, therefore, are not simply proposals for a more equitable economy; they are essential investments in a more stable, just, and prosperous future for all.

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