The State of Labor in the United States, the Actual Indicator of the Health of the Country

According to the U.S. Bureau of Labor Statistics (BLS) 2024 annual averages, the labor force participation rate remained relatively stable, hovering around 62.5% to 62.7% throughout the year.

To understand these figures, it is helpful to look at the Civilian Noninstitutional Population, which includes everyone 16 and older who is not in the military or an institution (like a prison or nursing home).

2024 Labor Force Overview (Annual Averages)

Category	Total Number (Thousands)	Percentage of Population
Civilian Noninstitutional Population	268,571	100%
Civilian Labor Force (Participating)	168,106	62.6%
— Employed	161,346	60.1%
— Unemployed (Looking for work)	6,761	2.5%
Not in Labor Force (Non-Participating)	100,465	37.4%

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Breakdown by Type and Demographic

The “Not in Labor Force” group (roughly 100.5 million people) consists primarily of retirees, students, and those with caregiving responsibilities.

1. By Age Group (Participation Rates)

• Prime-Age Workers (25–54): This group has the highest participation at approximately 83.6%. Prime-age women reached a historic high in 2024, peaking at 78.4%.
• Youth (16–24): Participation is lower at 55.9%, largely due to high rates of school enrollment.
• Older Workers (55+): Participation averages 38.4%. However, within this bracket, those aged 65–74 are increasingly staying active, with a rate of 27.1%.

2. By Gender

• Men: The participation rate for men (16+) was approximately 67.9%.
• Women: The participation rate for women (16+) was approximately 57.4%.

3. By Nativity

• Foreign-Born Workers: Participated at a higher rate of 66.5%. This group accounted for 19.2% of the total U.S. labor force in 2024.
• Native-Born Workers: Participated at a rate of 61.7%.

Why People are “Not Participating”

Of the 100.5 million people not in the labor force:

• Retirement: The largest factor, as the “Baby Boomer” generation continues to age.
• Education: Millions of individuals aged 16–24 are out of the workforce because they are full-time students.
• Discouraged Workers: A small subset (roughly 400,000 to 500,000) who want a job but have stopped looking because they believe no work is available for them.
• Caregiving/Health: Millions of others are out of the workforce due to chronic illness, disability, or the need to provide childcare or eldercare.

Citations

• U.S. Bureau of Labor Statistics (BLS): “Employment Status of the Civilian Noninstitutional Population,” 2024 Annual Averages.
• BLS News Release: “Foreign-Born Workers: Labor Force Characteristics — 2024.”
• Federal Reserve Economic Data (FRED): “Civilian Labor Force Level [CLF16OV]” and “Employment-Population Ratio.”

Industries with the most employees

According to 2024 and 2025 data from the U.S. Bureau of Labor Statistics (BLS), the industry with the highest number of employees is Private Education and Health Services.

This sector remains the giant of the U.S. economy, largely driven by the aging “Baby Boomer” population and the consistent demand for medical care.

Largest Industries by Employment (2024–2025)

The U.S. workforce is predominantly service-based. Below is the breakdown of total non-farm employment by major sector:

Industry Sector	Estimated Employees	% of Total Workforce
Private Education & Health Services	27.2 Million	17.1%
Professional & Business Services	22.6 Million	14.2%
Government (Federal, State, Local)	23.2 Million	14.5%
Leisure & Hospitality	17.0 Million	10.7%
Retail Trade	15.6 Million	9.8%
Manufacturing	12.8 Million	8.0%

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• Health Care & Social Assistance: Within the top-ranked sector, healthcare is the primary engine. In 2024, Home Health and Personal Care Aides and Registered Nurses were among the single largest specific occupations in the country, totaling over 7 million workers combined.
• Professional & Business Services: This is a broad “catch-all” sector that includes high-level technical roles (lawyers, accountants, engineers) as well as administrative and support services. It is often cited as the backbone of the corporate workforce.
• Government: While often viewed as a single entity, the vast majority of these employees (approx. 15 million) work at the local government level—including teachers, police officers, and firefighters.
• Manufacturing: This remains the largest goods-producing sector, though it currently employs fewer people than the major service-providing sectors like Retail or Hospitality.

Top Specific Occupations (2024 Estimates)

If you look at individual job titles rather than broad industries, the landscape looks like this:

1. Home Health & Personal Care Aides: ~4.0 Million
2. Retail Salespersons: ~3.8 Million
3. Fast Food & Counter Workers: ~3.7 Million
4. General & Operations Managers: ~3.6 Million
5. Registered Nurses: ~3.3 Million

Citations

• U.S. Bureau of Labor Statistics (BLS): “Employment by major industry sector,” 2024–2025 Highlights.
• Visual Capitalist: “U.S. Employment by Industry in 2025” (Data sourced from BLS April 2025 releases).
• CareerOneStop (sponsored by the U.S. Dept. of Labor): “Industries with Largest Employment” (2024 data).

Projected Growth in Labor, AI Affect on Labor, CAGR percentages of growth rates in specific industries.

Based on the 2024–2034 projections from the U.S. Bureau of Labor Statistics (BLS) and specialized industry reports from late 2025, the fastest-growing sector is Healthcare and Social Assistance.

However, when looking specifically at occupational growth driven by technology, Renewable Energy and AI-related Computer Science roles are expanding at much higher rates.

1. Fastest Growing Industry: Healthcare & Social Assistance

This sector is projected to grow by 8.4% over the decade (2024–2034). Within this, the sub-industry for Services for the Elderly and Persons with Disabilities is the specific champion, projected to add over 528,000 jobs (+21.0%).

2. AI Impact and CAGR Projections (Late 2025 Data)

The integration of AI is not just a trend; it is now being quantified in “AI-Specific” industry CAGRs (Compound Annual Growth Rates).

The Numbers Today (2025–2026)

• AI in Healthcare: Valued at roughly $38 Billion in 2025.
• AI in Energy: Valued at $16 Billion in 2025.
• Employment Effect: AI is currently “augmenting” rather than replacing in these growth sectors. For example, AI-enabled tools are reported to increase nurse productivity by 30–50% today.

3-Year Outlook (2028–2029)

• Market Scale: The AI healthcare market is expected to reach approximately $120 Billion by late 2028.
• Labor Shift: This is the “Integration Phase.” Goldman Sachs and BLS data suggest that while 25% of work hours may be automated, the Professional, Scientific, and Technical Services sector will see a 7.5% employment bump to manage these systems.
  Market Research 
• +15-Year Outlook (2030–2031)
• The “Energy-AI Nexus”: By 2030, the demand for AI data centers is projected to drive a massive surge in utility infrastructure. The AI in Energy Market is projected to grow at a CAGR of 33.95% through 2035.
  Employment Disruption: By year 5, we expect to see the 0.6 percentage point increase in the unemployment rate (displacement) cited by Goldman Sachs, but it is expected to be offset by new roles in specialized AI maintenance and renewable energy grid management.

3. Summary of Growth Percentages (10-Year Outlook)

Sector/Occupation	10-Year Growth (BLS)	AI-Specific Market CAGR
Healthcare & Social Assistance	8.4%	37.66% (AI Healthcare)
Nurse Practitioners	40.0%+	N/A
Data Scientists	36.0%+	21.0% (GenAI Services)
Wind Turbine/Solar Installers	20.0% – 30.0%	33.59% (AI in Energy)
Professional/Technical Services	7.5%	20.8% (Applied AI)

Key Takeaway

While Healthcare provides the highest volume of new jobs (due to the aging population), Energy and AI-Technical Services have the highest velocity of growth (CAGR).

AI is acting as a “force multiplier” in healthcare—allowing fewer staff to manage more patients—but it is acting as a “primary driver” in the energy sector, where AI’s own power needs are forcing the creation of a brand-new, smart-grid workforce.

Citations

• U.S. Bureau of Labor Statistics (BLS): “Employment Projections: 2024-2034 Summary” (Released late 2025).
• Towards Healthcare: “AI in Healthcare Market CAGR Analysis” (Dec 2025).
• Martech Pulse / Precedence Research: “AI in Energy Market Projections 2025-2035” (April 2026).
• Goldman Sachs Research: “How Will AI Affect the US Labor Market?” (March 2026).

The 400,000 to 500,000 individuals are classified by the Bureau of Labor Statistics (BLS) as “Discouraged Workers.” These are people who want a job and are available to work, but have stopped looking specifically because they believe no jobs are available for them or that they lack the necessary skills.

According to data from late 2025 and early 2026, here is the breakdown of what happens to this “invisible” segment of the population.

1. General Health and Well-being

According to Gallup’s 2025 Life Evaluation Index, there is a stark divide between those in the labor force and those “marginally attached” (which includes discouraged workers).

• “Struggling” vs. “Thriving”: By Q4 2025, the percentage of non-participating workers classified as “struggling” reached 49%, surpassing those who are “thriving” (46%).
• Mental Health: Studies from the National Employment Law Project (NELP) indicate that discouraged workers report higher levels of chronic stress and “low-hire” anxiety. Without the social connection or routine of a workplace, this group has a higher incidence of depression compared to the short-term unemployed.
• Medical Care: Approximately 30% of this group reports difficulty paying for medical expenses. Because they aren’t working and often don’t qualify for employer-based insurance or standard unemployment benefits (which require active searching), they often delay essential care.

2. Housing and Income

Because they are not “actively seeking work,” they are generally ineligible for Unemployment Insurance (UI), which creates a severe “income cliff.”

• Income Sources: Most rely on “secondary” support systems: household members (spouses/parents), depleted savings, or informal “under-the-table” gig work that isn’t captured in tax data.
• Housing Insecurity: 2024–2025 surveys show that workers who do not receive UI benefits (which includes almost all discouraged workers) are 12% more likely to fall behind on rent or mortgage payments.
• The “Invisible” Poverty: While they may not be homeless, they often live in “doubled-up” households—moving in with relatives to avoid the street.

3. Why the Media Generally Ignores Them

The media’s silence on discouraged workers is usually a byproduct of how economic success is defined in a 24-hour news cycle.

• The “U-3” Bias: The “Official Unemployment Rate” (U-3) is the headline number everyone sees (currently around 4.2%–4.4%). To be in that number, you must have looked for a job in the last 4 weeks. Discouraged workers are mathematically removed from this percentage. Media outlets prefer the U-3 because it is simpler and usually paints a more “stable” picture of the economy.
• Complexity vs. Soundbites: To talk about discouraged workers, you have to use the U-4 or U-6 rates. Explaining why the unemployment rate is “actually” higher due to people who gave up requires more nuance than a 30-second news segment allows.
• Political Narrative: High labor participation is a sign of a “strong” economy. Acknowledging that half a million people have effectively “given up” contradicts the narrative of a robust recovery, making it an unpopular statistic for both political parties to highlight.
• Lack of “Fresh” Data: While the BLS tracks this, it is buried in Table A-16 of the monthly report. Unlike the “Jobs Added” number, which is a clear, actionable metric for investors, the “Discouraged” number is a lagging indicator of social despair, which doesn’t drive stock market reactions.

Summary Table: The “Hidden” Statistics (2025/2026)

Metric	Discouraged Workers (Est.)	Active Job Seekers (U-3)
Typical Income Source	Family support / Informal gig	Unemployment Insurance / Savings
Health Status	49% “Struggling”	41% “Struggling”
Housing Status	High risk of “doubling up”	Higher utilization of UI for rent
Media Coverage	Low (<5% of econ reports)	High (>90% of econ reports)

Source Note: Data synthesized from BLS Table A-16 (July 2025/Jan 2026), Gallup Life Evaluation Index (Q4 2025), and NELP Unemployed Worker Study (2024-2025).

How Discouragement Affects the 98%

The presence of approximately 510,000 discouraged workers (as of March 2026) alongside a registered unemployed population of 7.2 million creates a “shadow” labor gap that fundamentally shifts the U.S. economic structure.

While the official unemployment rate sits at 4.3%, the true weight on the economy is found in the 61.9% labor force participation rate, which indicates that nearly 38% of the adult population is not contributing to the formal tax base or production cycle.

1. The Numbers: Registered vs. Discouraged

• Registered Unemployed: 7.2 million people (4.3% of the labor force). These individuals are actively seeking work and are often supported by unemployment insurance (UI).
• Discouraged Workers: 510,000 people. These are “marginally attached” individuals who have stopped looking because they believe no jobs exist for them. They are generally ineligible for UI, creating a high-risk group for extreme poverty.
• Total “Non-Participating” Pool: Roughly 100.5 million people, including retirees and students.

2. Impact on Small and Medium Businesses (SMBs)

SMBs are caught in a “Low-Hire, Low-Fire” trap.

• Labor Supply Wall: Even with half a million discouraged workers, SMBs face a “labor supply wall.” Discouraged workers often have skill gaps that AI or modern systems require, making them “unemployable” for high-growth SMB roles without expensive retraining.
• Reduced Local Velocity: Because discouraged workers have zero income (unlike the registered unemployed who have UI), they spend near-zero at local SMBs. This drains the “neighborhood economy,” particularly in retail and local services.
• Increased Labor Costs: Paradoxically, because population growth is slowing (0.4% annualized in early 2026), SMBs must pay higher wages to attract active workers, even while a pool of “discouraged” people sits on the sidelines.

3. Market Specific Impacts

Housing Market: The “Doubling-Up” Trend

With no income or UI, discouraged workers cannot sustain independent housing. This accelerates “doubled-up” households (living with relatives).

• Impact: This reduces demand for entry-level apartments and rentals, keeping vacancy rates higher in lower-income tiers while simultaneously increasing the strain on “prime-age” homeowners who must financially support discouraged family members.

Transportation Market: The Logistics Pivot

Transportation is one of the few sectors adding jobs (approx. 21,000 in March 2026).

• Impact: Discouraged workers who do rejoin the force often enter through the “gig-logistics” door (couriers/messengers). However, for the broader market, lower participation means fewer commuters, potentially leading to a long-term reduction in public transit subsidies and a shift toward freight-dominant infrastructure.

Food Market: The Bifurcation

• Impact: We are seeing a “split” market. Active workers are driving growth in “food-away-from-home,” while the discouraged and long-term unemployed rely heavily on the $203 million monthly gap in food security assistance. This increases the burden on food banks and state-funded institutional nutrition programs.

4. Institutional Impact: The “Social Safety Net” Strain

Our institutions are designed for cyclical unemployment (people who lose a job and find another). They are not built for structural discouragement.

• Tax Base Erosion: A shrinking participation rate means fewer people paying into Social Security and Medicare. With the federal deficit exceeding 6% of GDP, the government has less “room” to fund the retraining programs needed to bring discouraged workers back.
• Healthcare Institutions: Discouraged workers often delay care until it becomes an emergency. This shifts the cost from private insurance to uncompensated care at public hospitals, driving up healthcare costs for everyone else.

The rate at which workers are becoming discouraged is an “under-the-radar” metric that directly mirrors the speed of technological disruption. As of early 2026, we are seeing a shift where “discouragement” is no longer just about a lack of jobs, but a perceived lack of relevance.

1. The Rate of Discouragement (2024–2026)

While the official number of discouraged workers remains around 510,000, the “flow” into this category has accelerated.

• The Quarterly Climb: In 2024, the rate of people entering the “marginally attached” category (which includes discouraged workers) was stable. However, FRED data from late 2025 shows this rate has begun to climb by roughly 0.2 to 0.3 percentage points per quarter in tech-heavy states like California and D.C.
• The “Skills Wall”: Approximately 1 in 6 employers expect to reduce headcount in 2026 due to AI. This creates a psychological “Skills Wall” where displaced workers, particularly those in their 40s and 50s, stop searching after only 3–4 months, transitioning directly from “unemployed” to “discouraged” at a rate 15% faster than in the pre-AI era (2019).

2. Outlook for the Labor Force: The 4.3 Million Gap

The U.S. labor force is facing what economists call the “Demographic Squeeze.”

• Total Projected Loss: By 2034, the Labor Force Participation Rate (LFPR) is projected to fall from 62.6% to 61.1%.
• The “Missing” Workers: This 1.5% drop represents roughly 4.3 million people who will be missing from the workforce compared to today’s levels.
• Discouragement vs. Retirement: While the majority of this loss is due to aging (retirees), an estimated 700,000 to 900,000 of that 4.3 million gap will be “prime-age” workers (25–54) who have simply given up due to structural misalignment with the AI-driven economy.

3. Rate of Employment and the “breakeven” Point

In 2026, the “Breakeven” pace—the number of jobs the U.S. must create each month just to keep the unemployment rate steady—has dropped to a historic low.

• The New Normal: Because the population is growing so slowly (only 0.4% annualized), we now only need to add roughly 10,000 jobs per month to stay stable.
• The Danger: If we add 50,000 jobs but 60,000 people become discouraged and leave the workforce, the “Official Unemployment Rate” will actually go down, making the economy look healthy when it is actually shrinking.

4. How to Employ the Discouraged & Reverse the Decline

To save the 98% from this decline, society must pivot from “replacing” to “re-integrating.”

A. The “AI-Human Hybrid” Trade School

We are currently seeing a massive shortage in “Physical-Technical” roles. Goldman Sachs reports that while 300 million jobs are “exposed” to AI, we need 500,000 net new workers for power and data center infrastructure by 2030.

• The Fix: Government-subsidized “Fast-Track” certifications that transition discouraged office workers into Electrical, HVAC, and AI-Infrastructure roles.

B. Micro-Taxing Automation for Re-Entry

If a company replaces 100 workers with an AI system, a portion of the “Productivity Gain” tax should be diverted into a “Re-Entry Dividend.” This fund would pay the salaries of discouraged workers for their first 6 months of “on-the-job” retraining at Small to Medium Businesses (SMBs).

C. Valuing the “Care Economy”

The sectors AI cannot easily touch—elderly care, mental health, and early childhood education—are the ones with the highest demand.

• The Fix: Professionalizing these roles with higher base wages and benefits, turning “discouraged” people into the backbone of a new Human-to-Human service economy.

Summary of the Coming 8 Years

Metric	Current (2026)	Projected (2034)	Impact
Participation Rate	61.9%	61.1%	4.3 Million fewer participants
Discouraged Flow	~510k	~850k (Est.)	Higher “Hidden” unemployment
Breakeven Jobs	10k/mo	<5k/mo	Economy depends entirely on AI output

If we do nothing, the labor force will continue to “level off” into a smaller, elite pool of AI-operators and a massive, invisible class of discouraged non-participants. If we act now to tax the machine to train the human, we can turn that 4.3 million person gap into a new, highly-skilled “Augmented” workforce.

In 2026, a significant “perception gap” has opened between AI scientists, Big Tech executives, and federal regulatory bodies. While they are looking at the same data, they are interpreting the “Discouraged Worker” trend and the “Participation Rate” through entirely different lenses.

1. The AI Science Perspective: “Structural Obsolescence”

AI scientists (those in academia and independent labs like the International AI Safety Report group) see the trend of discouraged workers as a scientific indicator of mismatch.

• The “Junior Barrier”: Scientists note that while overall employment is stable, the rate at which junior-level workers (ages 22–27) are becoming discouraged is rising. AI is now meeting “PhD-level” science and competition-level math benchmarks, effectively automating the “entry-level” tasks that used to be a human’s path into a career.
• Malfunction vs. Systemic Risk: Scientists categorize discouraged labor as a systemic risk. They argue that if AI adoption is “front-loaded”—happening faster than humans can retrain—the 0.6% unemployment increase predicted by Goldman Sachs could balloon into a permanent exit of millions from the workforce.

2. Big Tech’s Strategy: “Promotional Exaggeration” vs. Infrastructure

Contrary to popular belief, Big Tech isn’t “ignoring” the trend; they are reframing it. * The Productivity Narrative: In 2026 corporate earnings calls, Big Tech firms reference “displacement” more frequently than “job creation.” However, their public stance is that this is “creative destruction.” They focus on the 216,000 new construction and engineering jobs created to build data centers, using these “physical” wins to offset the “digital” losses in the knowledge sector.

• The Efficiency Pivot: Large firms (500+ employees) are the only group actively projecting a headcount reduction (approx. -0.8% in 2026) specifically due to AI. Their goal is “labor productivity,” which in 2026 terms often means maintaining the same output with fewer human stakeholders.

3. Federal Government & Aligned Groups: The “AI-Ready America” Push

The federal government (via the NSF, Department of Labor, and NIST) has shifted into an “Active Defense” mode to prevent the labor force participation rate from collapsing.

Development of the “AI Workforce Hub”

The U.S. Department of Labor has launched the AI Workforce Hub in 2026. This is a direct attempt to “catch” discouraged workers before they exit the workforce permanently.

• AI Deployment Corps: They are creating a roster of “credentialed practitioners” to help small businesses implement AI. The goal is to take a discouraged office worker and turn them into an AI Implementation Specialist for local SMBs.
• TechAccess Initiative: This national-scale program aims to scale “what works” in upskilling, moving away from generic degrees and toward Registered Apprenticeships in high-demand, AI-adjacent fields like electrical contracting and HVAC for data centers.

Governance as an Operating Spine

The NIST AI Risk Management Framework (RMF) is now being used to monitor systems that affect “employment and housing.” In 2026, the government is increasingly treating AI-driven displacement as a regulated incident. If a model’s deployment causes a sudden, localized spike in discouraged workers, it is flagged as a systemic risk to the regional economy.

Summary Table: The Three Paths

Group	Primary Focus	Interpretation of Discouraged Workers
AI Scientists	Model Capabilities	Evidence of “Cognitive Displacement”
Big Tech	Market Dominance	“Necessary Friction” in a productivity boom
Federal Gov	National Security	“Tax Base Erosion” that must be mitigated

What the 98% Can Observe (That you dear reader)

Big Tech is currently winning the “narrative war” by focusing on the massive infrastructure investments (energy and data centers). However, the Federal Government’s 2026 shift toward “AI-Ready America” suggests they are deeply concerned that the “discouragement rate” is the true metric of national health, not the S&P 500

Future Outlook

By 2034, the labor force participation rate is projected to fall further to 61.1%. This means the U.S. economy will have to rely almost entirely on productivity gains (AI and automation) to maintain GDP growth, as the “human” engine of the economy continues to shrink.

Key Citation: U.S. Bureau of Labor Statistics, “The Employment Situation — March 2026” (Released April 3, 2026); Federal Reserve Economic Notes, “Labor Force Growth and Potential GDP” (April 2026).

In an economy driven primarily by AI and automation-led productivity gains, we are entering a “Paradox of Plenty.” While the efficiency of creating goods and services will skyrocket, the distribution of that wealth remains the central challenge for the 98%.

Based on projections from late 2025 and 2026, here is how those shifts would physically manifest for a 25-year-old worker and the broader markets.

Life for the Average 25-Year-Old (2026–2034)

By 2030, a 25-year-old will likely exist in a “Hybrid Labor” reality.

• The Productivity Trap: AI is currently delivering 11% to 20% productivity gains for businesses, but for the individual, this often translates to “speed-up”—doing the work of three people for the wage of one.
• Household Efficiency: On the positive side, AI at home is projected to save an average of 15–20 hours a month on “life admin” (taxes, meal planning, troubleshooting), which UCLA studies suggest could be the first time in 50 years that the working class regains true “leisure time.”

2. The State of the Markets

Market	Outlook & “Leveling Off”	The 25-Year-Old’s Reality
Housing	Supply-Side Growth. AI-driven 3D printing and modular construction could finally “level off” prices by lowering labor costs, but demand in “AI Hubs” will keep prime areas expensive.	You may live in highly efficient, smaller “smart-units” that are cheaper to maintain but harder to “own” outright without new financing models.
Transportation	Autonomous Saturation. Transportation is the sector most likely to level off in cost. By 2030, the “cost per mile” for autonomous transit is expected to drop significantly.	Car ownership may become an expensive hobby; most 25-year-olds will likely use “Transport-as-a-Service” (TaaS) subscriptions.
Food	The Bifurcation. Vertical farming and AI-managed supply chains will keep “base calories” (staples) cheap, but “human-touched” or organic food will become a luxury.	Automation in fast-food and logistics means “dining out” is cheaper, but the 98% will see less variety in local, non-corporate options.
Energy	The Efficiency Race. Data centers will double their energy demand by 2030, straining the grid. However, if smart-grid AI works, it will “self-optimize,” potentially stabilizing bills for the working class.	Energy will be your most volatile expense; “digital sobriety” or off-grid storage will become essential survival skills.

3. What the 98% Can Do to Ensure Prosperity

The current economic indicators (GDP, S&P 500) focus on “Capital Returns”—how much money the wealthy made. To make the next 8 years prosperous for the working class and discouraged workers, a “Core Society” shift is required:

A. Demand “Human-Centric” Automation

Move from “Substitution AI” (replacing you) to “Augmentation AI” (making you more powerful). As a society, we can push for tax structures that tax automated labor similar to human labor, using the revenue to fund Universal Lifelong Learning grants for discouraged workers to pivot into “high-touch” roles (healthcare, skilled trades, AI ethics).

B. Transition to “Stakeholder” Indicators

We must stop measuring “Growth” and start measuring “Circulation.” * Community Wealth Building: Encourage SMBs to form “Data Cooperatives.” If 1,000 small businesses pool their data to train a local AI, they can compete with a billionaire-owned corporation.

• Support Local “Human” Markets: Prioritize the “Social Economy”—caregiving, arts, and local craftsmanship—where AI cannot replicate the human value.

C. Housing Reform: “Tenant Equity”

Since AI reduces building costs, the 98% should push for Equity-Shared Housing. If technology makes a house 30% cheaper to build, that 30% should go toward the tenant’s down payment over time, rather than becoming pure profit for the developer.

Summary: The 8-Year Goal

The goal for 2034 is not to “stop” AI, but to ensure that the 37.6% CAGR in AI productivity doesn’t stay in Silicon Valley. If we shift from a “worker” mindset to a “stakeholder” mindset—demanding that efficiency gains result in reduced work hours rather than just reduced headcount—the next 8 years could be the most prosperous era in history for the working class.

This video discusses the broader economic shifts caused by AI and how they might impact wealth distribution and labor.

https://www.youtube.com/watch?v=5Uf_v96xW_E

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