Toward a Post-Labour Society
Imagining life when AI handles most routine work — backed by research, data, and real-world experiments
Current Reality — 2025
invested in corporate AI in 2024, a 44.5% increase from the previous year
Corporate investment data 2024of Icelandic workers report satisfaction after transitioning to shorter work weeks
Iceland trials 2024The Post-Labour Horizon
For the first time in human history, we can realistically imagine a world where most routine labour is performed by machines. Not in some distant science fiction future, but within the coming decades. What does such a world look like?
A post-labour society doesn't mean no one works. It means work becomes a choice rather than a necessity — something we do because we want to, not because we must to survive.
Key Finding
While 57% of work hours are technically automatable, the transition to a post-labour society isn't predetermined by technology—it's shaped by policy decisions, economic structures, and societal values we choose today.
The Automation Reality
We're not speculating about a distant future. The automation of work is happening now, at an unprecedented pace. Understanding the scale and timeline helps us prepare for what's ahead.
| Timeline | Projection | Source |
|---|---|---|
| By 2030 | 400-800 million workers globally will need to shift careers due to automation | McKinsey |
| This Decade | 30% of work hours could be automated with existing technology | McKinsey |
| By 2030 | 14% of global workforce (375 million workers) will need to switch occupational categories | McKinsey |
| Next Decade | AI could boost U.S. productivity by 1.5% annually | Goldman Sachs / Penn Wharton |
These aren't pessimistic predictions—they're opportunities. Higher productivity could mean more wealth to distribute, more time for human pursuits, and the chance to reimagine what work means in our lives. The question is whether we'll design systems that share these benefits broadly.
Beyond Necessity
Throughout history, most humans have worked because they had to. Survival required labour — growing food, building shelter, earning income. This necessity has shaped our institutions, our values, and our understanding of what it means to live a good life.
When AI can perform most economically necessary labour, this fundamental constraint relaxes. The question shifts from "how do I earn a living?" to "how do I spend my time meaningfully?"
Real-World Experiments
We don't need to guess about post-labour possibilities. Countries and organizations are already testing reduced work hours, universal basic income, and new economic models. Here's what the evidence shows.
Reducing Work Hours
What happens when societies deliberately choose to work less? Iceland and the UK have run large-scale trials to find out.
Iceland Trial
- Productivity stayed the same or improved
- Worker wellbeing increased dramatically
- 51% of workers now have shorter hours
- 78% report satisfaction with working time
- Iceland's economy grew 5% in 2023
UK Trial
- 49% of businesses permanently adopted 4-day week
- 57% improvement in talent retention
- 1.4% revenue increase reported
- Productivity improvements or no change in most areas
Universal Basic Income Pilots
Multiple countries have tested giving people unconditional cash payments. The results challenge common assumptions about work motivation.
| Country | Program Details | Key Outcomes |
|---|---|---|
| Kenya | 23,000 participants 195 villages Started 2018 |
|
| Finland | 2,000 participants €560/month 2017-2018 |
|
| United States | Recent study: 1,000 participants $1,000/month for 3 years 40% income increase |
|
Important Context
As of 2025, no country has implemented a full nationwide UBI system. These are controlled pilots that inform policy discussions. The work hour reductions observed are modest—people still want to work, but gain flexibility to pursue education, caregiving, or better job opportunities.
AI's Economic Impact
AI isn't just automating tasks—it's creating economic value at unprecedented rates. The question is how this value gets distributed.
Current Impact (2025)
GDP growth boost from AI in Q2 2025
Average labor cost savings from AI tools
of organizations use AI in at least one function
Projected Impact
Annual U.S. productivity increase (next decade)
GDP increase by 2075 (Penn Wharton estimate)
The Meaning Question
One of the deepest challenges of a post-labour society is psychological. Work provides more than income — it provides identity, purpose, structure, and social connection. What replaces these functions when work becomes optional?
Research Finding: The Purpose Crisis
A 2024 Harvard study found that 58% of young adults reported experiencing little or no purpose or meaning in their lives in the previous month. This lack of meaning correlates strongly with mental health challenges including anxiety and depression.
The study also found that over half of young adults said their mental health was negatively influenced by "not knowing what to do with my life." Purpose matters—and we need to understand how to cultivate it beyond traditional employment.
History offers some precedents. The aristocracy of past eras lived without economic necessity and found meaning in art, politics, philosophy, and social pursuits. Some thrived; others descended into ennui. The difference now is scale: we're talking about this choice being available to everyone, not just a privileged few.
What Research Shows About Purpose
New Forms of Contribution
In a post-labour society, human activity might shift toward pursuits that emphasize human expression, connection, and judgment rather than economically necessary output.
Creative Pursuits
Art, music, writing, design — activities valued for their human expression rather than economic output.
Example: Independent creators, community theater groups, local arts initiatives that exist for cultural value rather than profit maximization.
Care and Connection
Nurturing relationships, community building, caregiving — work that benefits from human presence and emotional intelligence.
Example: Elder care, mentorship programs, neighborhood organizing, emotional support networks that prioritize quality time over efficiency.
Learning and Exploration
Education, research, discovery — pursuing knowledge for its own sake rather than immediate economic application.
Example: Citizen science projects, independent research, lifelong learning communities, curiosity-driven investigation.
Direction and Judgment
Guiding AI systems, making values-based decisions, ensuring human interests and ethics are served in an AI-augmented world.
Example: AI alignment work, ethical review boards, democratic technology governance, human-in-the-loop oversight roles.
Economic Models: A Comparison
How would economics work in a post-labour society? Researchers and policymakers have proposed several models. Here's how the leading approaches compare, based on current evidence and analysis.
Universal Basic Income (UBI)
How It Works
Every citizen receives a regular, unconditional cash payment regardless of employment status or income level. Funded by taxes on AI-generated productivity, wealth taxes, or resource revenues.
Advantages
- ✓Maximum individual freedom and choice
- ✓Eliminates means-testing bureaucracy
- ✓Reduces stigma of receiving benefits
- ✓Provides floor that prevents falling too low
- ✓Pilot data shows no "laziness" effect
Challenges
- !Very high cost (requires major tax reforms)
- !Potential inflation if not carefully designed
- !May not address specific needs (healthcare, housing)
- !Political difficulty of implementation
Real-World Status: No full national implementation. Pilots in Kenya, Finland, US show promise. Alaska Permanent Fund is longest-running partial example (since 1982).
Universal Basic Services (UBS)
How It Works
Essential needs (housing, healthcare, education, transportation, internet) are provided free or heavily subsidized, funded by AI productivity. Citizens receive services rather than cash.
Advantages
- ✓More cost-effective than cash transfers
- ✓Directly addresses essential needs
- ✓Highly redistributive (benefits poorest most)
- ✓Builds on existing public services
- ✓More politically feasible in many contexts
Challenges
- !Less individual choice and autonomy
- !Requires large public sector capacity
- !Risk of bureaucratic inefficiency
- !May not cover all individual needs
Real-World Status: UNESCO research shows existing public services in OECD countries worth 76% of poorest quintile's income vs 14% of richest.
Shared Ownership Models
How It Works
AI systems and automation infrastructure are owned collectively through public ownership, worker cooperatives, or sovereign wealth funds. Benefits are distributed as dividends or shared profits.
Advantages
- ✓Addresses wealth concentration at the source
- ✓Gives citizens stake in AI economy
- ✓Democratic control over powerful systems
- ✓Incentivizes responsible AI development
- ✓Sustainable long-term funding model
Challenges
- !Requires fundamental restructuring of ownership
- !Massive political resistance from current owners
- !Complex governance and decision-making
- !Risk of inefficiency or capture
Real-World Status: Norway's sovereign wealth fund ($1.7T) and Alaska Permanent Fund provide precedents. Tech cooperatives and public ownership models being explored.
The Common Thread
All three approaches share a fundamental insight: when AI dramatically increases productivity, we need mechanisms to distribute the benefits broadly rather than letting them concentrate among AI owners. The models differ in how distribution happens—through cash, services, or ownership—but agree on the need for some form of redistribution to maintain a functioning society and economy.
The Transition Challenge
The hardest part isn't imagining the end state — it's managing the transition. Moving from a work-based society to a post-labour society is a multi-generational project involving deep changes to education, policy, culture, and identity.
Key Transition Areas
Rethinking Education
What skills matter when AI does most work? Education needs to shift toward creativity, critical thinking, emotional intelligence, and lifelong learning rather than job-specific training.
Restructuring Social Safety Nets
Current systems tie benefits to employment. We need new models that provide security whether people work traditionally or not—experimenting with UBI, UBS, or hybrid approaches.
Developing New Sources of Meaning
With 58% of young adults already struggling with purpose, we need intentional efforts to build community, support creative pursuits, and help people find meaning beyond employment.
Ensuring Broad Benefit Distribution
AI benefits are currently concentrating among tech companies and their shareholders. Policy interventions—taxation, regulation, public ownership—are needed to ensure widespread prosperity.
These are not primarily technical challenges — they're social, political, and psychological challenges. The technology to enable a post-labour society already exists or is rapidly developing. The harder work is building the institutions, policies, and cultural frameworks to make the transition equitable and humane.
Thought Leaders & Academic Discourse
The idea of a post-work society isn't new, but it's gained urgency as AI capabilities accelerate. Here are key voices shaping the conversation.
Nick Srnicek & Alex Williams
Authors of "Inventing the Future: Postcapitalism and a World Without Work"
Argue for a post-work consensus built on three pillars: full automation to free labor from routine work, a sharply reduced work week, and universal basic income. They emphasize that anti-work politics should appeal broadly enough to form a populist movement.
Additional work: "Platform Capitalism" (2016), "After Work" (2023)
Rutger Bregman
Author of "Utopia for Realists" and public intellectual
Advocates for three solutions to create an ideal society: universal basic income, a 15-hour work week, and open borders. Emphasizes intellectual honesty in evaluating evidence—in 2024, acknowledged mixed results from recent UBI pilots while maintaining commitment to the idea.
BBC Reith Lectures 2025: "The Moral Revolution"
Post-Labor Economics: A Systematic Review
A comprehensive 2025 academic review synthesized research across economics, sociology, and technology studies, organizing discourse around four themes:
- 1.Theoretical frameworks for conceptualizing post-labor economies
- 2.Transition pathways from current labor-centric systems
- 3.Distribution models when income decouples from employment
- 4.Governance and policy implications of reduced labor requirements
Key debate: Is technology's impact on work predetermined, or shaped by human choices? The review emphasizes that post-labor outcomes depend on governance, policy incentives, and societal pressures—not technological determinism.
Not Utopia, Not Dystopia
A post-labour society could be wonderful or terrible depending on how we build it. It could mean freedom, creativity, and flourishing for all — or it could mean purposelessness, inequality, and loss of human agency.
The outcome isn't predetermined. It depends on the choices we make now about how AI is developed, who benefits from it, and what kind of society we want to create. The evidence from real-world experiments—UBI pilots, reduced work weeks, AI productivity gains—shows that positive outcomes are possible. But they require intentional design, equitable distribution mechanisms, and attention to human psychological needs.
Positive Scenario
- • Broad distribution of AI benefits
- • Freedom to pursue meaningful work
- • Strong social safety nets
- • Investment in community and culture
- • Democratic control over powerful systems
- • Focus on human flourishing over GDP
Negative Scenario
- • Extreme wealth concentration
- • Mass unemployment without support
- • Widespread purposelessness and despair
- • Loss of human agency and dignity
- • Social fragmentation and instability
- • Authoritarian control through dependency
The Planetary Labour Vision
At Planetary Labour, we believe in a future where AI amplifies human capability rather than replacing human value. Where the benefits of AI labour are broadly distributed. Where humans are freed to pursue meaning, creativity, and connection.
This isn't inevitable — it's a choice. And building it starts with how we design AI systems today. The research is clear: automation can improve lives, reduce drudgery, and create space for human flourishing—if we build the social and economic structures to support it.
The data from Iceland, Kenya, Finland, and dozens of other experiments shows that when we give people security and reduce mandatory work hours, they don't become lazy. They become healthier, happier, more creative, and more engaged in their communities. That's the future worth building.
Sources & Further Reading
AI Automation & Economic Impact
Universal Basic Income Research
Reduced Work Hours Experiments
Meaning, Purpose & Psychological Research
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