The New Anxiety Class: AI isn’t the threat to jobs. Our idea of work is ...

AI isn’t the threat to jobs. Our idea of work is. So what happens when work no longer works?

The debate about artificial intelligence and employment is often framed as a race between humans and machines. Which jobs will disappear? Which skills will survive? How quickly will automation spread?

These are understandable questions. But they miss the deeper issue. AI is not breaking the economic system. It is exposing that it was already out of alignment with reality.

In the global economic situation unfolding today the challenge isn’t just about jobs displaced by AI or technological disruption; it’s about how we conceive of work, identity, and worth in a world where inequality, automation, and prosperity are unevenly distributed. Bringing that deeper awareness into our economic conversations allows us to see not just the symptoms anxiety, insecurity, inequality but the root narrative we’ve inherited about value and survival. This new article continues that exploration: from personal belonging in 2026 to collective belonging in an economy transforming under the weight of artificial intelligence, automation, and systemic imbalance.

AI isn’t just changing jobs. It’s exposing an outdated idea of work, money, and worth. Robert Theobald warned us decades ago. Alan Watts explained why we didn’t listen. The real question now isn’t technical. It’s human.

AI, Global Inequality, and the question Robert Theobald asked too early

There is a quiet fracture running through the global economy. It is not just inflation, interest rates, or geopolitical instability. It is deeper than market cycles or technological disruption. It is the growing realisation that the rules we organised modern life around, work, money, and worth no longer align with reality.

Artificial intelligence has not created this moment. It has exposed it.

AI isn’t just changing jobs. It’s forcing a more uncomfortable conversation

The public debate about artificial intelligence and work is moving fast and staying shallow. We argue about displacement, reskilling, and productivity. These are reasonable concerns. But they are not the most important ones.

AI is not simply a labour-market issue. It is a mirror.

It reflects back assumptions we have lived with for so long they have become invisible about work, money, value, and what it means to deserve a secure life. Before we rush to technical solutions, it may be worth pausing to ask more fundamental questions.

What happens to human worth when intelligence, productivity, and creativity are no longer scarce? If machines can analyse, design, write, and produce at scale, what exactly remains uniquely human about value?

Why do we still tie survival to employment in economies that no longer need everyone to be employed? Is this an economic necessity, or a moral inheritance from an earlier age of scarcity?

When did work quietly become a test of deserving to live rather than a tool to serve life?

At what point did productivity replace dignity as the measure of worth?

How do we redesign systems for meaning, contribution, and social coherence in a world where AI makes abundance possible? What would an economy organised around human flourishing, rather than fear of exclusion, actually look like?

These are not abstract questions. They are already shaping anxiety levels, political tension, and social trust across advanced economies.

They are also questions that were asked quietly and unfashionably decades ago.

A Global context we rarely acknowledge

Only around 16% of the world’s population lives in high-income countries. The UK is part of that minority, with strong institutions, infrastructure, and access to healthcare and education.

The remaining 84% of humanity lives in low- or middle-income countries, where economic security is far less certain. By broader measures, around 44% of the global population lives on less than $6.85 a day, and nearly 9% in extreme poverty.

This matters because it reveals a truth we tend to avoid:

Economic security is not the global norm. It is the exception.

Living in a wealthy economy places someone in roughly the top 15–20% of the world by prosperity and opportunity. That position reflects geography, history, and inherited systems at least as much as effort or talent.

When we talk about the “future of work”, we are doing so from inside a minority experience that most of the world has never known.

A warning we chose not to hear

Long before artificial intelligence entered everyday language, the economist and futurist Robert Theobald identified the problem we are now confronting.

Writing in the 1950s through the 1970s, Theobald argued that technological progress would permanently reduce the need for human labour. While others focused on productivity and growth, he asked a different question:

What happens to people when work is no longer central to survival or identity?

At the time, automation meant machines replacing manual labour. Today, it includes algorithms that analyse data, generate text and images, diagnose illness, and perform tasks once assumed to require human judgment.

The scale has changed. The logic has not.

Theobald’s concern was not unemployment itself, but the decision to continue tying survival to employment in an economy that increasingly does not require everyone to be employed.

In such a system, insecurity is not a temporary failure.

It is a design outcome.

The rise of the new "Anxiety Class"

AI’s most immediate impact is not mass unemployment, but widespread unease. A new anxiety is emerging among professionals who are educated, skilled, and still employed, yet increasingly uncertain about their long-term relevance. This is not because they lack adaptability. It is because intelligence, once scarce, is becoming cheaper.

The underlying question is no longer simply “will my job disappear?" It is “if productivity no longer needs me, what is my place?”

Work has become more than an economic function. It has become a moral test, a measure of worth, deserving, and legitimacy.

AI does not destroy this belief. It exposes how fragile it is.

Outdated assumption of "Universal Basic Income" and what it means

Theobald concluded that societies would eventually need to decouple income from employment through some form of guaranteed income, not as charity or welfare, but as an adjustment to how wealth is actually created.

Modern prosperity rests on collective inheritance: infrastructure, technology, scientific knowledge, data, and institutions built over generations. When production no longer depends on full human labour, withholding income becomes a policy choice rather than an economic necessity and AI strengthens this argument. It does not weaken it.

The illusion beneath the system

Where Theobald diagnosed the structural flaw, the philosopher Alan Watts highlighted the conceptual confusion beneath it. Money, Watts observed, is not wealth or value. It is an accounting system, a way of measuring claims on real goods and services. Yet modern societies often treat money as though it were reality itself.

This leads to familiar contradictions: food exists but people go hungry; homes exist but people are homeless; skills exist but people are told they are “not needed”.

In an AI-driven economy capable of unprecedented abundance, this confusion becomes harder to justify.

Scarcity persists less because it must and more because it has been normalised.

The real challenge ahead

Technology does not create inequality. It accelerates it, and for those of us in high-income countries, AI feels disruptive, a break from assumptions we believed were settled. However for much of the world, precarity has always been the baseline and unless institutions evolve to keep pace, that divide will only widen.

This is why the debate about AI and jobs cannot remain technical. The deepest challenge we face is not economic. It is existential.

For centuries, work answered a fundamental question: Who am I useful to? As AI destabilises that answer, societies are forced to confront more difficult ones.

So how do we define human worth beyond productivity? What replaces survival as the organising principle of economic life? How do we design systems that reflect abundance rather than fear?

The future is not a world without work. It is a world in which work no longer determines who deserves to live well where contribution is chosen, dignity is inherent, and security is not conditional.

AI did not create this reckoning It has simply made it impossible to ignore.

What Global implementation would actually require?

Implementing this shift globally would not be a single policy change. It would be a civilisational transition, comparable in scale to the creation of public education, modern welfare states, or international labour standards.

1. A shift in first principles

Before policy, something deeper must change.

Most economic systems are still organised around a 19th–20th century assumption:

Human labour is scarce, necessary, and the primary source of value.

AI breaks that assumption.

A global transition would require explicit acknowledgement that:

• Productivity no longer depends on full human employment

• Survival is technically abundant, not scarce and we need to change perceptions

• Income distribution is a design choice, not a natural law

  
  

Without this intellectual honesty, every downstream reform remains defensive and temporary.

2. Redefining income as infrastructure, not reward

Globally, this would mean treating basic economic security the way we treat:

• Roads

• Clean water

• Public health

• Education

  
  

Not as something earned individually, but as foundational infrastructure for a functioning society. Practically, this could include:

• A guaranteed income floor (locally calibrated)

• Universal access to essentials (healthcare, education, energy, connectivity)

• Reduced dependence on employment as the gateway to survival

This would not eliminate markets or work. It would remove coercion from them.

3. Global differentiation, not uniformity

A critical point often missed: global implementation would not mean one universal number or identical system. Instead:

• High-income countries would primarily redistribute abundance

• Low-income countries would focus on development dividends, debt relief, and infrastructure-linked guarantees

• International institutions would need reform to prevent capital flight, regulatory arbitrage, and exploitation

  
  

This is coordination, not centralisation.

4. Tax, ownership, and automation of dividends

Funding mechanisms would vary, but globally would likely include combinations of:

• Automation and AI productivity dividends

• Land, resource, and data value capture

• Reduced administrative overhead from means-tested welfare

• Rebalancing taxation away from labour and toward rents, monopolies, and extreme concentration

  
  

The question is not “where does the money come from? ”It is who currently captures the value AI creates.

The benefits of doing this

1. Economic stability in an age of automation

Decoupling survival from employment:

• Dampens boom-bust cycles

• Reduces panic responses to technological change

• Maintains demand in highly automated economies

  
  

This is not anti-growth. It is anti-collapse.

2. Human capacity is freed, not suppressed

Evidence from pilots and real-world programmes consistently shows:

• People do not stop contributing

• They shift toward education, care, entrepreneurship, creativity, and community roles

• Risk-taking becomes possible without existential fear

  
  

Work does not disappear. Compulsion does.

3. Mental health and social trust improve

A system that does not threaten survival for non-compliance:

• Reduces chronic stress and burnout

• Lowers crime driven by desperation

• Increases trust in institutions

  
  

This matters more than GDP in the long run.

4. A truer measure of contribution emerges

When survival is guaranteed:

• Work becomes a signal of contribution, not obedience

• Care, volunteering, learning, and creativity gain legitimacy

• Human value is no longer reduced to employability

  
  

This is a cultural upgrade, not just an economic one.

The arguments against doing this (and why they persist)

It’s essential to take objections seriously

1. “People won’t work”

This concern is psychological, not empirical.

What people resist is:

• Meaningless work

• Exploitative work

• Work under threat

  
  

When survival pressure is removed, contribution changes, it does not vanish.

The deeper fear here is not laziness. It is loss of control.

2. “It’s too expensive”

This assumes:

• Current systems are efficient (they are not)

• Existing inequality is affordable (it is not)

• Crisis management is cheaper than prevention (it is not)

  
  

We already pay just badly, indirectly, and reactively.

3. “It will undermine merit”

This objection confuses dignity with reward.

Merit still matters for:

• Status

• Leadership

• Achievement

• Innovation

  
  

What changes is that failure no longer equals exclusion from life itself.

4. “It’s politically impossible”

This is often true until it isn’t.

Most foundational social systems were once considered:

• Radical

• Unaffordable

• Dangerous

  
  

They became inevitable when the old system failed visibly enough.

The price of doing this

The real costs of implementation are not primarily financial.

They are:

• Loss of moral leverage over labour

• Reduced fear-based compliance

• Challenges to identity systems built on productivity

• Short-term political backlash during transition

• Institutional redesign at scale

  
  

In other words: the price is giving up control mechanisms that no longer serve reality.

The cost of not doing this

This is where clarity matters most.

If we do not decouple survival from employment in an AI-accelerated world, the likely outcomes are not neutral.

They include:

1. Permanent insecurity for a growing majority

• Even as productivity rises

• Even as abundance increases

• Even as jobs become structurally insufficient

  
  

This erodes legitimacy.

2. Escalating mental health and social breakdown

Burnout, anxiety, resentment, and nihilism are not side effects. They are system signals.

3. Political polarisation and authoritarian drift

When people feel economically disposable:

• They radicalise

• They disengage

• Or they submit to coercive stability

  
  

None of these lead to healthy democracies.

4. A wasted human era

Perhaps the greatest cost is this:

We would reach a moment of unprecedented technological capability and still organise society around fear. That would not be a failure of technology. It would be a failure of imagination and maturity.

Is it the end or the end of the beginning? Perspective matters.

What happens to human worth when intelligence, productivity, and creativity are no longer scarce? If machines can analyse, design, write, and produce at scale, what exactly remains uniquely human about value?

Why do we still tie survival to employment in economies that no longer need everyone to be employed? Is this an economic necessity, or a moral inheritance from an earlier age of scarcity?

When did work quietly become a test of deserving to live rather than a tool to serve life?

At what point did productivity replace dignity as the measure of worth?

How do we redesign systems for meaning, contribution, and social coherence in a world where AI makes abundance possible? What would an economy organised around human flourishing, rather than fear of exclusion, actually look like?

The primary question is no longer whether we can redesign systems for a post-scarcity, AI-enabled world. The question is whether we are willing to.

The price of doing so is change. The cost of not doing so is coherence, dignity, and trust at scale. Unfortunately history suggests that when systems refuse to evolve peacefully, they eventually change violently.

This is not a technical choice.

It is a human one.