The Rest Is Politics — Will AI Take Our Jobs? (Ep 2)

Date: December 19, 2025
Hosts: Alastair Campbell (A), Rory Stewart (B)
Theme:
Exploring the likely impacts of artificial intelligence (AI) on the future of work, employment, productivity, and economic wellbeing—while drawing historic parallels, debating political responses, and confronting both optimism and anxiety about tech-driven change.

Episode Overview

Campbell and Stewart continue their critical exploration of AI’s real-world effects, focusing this episode on the economic and social consequences of AI for jobs. The discussion weaves together perspectives from history (like the Industrial Revolution), today’s labor market worries (from law firms to manufacturing plants), global competitiveness, and existential questions about meaning and fulfillment in a labor-light future. The conversation is marked by constructive disagreement, a search for nuance, and regular reference to both policy and personal anxieties.

Key Discussion Points & Insights

1. AI’s Disruption of Professional Roles

• Entry vs. Senior Level Threats:
  • AI threatens to automate entry-level roles in fields like law and consulting, historically crucial for advancement.
    • “If you're entry level… basic legal discovery, basic case law, gathering documentation, can now be done by AI... These companies cease hiring the young people… in 30 years time there are no older experienced people because these young people haven't come in and haven't gone through all that drudgery work...” — Rory Stewart, [01:20]

2. Historical Parallels—The Engels Pause

• The Dark Side of Productivity Surges:
  • The ‘Engels Pause’ (Industrial Revolution): Productivity skyrocketed, but it took decades for ordinary people’s living standards to catch up—or actually declined at first.
    • “You see the massive investment, the massive productivity improvements, but living standards don't improve for ordinary people for 80 years.” — Alastair Campbell, [02:31]
  • The parallels with AI: “Would I rather be a ploughman in Cumbria or working in some horrible gradgrind factory?” — Campbell, [03:33]

3. Who Reaps the Gains from AI?

• Aggregate vs. Distributional Benefits:

  • AI’s productivity promise is immense, but who benefits and when is deeply political.
    • “The aggregate benefits of this technology will be enormous. The distributional benefits, who benefits and when they benefit, I think are very up for grabs and will largely come down to questions of political economy.” — Campbell, [03:44]

• Wages Lag Behind Productivity:

  • Example: Car industry productivity has soared while real wages have declined.
    • “The productivity per worker has increased tenfold. But the salary… has dropped massively in real terms at the same time as their productivity has gone through the roof.” — Stewart, [04:07]

4. Adoption vs. Caution—A UK Perspective

• Competitive Necessity:
  • Reluctance to adopt AI poses existential risks for UK industry; cautiousness could mean losing out globally.
    • “Our competitors internationally… accelerate, they adopt. We already know that the UK… are very slow adopters of technology… There’s a real risk to competitiveness in this country.” — Campbell, [05:12]

5. Deindustrialization, Retraining, and the Skills Gap

• Job Losses Aren’t Easily Offset by Reskilling:

  • History shows most affected workers (middle-aged, non-degree) struggle to shift careers.
    • “When the coal mine is closed, the coal miner doesn't end up suddenly retraining as a management consultant… seems pretty implausible to me.” — Stewart, [07:25]

• Where Are the New Jobs? Service Sector Pressure:

  • Optimists say new jobs always emerge, but skeptics ask what those are—with even service sector roles threatened by tech.
    • “It's very hard to imagine futures where we get to reallocate resources on this scale…” — Campbell, [08:38]

• The Real Issue: Meaningful Work, Not Just Any Work:

  • Unemployment isn’t the sole issue; what vanishes is dignified, well-paid work for people without degrees.
    • “I've lost a well paid, dignified job. And if I try to get a well paid job, the employer says to me, I don't have the skills... And you're not going to employ me in new tech. No.” — Stewart, [09:12]

6. AI, Universal Basic Income (UBI), and Human Fulfillment

• UBI Is Not a Panacea:

  • There’s skepticism that a future with “lots of lovely time” and no need to work will actually be fulfilling.
    • “I have a sort of instinct that humans really, really quite like working. We like being busy. And that this idea of us… living satisfying, fulfilled lives reading Shakespeare... No, I don't think that universal basic income or anything like it can be the answer...” — Stewart and Campbell, [11:05–12:12]

• Optimistic View: Human Ingenuity & New Wants

  • Humans repeatedly surprise; new desires and industries arise that couldn't be foreseen.
    • “We have historically always underestimated both the breadth and depth of human wants and needs and the breadth and depth of human ingenuity in meeting those needs.” — Campbell, [12:12]

7. Economic Concentration and the Risk of Trillionaires

• Inequality Worries:

  • Fears that AI economy could funnel wealth to a small number of ultra-rich, leaving most people out.
    • “All the money that's made is hoovered up by some trillionaires in the United States.” — Stewart, [12:52]

• Diffusion of Benefits Historically:

  • Counterpoint: Inventions mostly benefit society broadly, not just the companies that make them.
    • “Nearly all of the benefits of new technology diffuse into the economy... Only like 3% of the benefit of new technology is captured by the people that make it.” — Campbell, [13:10]

8. Should We Say "No" to AI?

• Could We Even Stop It? (And Should We?)
  • If it proves harmful, politicians actually could halt AI innovation—at least for now.
    • “At the moment... we switched off this stuff, these companies would collapse... it could still be a perfectly valid public policy choice if we thought this stuff was going to make people's lives worse.” — Stewart, [14:07]
  • Historic analogy: Facebook, plastics, ultra-processed food—mass adoption does not always equal positive impact.
    • “I think there are many things...where in retrospect we should have said no.” — Stewart, [15:20]

9. The “Optimist vs. Doomer” Perspective

• Pessimists Sound Smart, Optimists Make Money:

  • Being too cautious can mean missing out on transformative gains.
    • “There's a saying in venture capital which I quite like, which is pessimists sound smart, optimists make money…” — Campbell, [16:15]

• Is AGI Different from Past Tech Revolutions?

  • Is AI just like steam and electricity, or does it pose unique, unprecedented risks?
    • “I'd have to explain that actually creating artificial general intelligence is not just like electricity.” — Stewart, [16:52]

10. Limits of AI: Human Versatility and the “Jagged Frontier”

• Not All Jobs Replaced Easily:
  • Intelligence is multidimensional; human adaptability and creativity may preserve a “core human component” in many roles for decades.
    • “We're in a very complex, high friction world... humans are just so versatile and so well evolved to deal with the world that we actually live in.” — Campbell, [17:04]
    • “I do not think that we're heading for this frictionless plug and play... humans will have comparative advantage in a bunch of things for a very, very long time.” — Campbell, [17:34]

Notable Quotes & Memorable Moments

• On the generational risk posed by automating entry positions

  • “The problem then is… in 30 years time there are no older experienced people because these young people haven't… developed all that relationships.” — Stewart, [01:20]

• On the distribution of AI benefits:

  • “The distributional benefits, who benefits and when they benefit, I think are very up for grabs and will largely come down to questions of political economy.” — Campbell, [03:44]

• When optimism meets realism:

  • “I do think that it's for me hard not to hear this and think we would have made this argument about steam, electrification... everything that built the modern world.” — Campbell, [16:15]

• On human drive for work and meaning:

  • “I have a sort of instinct that humans really, really quite like working. We like being busy... The number of us who actually would genuinely live satisfying, fulfilled lives reading Shakespeare... I don't think that universal basic income or anything like it can be the answer.” — Stewart and Campbell, [11:05–12:12]

In Summary

The episode delves deeply into the profound, uncertain changes AI is poised to deliver to the world of work. Campbell is cautiously optimistic, emphasizing the adaptability and desires of people and the importance of the UK being an early adopter rather than a laggard. Stewart voices anxieties over lost dignified work, inequality, and the lack of truly meaningful alternatives for displaced workers—while warning that history provides examples of “progress” that did not yield better lives for ordinary people.

Throughout, the hosts underscore that AI’s societal impact won’t just be determined by the technology itself but by political choices, economic structures, and—crucially—the collective imagination of what kind of working future humanity actually wants.

Important Timestamps

• [01:20] — How AI threatens entry-level roles, leading to long-term skill shortages
• [02:31] — The Engels Pause: productivity up, living standards stagnant or down
• [03:44] — Why AI outcomes are deeply political
• [04:07] — Manufacturing: productivity surges but wages fall
• [07:25] — Why retraining isn’t a simple solution
• [09:12] — Loss of dignified, well-paid work
• [11:05] — Universal Basic Income: skepticism and limits
• [12:52] — Economic concentration: risk of AI “trillionaires”
• [13:10] — Historical evidence for broad diffusion of benefits
• [14:07–15:20] — Could (and should) we stop AI if it’s harmful?
• [16:15–17:34] — Is AI really different? Room for optimism and human adaptability

Listen to the full discussion and more in their series at therestispolitics.com.