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Part 2 of 3: The Economic Earthquake: Jobs, Robots & the Illusion of “Abundance”

Michael Lee, MBA
2 days ago
4 min read

Updated: 1 day ago

(My reflections after watching Tristan Harris on Diary of a CEO)

Humanoid robots used to feel like a distant science-fiction idea—something we’d joke about, not something we’d have to plan our lives around. But after watching Tristan Harris explain how fast robotics and AI are converging, I realised this isn’t a “one day” conversation anymore. It’s a “we should probably understand this now” conversation.

And frankly, I’m not an expert in AI safety or robotics. I’m just a data professional trying to make sense of the world we’re accelerating into. What I heard in that interview made me pause—not because it was sensational, but because it was… practical.

1. Robots Are Not Coming — They’re Already Here

Harris talked about Elon Musk’s ambition to deploy millions (and eventually billions) of humanoid robots—machines with physical bodies, hands, legs, sensors, and a brain powered by advanced AI models.

The part that got me wasn’t the robotics…It was Musk’s claim that a robot could someday be 10 times better than the best surgeon on earth.

Not “assist surgeons. "Not “help in hospitals. "But completely replace them.

If this is true—even halfway true—it’s also true for:

drivers
factory workers
logistics staff
cleaners
retail workers
security positions
“knowledge workers” like analysts, writers, designers

This isn’t automation of tasks anymore. It’s automation of entire categories of human effort.

And unlike past technological shifts, this one hits both physical labour and cognitive work at the same time.

2. Why This Isn’t the Usual “Jobs Will Come Back” Story

People often respond to automation concerns with the argument:

“We lost farming jobs. We lost elevator operators. We’ll just find new jobs.”

Historically, that’s been true. But AI changes the equation because it’s not automating one field at a time — it’s learning all human cognitive tasks at once.

Humans can’t retrain faster than an AI can retrain itself. Humans can’t copy themselves a million times overnight. Humans can’t download every book ever written in 5 minutes.

This isn’t a competition. It’s a mismatch.

And according to data Tristan cited, AI-exposed entry-level job losses have already hit double digits. Not in theory. In payroll data.

This is the first time in economic history where technology threatens to become cheaper, faster, and more scalable than any human, in almost every productive role.

3. The UBI Question We’re Not Ready For

Tristan brought up Universal Basic Income (UBI)—a concept where the government pays everyone a baseline amount to live on.

Before watching, I used to think UBI might actually be a realistic solution.

Now? I’m not so sure.

Why?

Because if AI concentrates economic power into the hands of a very small number of companies or countries, the idea that those beneficiaries will voluntarily redistribute wealth… feels optimistic.

When in history has:

a small group gained massive economic advantage
and then voluntarily shared it evenly with 8 billion people?

It has never happened.

The intention of UBI might be noble. The incentive to actually pay for it might be almost nonexistent.

That part hit me hard. Because it means the real challenge isn’t just job loss. It’s the transition period, where millions lose work long before any meaningful safety net appears.

4. The Competitive Trap: “If We Don’t, Someone Else Will”

This was the part I personally found most uncomfortable.

Businesses will adopt robots not because they want to replace people, but because:

their competitors will
overseas companies will
investors will demand it
margins will depend on it
consumers will expect it

If Company A automates and Company B doesn’t, Company B loses. If Country A automates and Country B doesn’t, Country B loses.

It’s not evil. It’s incentives.

Tristan calls this the xenithification of competition — the idea that AI accelerates competitive pressure to the point that companies and countries feel forced into actions they’d otherwise avoid.

And this leads to an uncomfortable truth:

Even if we wanted to slow down, the economic system might not let us.

5. So What Happens to Meaning?

What shook me the most weren’t the job numbers or the robot predictions.

It was a simple question:

“If AI and robots can do almost everything… what remains uniquely human?”

Connection. Empathy. Presence. Love. Community. Caregiving. Art. Identity. Story.

Not very GDP-friendly outputs.

But perhaps more essential than ever.

The interview didn’t push me toward panic. If anything, it pushed me toward introspection: What do we value when productivity is no longer a uniquely human advantage?