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Introduction
At this year’s Google I/O, Demis Hassabis, CEO of DeepMind, made a bold prediction:
“We are less than a decade away from achieving artificial general intelligence (AGI).”
He further addressed students entering college, stating:
“The world you are entering will undergo major transformation due to AI.”
“New, more valuable, usually more interesting jobs get created.“
“Immerse yourself now and strive to become a sort of ninja using the latest tools.”
Similarly, OpenAI CEO Sam Altman has repeatedly downplayed concerns about job loss. When asked in various interviews, he confidently stated:
“I’m not worried. New kinds of jobs will emerge.”
These statements, often delivered with calm conviction, are meant to reassure. To give the impression that we’re simply at the cusp of yet another industrial revolution, where old jobs vanish, but new and better ones take their place.
But something about these narratives doesn’t sit right with me.
As a father of two, currently navigating a challenging job market, I find these assurances increasingly unconvincing.
My passion lies in AI and machine learning, particularly in classical approaches beyond just large language models (LLMs). Yet, it’s evident that LLMs are the primary drivers of current disruptions, rapidly automating tasks across various industries.
This “blog entry” is my attempt to examine that illusion, understand the psychology and motives behind it, and ask the uncomfortable questions:
What if this time really is different? What if the jobs aren’t coming back?
A Brief History of Work: From Muscle to Mind
To understand what’s happening today, it helps to take a quick look at where we’ve come from.
Before the industrial revolution, most people worked with their hands. Farming, craftsmanship, trade, life was local, physical, and slow-moving. Jobs were tied to nature, to seasons, and to inherited skills. It wasn’t easy, but the rules of survival were simple: work the land, make things, sell things.
Then came machines.
The industrial revolution replaced muscle with mechanical power. Entire categories of labor disappeared almost overnight. But new jobs did emerge. In factories, logistics, engineering, and later in management and administration. Humans moved from fields to cities, from manual work to machines, and eventually into offices.
Over time, the service sector became the backbone of modern economies. Education, healthcare, retail, media, finance. All jobs that required communication, empathy, and decision-making. Work was increasingly about using our brains, not our bodies. For a long time, it seemed like these kinds of jobs were safe from automation.
And now? We’re standing at the edge of a new kind of disruption. One that doesn’t just replace physical labor, but cognitive effort too. AI systems, especially those powered by large language models, are starting to take over tasks that once felt uniquely human: writing, summarizing, planning, coding, designing, even reasoning.
This isn’t just another shift. It feels like something fundamentally different and far more unpredictable.
1. The Great Promise: “New Jobs Will Appear”
If you listen to tech leaders today whether it’s Sam Altman, Demis Hassabis, Mark Zuckerberg, or Sundar Pichai you’ll hear the same message over and over:
“Yes, AI will change everything — but don’t worry. It will create new kinds of jobs we can’t even imagine yet.”
It’s a comforting promise. And it’s everywhere.
At conferences, in interviews, in blog posts and open letters, this idea gets repeated like a mantra. Altman often says he’s “not concerned” about job losses because new roles will emerge, just like they always have. Hassabis recently told students that AI will lead to “more valuable and interesting work.” And Zuckerberg claims that AI will unlock human creativity by automating the boring stuff.
But here’s the thing: no one ever really explains what these new jobs will be. There are rarely examples, no numbers, no roadmap: just vague ideas like “AI ethics advisor,” “prompt engineer,” or “digital experience designer.” These are niche roles, often requiring advanced technical backgrounds, and they certainly don’t scale to millions of people.
So why is this idea repeated so confidently?
Because it serves a very clear purpose: reassurance.
It helps calm fears, silence critics, and, most importantly, legitimize the rapid deployment of technologies that could reshape entire job markets. If people believe that disruption is temporary and will soon be followed by a boom in new opportunity, they’re less likely to push back. Less likely to question. Less likely to demand regulation or a societal plan.
It’s a kind of moral shield for the builders of these systems.
“Yes, we’re changing the world but don’t worry, it’s for the better.”
And maybe some of them truly believe it. But whether it’s belief or strategy, the effect is the same: the world is being transformed under the assumption that things will just work out in the end.
But what if they don’t?
2. Why This Promise No Longer Holds Up
It’s true that in the past, technological revolutions have wiped out jobs and then created new ones. When machines took over agriculture, people moved to factories. When factories became automated, people shifted into service jobs, creative industries, or tech.
But here’s the problem: this time, the pattern may not repeat. The nature of what’s being automated is fundamentally different.
AI, especially the kind powered by large language models, isn’t just automating tasks, it’s automating thinking (Please do not confuse the term thinking with Consciousness and Sentience). Writing emails, making presentations, summarizing research, debugging code, designing logos, answering customer support tickets or things that once required a human brain are now being done in seconds by a machine.
And these systems don’t need breaks. They don’t ask for salaries. They don’t unionize or get tired or resign.
It’s not just blue-collar jobs that are threatened. No, it’s white-collar ones, too. Jobs in marketing, journalism, design, law, software development, education. These are the very fields that grew out of previous waves of automation and now they’re under pressure themselves.
Meanwhile, the global population keeps growing. Millions of young people enter the job market every year. So we’re not just talking about replacing existing jobs, we’re also talking about failing to create new ones fast enough to meet demand.
Sure, some new roles may appear. But they’ll be specialized, technical, and limited in number. We might need a few thousand AI trainers or safety auditors. But what about the millions of people currently doing routine office work, customer service, or content creation?
This isn’t just a shift. It’s a potential mismatch between what machines can do and what humans are left with.
And let’s be honest: the companies building these systems aren’t focused on job creation. They’re focused on efficiency, scale, and return on investment. The whole point of AI is to do more with fewer people. That’s not a bug. It’s the business model.
So when leaders say “new jobs will appear,” it sounds less like a plan and more like wishful thinking.
Or maybe just a convenient story to tell while pushing forward, full speed ahead.
3. What Drives the AI Elite?
It’s easy to wonder: How can the people building these world-changing systems stay so calm? So optimistic? So sure that everything will be fine?
To understand that, we have to look at the mindset, and the world, of the people leading the AI race.
Many of them genuinely believe in what they’re doing. Demis Hassabis talks about curing diseases and solving science with AI. Sam Altman speaks of accelerating abundance and pushing humanity forward. These aren’t just PR lines, for some, they’re core beliefs. In their minds, AI isn’t a threat. It’s a gift to the world. A tool to unlock progress, discovery, and human potential.
And of course, there’s another powerful motivator: legacy and control.
The companies and individuals who lead in AI today are shaping the future — economically, culturally, politically. That kind of influence is hard to let go of. When you’re in a race to build something as powerful as AGI, it’s easy to justify moving fast and asking questions later.
But maybe the biggest factor is this:
They live in a different world.
The AI elite (the CEOs, the top researchers, the tech founders) are not affected by the disruption they’re causing. They don’t worry about layoffs. They’re not applying for freelance gigs on saturated platforms. They don’t stress over how to feed a family if the next project falls through.
They live in a bubble of abundance:
- Surrounded by other high-performers
- Supported by massive salaries and stock options
- Shielded by teams of advisors, PR professionals, and like-minded peers
- Living in places where optimism is part of the culture and where doubt is seen as weakness
This disconnect from everyday reality matters.
Because when you’re not exposed to the fear, anxiety, and uncertainty that others are feeling, it’s simply much easier to believe everything will “just work out.”
Easier to say, “people will adapt,” or “society will figure it out,” without having to explain how.
It’s not necessarily malicious. But it is dangerous.
Because when those with the most power are the most insulated from consequences, bad outcomes can unfold without anyone hitting the brakes.
So while the rest of us brace for impact, they’re racing ahead, certain they’re building the future, but blind to the fractures they’re leaving behind.
4. Why They Still Sleep Well at Night
You’d think that building technologies that might eliminate millions of jobs — maybe even reshape the very idea of human work — would keep someone up at night.
But if you watch the interviews, the keynotes, the podcasts… they seem fine. Calm. Focused. Confident.
So how do they do it?
A) They’ve made peace with the consequences — in their own way
Most AI leaders believe the benefits outweigh the risks. In their view, yes, there will be disruption but it’s a small price to pay for curing diseases, accelerating science, solving climate change, or making knowledge universally accessible. These are big promises, and they help paint the tech as a moral good.
Even if the path is messy, they believe the destination justifies it. That’s not per se evil it’s classic ends-justify-the-means thinking. But when the “means” involve destabilizing entire labor markets, the stakes are enormous.
B) They shift responsibility to others
There’s a quiet but consistent message behind many of their statements:
“We just build the tools. So it’s up to society to figure out how to use them.”
Or:
“Policymakers need to step up. We can’t solve everything.”
In a way, they’re not wrong. But it’s also incredibly convenient.
They get to launch disruptive technologies at full speed and when the fallout comes, they can say, “Hey, we warned you.”
This diffusion of responsibility makes it much easier to live with the outcomes — even if those outcomes include mass job displacement, social unrest, or growing inequality.
C) They live in a feedback loop of reassurance
When everyone around you is optimistic, ambitious, and focused on building it’s easy to believe you’re doing the right thing. These leaders aren’t surrounded by teachers, truck drivers, freelance designers, or support agents worried about their jobs.
They’re surrounded by engineers, venture capitalists, and other founders. All the people who benefit from the very disruption that others fear. It’s a world that reinforces itself.
That’s not sociopathy. It’s just structural empathy loss — where the design of your environment shields you from the real impact of your actions.
So yes, they sleep well.
Not because they’re evil. But because their world is designed to make them feel like heroes, not disruptors.
They aren’t burdened with the fear of being replaced by a chatbot.
They aren’t worrying how to explain a layoff to their kids.
They aren’t feeling the first tremors of instability in the freelance or contract market.
We are.
And that’s exactly why their confidence should make us nervous.
5. What This Means for the Rest of Us
While the AI elite pushes forward with optimism and a sense of purpose, many of us are starting to feel something very different: uncertainty, pressure, and a creeping sense that the ground beneath our feet is shifting.
Because it is.
What’s happening isn’t just another “wave of innovation”. It’s a structural shift in how value is created, who creates it, and who gets left behind.
A) This is not a normal cycle of job change
In past revolutions, new technology replaced human labor, but it still needed human judgment, coordination, creativity, or service. That’s where the new jobs came from.
But now, we’re building systems that can simulate those very human traits. They can analyze, write, design, code, even teach, sometimes well enough to compete with real professionals. So the old safety net “we’ll just move into more complex jobs” is wearing thin.
And the new safety net?
It doesn’t exist yet.
B) There’s no plan for mass transition
Let’s be honest: governments are not prepared for what’s coming.
There are no national strategies for large-scale retraining, no serious discussions about universal basic income at scale, no clear vision for how to maintain dignity and purpose in a post-labor world.
And while some companies invest in “upskilling” programs, these often target only a small, already tech-savvy population and not the millions whose jobs are quietly being squeezed.
The people developing this tech are racing ahead, assuming that others, policymakers, schools, markets, will somehow catch up.
They won’t. At least not fast enough.
C) The disruption is already visible
We don’t need to look into the distant future. The cracks are showing now.
Freelancers losing clients because chatbots now do “good enough” work.
Companies freezing hiring because AI tools are filling the gaps.
Job platforms flooding with applicants for fewer and fewer roles.
And professionals (like me) who are deeply interested in AI, trained in machine learning, and still struggling to land stable work in an oversaturated, shifting market.
This isn’t science fiction. It’s early-stage reality.
So where does that leave us?
It leaves us in a position that feels disturbingly familiar:
Watching a small group of people steer the world in a direction that benefits them — while the rest of us are told to adapt, upskill, or hope for the best.
But blind faith in progress is not a strategy.
And reassurances from billionaires are not policy.
6. Conclusion: Time for a New Kind of Honesty
The story we’ve been told that new technology always creates new jobs, that everything will balance out, that progress takes care of its own mess, is starting to fall apart.
Not because technology is evil. Not because innovation should stop. But because this time, the scale, the speed, and the nature of the disruption are different.
We’re not just automating physical labor. We’re automating intelligence or at least something that looks very much like it. And that challenges the very foundation of how modern societies work: how we earn money, how we contribute, how we find meaning and status.
The leaders of the AI industry are not likely to fix this for us. Not because they’re malicious, but because they’re too far removed from the consequences. They build systems to solve problems and not to preserve social contracts. Their job is to push boundaries, not to draw them.
And so the responsibility falls on the rest of us. As citizens, as voters, as thinkers, as builders.
We need to demand a new kind of honesty:
- Honesty about the limits of reskilling.
- Honesty about how many jobs might truly never come back.
- Honesty about who benefits — and who doesn’t.
- Honesty about what kind of society we want in a world where human labor is no longer the engine of value.
This doesn’t mean stopping AI.
It means steering it: consciously, collectively, and with courage.
Because if we don’t, we may find ourselves in a world that’s more efficient, more powerful, and more “advanced” but one where millions of people are left without a place, without a purpose, and without a voice.
That future isn’t written yet.
But the time to shape it is now.
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