Artificial intelligence (AI) now seems inevitable. It comes with a raft of promises, from transforming how we produce knowledge and run industries to making life easier. But will the reality match the hype?
AI’s rise as a defining feature of the Fourth Industrial Revolution recalls stories about the human costs of early industrialization, from Oliver Twist, a novel set in industrial England, to Die Weber, a drama depicting the weavers’ uprising in Silesia, Prussia.
In Oliver Twist, for instance, the Industrial Revolution in the 19th century leaves working-class lives in ruins. Rapid urbanization floods cities with the unemployed, while children become victims of labor exploitation.
Meanwhile, Die Weber tells the story of weavers paid far below a living wage, unable to compete with textiles produced by mass machinery. Their meager earnings trap them in poverty, leaving them unable even to afford basic food.
From these two accounts, I find myself asking whether the AI revolution will bring similar consequences, or whether its effects will be harder to see, and even more frightening.
It is easy to imagine companies replacing workers with AI overnight, setting off mass unemployment, widening poverty, and hunger in the streets. But I don’t think it will be that straightforward.
I believe some jobs will be replaced by AI, but that is not the worst of it. Something more frightening lies ahead. It will not be visible at a glance. Like water seeping into a wall, the damage builds slowly, rotting it from within and weakening the pillars of the house.
From the outside, everything looks normal, but inside it is falling apart. The rhythms, relationships, and structures of work, even the way wages are set, can make people unaware that they are being controlled by machines that generate profit only for business owners.
Ride-hailing drivers offer a clear example. Their work is governed by algorithms. Routes, fares, and even the chance of getting an order are no longer shaped by human negotiation but by invisible machine decisions. The result is a workforce tethered to phone screens. If a driver’s performance slips, whether from rejecting orders or being slowed by bad weather, the system quietly downgrades their visibility.
People still do the work behind the handlebars, but software automation now decides their livelihood and pay.
White-collar workers feel it too. They use AI to write, draft contracts, analyze and process data, and produce designs at breakneck speed. Projects move faster and more efficiently, and productivity rises. Managers are pleased, but workers struggle to keep up. Targets go up, hours do not go down, and pay does not rise with them.
This is what scholars call work intensification.
Even when their jobs are not at risk, the pressure does not ease. They are pushed to keep pace with automation that runs around the clock, taking on extra tasks just to keep the machines fed with a constant stream of data.
Entry-level workers are feeling the squeeze too. The usual pathways into work are narrowing, as many repetitive junior tasks can already be done by AI.
In the United States, for instance, law graduates are finding it harder to land jobs because basic tasks such as drafting contracts can now be handled by AI. Copywriting is no exception, with fewer openings as social media captions can be generated in seconds.
And yet entry-level jobs are crucial. They are the first rung on the ladder, where people learn the ropes and build real workplace skills. When that rung disappears, the situation becomes worse than the old meme: you need experience to get a job, and you need a job to gain experience.
Another thing I’ve felt firsthand is the endless need to adapt. The skills I once acquired to stay relevant quickly became ordinary. Mastering Microsoft Office was once an asset. Then writing well became the differentiator. Later, using data strengthened my analysis. Today, with AI, anyone can do the data work faster and more accurately. It doesn’t feel special anymore.
This is similar to what programmers are experiencing. They once rode the tech boom, but now they are starting to feel threatened too, as AI allows non-coders to build websites, apps, even games with a single prompt.
That is why I was perplexed when Vice President Gibran Rakabuming Raka held a competition to create AI-generated animations. What purpose did it serve?
At some point, I realized that for all my effort to keep up with technology, the truly irreplaceable person is the handyman I call every rainy season to fix a leaking roof. AI can’t pinpoint where the seepage in my kitchen is coming from, or trace the source of the water dripping from my living-room ceiling.
Skills like this are not easy to automate because they are bound up with materials and real-world conditions, and they require on-the-spot improvisation. The maddening part is that this kind of work is rarely well paid.
Isn’t that ironic?
Workers are left facing the same unpleasant choice: get exploited while working with AI, or get paid poorly for work AI still can’t do.
Of course, this is not AI’s fault.
AI is already helping drive medical breakthroughs. Researchers, for example, have created an AI tool that acts as a “copilot” for gene editing, speeding up the search for new treatments for genetic diseases. It has also been used to improve early detection of cancer and accelerate the development of more targeted treatments.
The question is, who will have access to such advanced treatments? Most likely, only those who can afford them. If the technology ever reaches Indonesia, the cost would probably be too high to be covered under the national health insurance scheme administered by BPJS Kesehatan.
And that is the problem. Unequal access turns AI into yet another tool for squeezing workers.
AI is creating a working life that looks normal on the surface, even as workloads, inequality, and insecurity grow beneath it. This is the paradox of AI’s promise. It offers efficiency and growth, but without fair governance, its benefits will be concentrated in the hands of a wealthy few.
I agree with Geoffrey Hinton, often called the “godfather of AI”, who has argued that AI development should be slowed down because we are not ready. A technology this powerful is being deployed within the same global system where injustice remains the central problem. As a result, it brings little benefit except to the ultra-rich.
We need to change the rules of the game.
Worker protections, pathways for entry-level workers, more equitable access to technology, auditable algorithmic transparency, and guaranteed collective bargaining rights should come first. Fair AI deployment can follow.
This essay is the introduction to our #AutomationFever series.
