If you've read my previous pieces, you know I frequently share my thoughts on how AI will shape our society going forward. But I haven't reached a final conclusion on this subject. At my core, I'm deeply curious whether artificial intelligence will ultimately turn out to be a blessing or a curse for us. There are already countless articles by experts on this same topic. Bill Gates keeps painting a rosy picture of a happy future where humans no longer have to work as AI advances. On the flip side, other people predict AI will snatch up every job and leave everyone except a tiny minority in absolute poverty. The actual future will likely land somewhere in the middle, between paradise and dystopia.
I once read an article whose author I honestly do not remember anymore, and it argued something that stuck with me. It said that while AI will undoubtedly bring us huge convenience, that very convenience might make our labor far more exhausting. Why would that be the case? Here's my take.
The Rise Of Artificial Busywork
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| Fake Work Multiplies When Tasks Get Easier |
First off, AI can generate an absurd amount of fake work. Fake work refers to the useless tasks you do just to make things look good. In any organization, fake work inevitably sprouts up as you go about your business. Holding weekly meetings that accomplish nothing, or dressing up a slide deck just to impress your boss, are classic examples in a corporate setting. The problem is that fake work can actually multiply precisely because of technological progress. If computers get better and writing reports becomes easier, you might suddenly be expected to write much more detailed and expansive reports than before. It's not even necessary work. You're just forced to do more simply because the task itself got easier. I have already watched this happen at my own company. Since a few of us started using AI to draft reports faster, the expected length and polish of those same reports has quietly crept up, so the actual time saved turned out to be far smaller than it looked at first. We'll see the same thing happen with AI more broadly. For instance, if adopting AI makes writing meeting minutes effortless, you might suddenly be required to record minutes for the most trivial meetings that never needed them before. The less an organization genuinely reflects on the nature of its work, the more it will endlessly inflate this kind of fake work.
The Death Of The Specialist
Furthermore, as AI develops, it will weaken our current system of division of labor and bring forth a far more integrated way of working, one that could pressure individuals to possess exceptional skills across the board. It's no exaggeration to say the history of modern industry has largely been the history of the division of labor. In 1913, Henry Ford was inspired by the conveyor belt systems used in slaughterhouses and invented a new automobile assembly method where each worker only performed a specifically assigned task along the belt. With that single innovation, the Ford factory slashed the assembly time of a single car from twelve hours and thirty minutes down to an astonishing one hour and thirty three minutes. It was an earth shattering innovation at the time, and the success of this division of labor spread rapidly to other fields.
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| Charlie Chaplin in Modern Times, 1936. Division of labor in its purest form. Via United Artists |
On one hand, the division of labor made work significantly easier. In the past, assembling a car was highly skilled labor that only someone who understood the entire blueprint could pull off. But once the conveyor belt was introduced, everyone just assembled their one specific part. That meant people could be thrown right into the factory and start working even without deep knowledge or high skill levels. This division of labor created a massive influx of easy jobs. On the other hand, it also created countless jobs where people specialized deeply in remarkably narrow fields. As industries became increasingly fragmented, the role of experts who spent their entire lives researching just one area and performing at the highest level within it became crucial. This was the era of division of labor we all grew used to, where you could learn one major, do the same job your whole life, and make a decent living without much trouble. If nothing had changed, I probably would have just built my whole career on this path as a network engineer until the day I retired.
The Burden Of Being Everything
But the advancement of AI is about to upend that reality entirely. In the future, AI will possess at least intermediate expert level skills across multiple fields at once. That means one person will be able to do the work that used to require several. We're already seeing this happen in software development. It's extremely common now for a single person to use AI to comprehensively handle the work that used to be split between frontend, backend, and DevOps specialists. I even used vibe coding to run a business by myself that would normally have required a whole team. I truly believe this same phenomenon can easily show up in any other field. Of course, experts won't become entirely obsolete, but the number of jobs requiring fewer experts, or no experts at all, will keep climbing.
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| Sitting still while the world keeps moving forward without you |
The real problem is that this might actually make work much harder. In the past, you only had to dig deep into your one area of expertise. But moving forward, you'll increasingly hear people say you have no competitive edge if you can't do everything yourself. You'll face the crushing pressure of not being able to safely root yourself in one field, while being pushed to become an integrated talent who constantly studies every field and develops a comprehensive perspective. Depending on the person, this could drastically raise the actual difficulty of their labor. People whose aptitude is perfectly suited to doing just one thing will feel genuinely overwhelmed when suddenly asked to juggle a wide variety of tasks. As occupational diversity expands from a broader perspective, we might reach a point where making a living from a single job becomes impossible, and holding down multiple jobs at once becomes the norm rather than the exception.
If you are terrified by the idea of having to do the work of an entire team by yourself you should definitely read Small Companies Have The Real Advantage With AI. It explains why being forced to operate solo with artificial intelligence is actually a serious structural edge rather than a weakness.
The Mandatory Creativity Trap
There's undeniably a positive side to this shift. The philosopher Karl Marx argued early on that during the industrial era, workers only performed simple repetitive tasks, which stripped them of the chance to exercise their creativity as humans and left them alienated, unaware of what they were even building. If AI shifts our work style from division back to integration, people might finally oversee their entire process, exercise real creativity, and find genuine meaning in their work again. However, this also leaves considerable room for the burden of labor to increase, because exercising creativity might shift from an option into a strict obligation. In the past, you could work even if you had very little creativity to offer. Now, if you don't actively exercise it, you might lose your competitive edge in the job market entirely. I notice this pressure in myself whenever I sit down to write one of these columns, since AI can draft the structure but the actual point of view still has to come from me every single time. We'll have to think long and hard about whether this actually makes for a better situation for humanity.
The End Of The Training Wheels
Finally, an AI expert friend of mine told me something fascinating. AI can fundamentally change the way we learn, but this might also end up exhausting us. They predict AI will shift our learning methods away from rote memorization toward a heavily practice oriented approach. In the past, when you joined a company, you'd memorize rules and terminology, study the workflow, and slowly apply it as you worked. But AI lets you simulate the work almost immediately. For example, if I were a counselor in the past, I'd have had to learn all the necessary counseling knowledge before my first session. Now I can practice counseling right away with an AI, as many times as I want. I can just do the work and ask questions about whatever I don't know as I go. If I'm learning design, I don't need enough knowledge to finish a project from scratch. I can just use AI to push a single project all the way to the end immediately, filling in the gaps by asking questions along the way. Humans improve their skills far faster when they face a situation directly rather than just studying it in their heads. That's why AI is expected to drastically shorten the time it takes people to learn what they need for a job.
The unsettling part here is that the friendly training systems of the past might vanish completely. Until now, you could handle a job just fine as long as you properly completed the training you were given. But moving forward, the ability to actively communicate with AI and learn in a fully self directed way might become a genuine requirement. Personally, I think this sounds exhausting just to imagine. Let me explain why.
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| Empty grounds where corporate training once thrived at scale |
A few years ago, GE put its massive Crotonville training center up for sale, a facility that held real symbolic weight in the history of American corporate training. It eventually sold for a fraction of what it once cost the company to run and maintain. At its peak, GE was spending around one billion dollars a year on talent development, and that training center sat at the very heart of it. They gathered employees and brought in experts for massive group training sessions. This model worked because in the past, knowledge was monopolized by a small minority. The job of the training department was to bring in brilliant instructors and spoon feed knowledge to employees. But the situation has flipped entirely now. Information and knowledge are overflowing everywhere, and YouTube is often better than a decent instructor. You can even use AI to simulate real situations and level up your skills incredibly fast. That's why traditional training center education is rapidly fading away.
This shift will open up countless possibilities. People with strong self directed learning skills will stop wasting time on useless training and level up a lot more efficiently than before. The problem is that not everyone actually has this ability. There are certainly plenty of people who feel much more comfortable with traditional education methods. Self directed learning requires you to constantly draw on a huge amount of passion and creativity on your own, so in many cases it can wear you out more than simply studying ever did. To survive in the market, people might have to force themselves into fierce, practical learning environments that are much more brutal than anything they experience today.
If you feel genuinely overwhelmed by the reality that you now have to direct your own education from scratch I highly recommend reading Why Learning How to Learn Is the Only Meta Skill You Need in the AI Era. It breaks down the mindset shift you need to survive when the traditional training wheels are taken away permanently.
As I've said, AI will undoubtedly bring massive innovation, but that doesn't necessarily mean it will make our labor any easier. It might actually generate a staggering amount of exhausting work. Unless there's a major political shift, it will likely widen the wealth gap significantly and create an insurmountable divide between those who possess integrated, creative abilities and those who don't. I truly believe that preparing for this future means working hard on simple self improvement, sure, but it also means deeply understanding the rapidly changing job environment of the coming AI era. Like I said at the very beginning, this topic is nowhere near settled, and it's a flow we all need to keep watching closely.
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