Richard Golian

1995-born. Charles University alum. Head of Performance at Mixit. 10+ years in marketing and data.

Castellano Français Slovenčina

Manage subscription Choose a plan

RSS
Newsletter
New articles to your inbox

Article

The AI Revolution: Time to Let Real Robots Do Robotic Work?

AI revolution restoring human work
Richard Golian
Richard Golian · 2 683 reads
Hi, I am Richard. On this blog, I share thoughts, personal stories — and what I am working on. I hope this article brings you some value.
Listen to this article
0:00 / 0:00

A few days ago, I posted this on social media:

"I heard an idea that stuck with me: Agricultural, industrial & digital revolutions made humans more like robots. The #AI revolution might finally let real robots do robotic work— so we can get back to being human. Not such a crazy thought."

The idea that artificial intelligence could, paradoxically, liberate us from robotic work imposed on us by past revolutions does not always land well with everyone. One commenter replied:

"Somewhat absurd logic. If labour had humanized apes, do I understand correct that handing labour over to robots would return humankind back down among the apes?"

To which I responded:

"The revolutions turned most jobs into repetitive tasks—operators, accountants, salespeople. Before, beyond getting food, we did music, art, sex. I don’t get what the apes have to do with it."

And I got this reply:

"'I don’t get what the apes have to do with it.' Everything. Before we hand all the bullshit work over to the machines, we will cease being able to do everything that differentiates us apart from the apes..."

This exchange intrigued me so much that I decided to explore it further in this article.

How I See It: How Agriculture, Industry, and Digitalization Made Our Work Robotic

Each revolution fundamentally reshaped the way we live and work.

The Agricultural Revolution taught us to function in cycles — tied to the land and seasons — requiring regularity and routine. Yet we could still live as relatively independent units.

The Industrial Revolution, however, anchored us more firmly into rigid structures. We became cogs in vast machines: factories, assembly lines, narrowly defined roles.

The Digital Revolution moved work onto screens, but the core principle remained the same: repetition, efficiency, performance. In many cases, humans behave like robots, and their work feels increasingly robotic.

Thinking about my own profession, the most robotic part of my work lies in filling out spreadsheets and reports. That is why I push hard for automation — not because data are not important, but because I want to spend more time interpreting them rather than mechanically processing them.

The way things are developing, it is likely that even operational data interpretation will soon be handled by machines. In some industries, it is already happening. Companies will probably make strategic choices to delegate even more decisions to machines — especially in repetitive scenarios.

If I follow this line of thought, I realise that virtually every task I do with my mind could eventually be automated. Which brings me back to the main question: Could the AI revolution actually bring us back to a more human way of living?

Continue

Join the Library

Full access to my thoughts, personal stories, findings, and what I learn from the people I meet.

Join the Library — €29.99 per year
Or just this article · €2,99

Get the full article by email and feel free to reply if you want to discuss it further.

Visa Mastercard Apple Pay Google Pay

Summary

Every revolution — agricultural, industrial, digital — turned human work into something more mechanical. AI could reverse that. Not by replacing us, but by taking over the robotic parts of our jobs, freeing us to do what is actually human. Music, art, creative expression.

Common questions on this article's topic

How did past revolutions make human work more robotic?
Each revolution reshaped work in ways that reduced human autonomy. The Agricultural Revolution tied people to seasonal cycles and routine. The Industrial Revolution, as documented by historian E.P. Thompson, replaced task-oriented work with strict clock-time discipline — turning humans into cogs in factory machines. The Digital Revolution moved work onto screens but kept the repetitive nature. In the article, this trajectory is presented as a long drift away from what makes us human.
Could AI actually reverse this trend and make work more human?
This is the central idea of the article. If AI automates the repetitive, mechanical parts of work — filling spreadsheets, processing reports, routine optimisation — what remains could be more genuinely human: creativity, curiosity, relationships, and meaningful projects. Research supports this as more than utopian thinking: businesses implementing AI for repetitive tasks report 10 to 20 hours saved per employee per week, with that time redirected toward strategic and creative work.
What does it mean to be human in the context of AI?
In the article, being human means the ability to be curious, to create, to make art, to build relationships, and to live in ways that make sense to ourselves — not just to fulfill routines dictated by external systems. It also means striving to understand ourselves, because human existence relates not just to the external world but to our inner world. This definition shapes the argument that AI could liberate rather than replace us.
Will AI-generated art replace human art?
In the article, the answer is no — because art is not just about the final product. The example of a sister who paints not to impress but to express her inner world illustrates the point: even if AI produced a more perfect painting, it would never carry the story and lived experience behind human creation. This perspective is supported by aesthetics philosophy, where imperfection and authenticity are valued precisely because they feel human and honest.
Did pre-industrial humans really spend more time on creative activities?
Historical research supports this. Pre-industrial workers had significantly more discretionary time — approximately 1,600 hours of work per year compared to over 3,000 after industrialisation. Work and leisure were organically mixed, with music, storytelling, and community activities integrated into daily life rather than compartmentalised into evenings and weekends. In the article, this is referenced through the observation that before industrialisation, beyond getting food, people did music, art, and lived in community.
Is this vision realistic or just optimistic?
The article acknowledges uncertainty. Whether AI liberates us or further constrains us depends on choices that have not yet been made — about who controls the technology, how the economic system adapts, and whether humans remain at the top of the decision-making chain. The vision of more human work is presented as one possible storyline, not an inevitability. But the underlying logic is sound: if machines handle what is mechanical, what remains is, by definition, more human.
Richard Golian

If you have any thoughts, questions, or feedback, feel free to drop me a message at mail@richardgolian.com.

NEWSLETTER
What I write about, what I am working on, what I learned.
Sent the first Sunday of the month. Unsubscribe anytime.

Related articles

Full AI agents or fully offline.

Four days in Catalonia. No computer, no AI, almost no social media. I bought this notebook so that I could write down what I would think about, and what I would come across and learn on the trip.

10.5.2026·323 reads
Will AI take my job?

Will AI take my job? A certified Google trainer told me in June 2024 that my profession would cease to exist. Twenty-two months later, my job title has not changed — but ninety percent of what I do during the day is different. I have delegated more of my thinking to AI agents than I thought possible. I am not afraid. This is why, and what it means for anyone asking the same question.

23 April 2026·366 reads
An Idea About the Future Everyone Should Hear Today

It’s a strange feeling. I haven’t fully processed it yet.

8 June 2025·1 274 reads

More articles

Where the Money Goes When AI Takes the Work

Prague, 13 May 2026. On my way to work I started thinking about something that stayed with me for days. If most routine work on a computer disappears in the next ten years, and a large share of repetitive manual work disappears with it, what happens to the flow of money? Who pays whom for what? Which economic layers will exist, how large will they be, and what relationships will run between them? This is the six-layer map I sketched as an answer.

15 May 2026·102 reads
Building an AI Stock Market Prediction System That Grades Itself

I am building an AI system to predict the S&P 500. It runs on my own machine, uses free public data — yfinance, FRED, the Shiller dataset — and grades every forecast against reality. This series documents the build itself: the decisions, the methodology, the mistakes. What I will eventually share from the running system is a separate question, and an honest one.

26 April 2026·612 reads
AI sales forecast: 9 traps so far

Yesterday I could not tear myself away from the computer. When I lifted my head, it was half past eight in the evening. I had been sitting alone upstairs for about three hours.

25 April 2026·585 reads
€50,000 Quote vs. Two Hours with Claude Code

One hour. Fifty-five minutes. That is how long it took to build what a Czech software firm had quoted at over €50,000. I built it with Claude Code. Not a prototype. Not a proof of concept. A working tool — the one the company actually needed. By the evening of the same day, it was running on staging. This is not about Claude Code. It is about what Claude Code exposes.

18 April 2026·723 reads
Is AI Making Us Dumber?

I have conducted roughly one hundred and fifty practical interviews over the past four years. Fifty for data specialist roles. A hundred for advertising and performance marketing specialists. Almost every one of them involved sitting down with a candidate over a practical task — something close to a real problem we actually need to solve at the company. Not theory. Not trivia. Applied problem-solving. Over time, I started noticing a pattern.

14 April 2026·674 reads
What AI Hides From You

Before you can teach AI to understand anything, you need to see what it is hiding from you.

11 April 2026·672 reads
When Your AI Agent Joins the Team

The moment other people needed access to it, the problem changed completely. It was no longer about whether the agent could learn. It was about who gets to teach it.

8 April 2026·827 reads
Training an AI Agent That Learns Between Sessions

I wanted to build an agent that doesn't just assist. One that acts.

4 April 2026·880 reads
Local AI Model Limitations: Why I Switched from Ollama to Claude for Autonomous Agents

This is what I learned about local vs cloud AI, and why I switched to Claude Code.

3 April 2026·1 477 reads
NEWSLETTER
What I write about, what I am working on, what I learned.
Sent the first Sunday of the month. Unsubscribe anytime.