Tomorrow, will you be more capable or less?
Human augmentation, deskilling, skills
The unsettling question
The same tool can make you a better pilot or a worse driver.
GPS gave you the whole city and cost you your sense of direction. Calculators freed you from mental arithmetic and weakened your ability to handle simple numbers. Spellcheckers erased your mistakes, along with some of your memory for spelling.
AI promises to make you more capable: a better writer, designer, analyst or doctor. Faster, more accurate, more creative. The promise is real.
The question is whether you will come out of the experience with one more skill or one less.
The starting point
When people use a tool, several things happen at once: they complete the task, form neural connections, and practise a skill (or let it fade). For decades, we invented tools that did the tedious work while leaving us the essential task.
AI can perform that essential task itself, leaving us the tedious work of rereading, validating and correcting.
So the question is no longer “Will AI replace my job?” It is: “What will I keep, lose or learn as I do my job with it?”
Augmentation or deskilling depends on the tool’s design (does it let you act? does it let you learn?), the user’s approach (do they check? do they understand what they approve?), and the organisation’s culture (does it train its people or make them dependent?).
Tomorrow
Tomorrow, students will enter the job market having written all their essays with AI. Junior professionals will train for jobs they have never practised without an assistant. Senior professionals will gradually lose skills they once mastered. If junior recruitment stops, eventually there will be no senior professionals either.
The question will then become: what does it mean to be a competent human in 2030? Which skills must we preserve at all costs, and which can we safely delegate?
Possible angles
Reading to get started
Garry Kasparov — Deep Thinking
The chess champion defeated by Deep Blue explains how he developed “centaurs” (human + AI), and what they taught him about collaboration.
Erik Brynjolfsson — The Turing Trap
A short, powerful article distinguishing automation (replacing) from augmentation (enhancing).
Daniel Susskind — A World Without Work
A way to think about a profession as a collection of tasks, some of which will move to machines.
Research on cognitive offloading (Sparrow, Storm, Risko)
To understand what happens in our minds when we delegate to a tool, and what we lose.
Harry Braverman — Labor and Monopoly Capital
A classic work on deskilling (loss of skills) that sheds remarkably precise light on today’s situation.
Recent articles on AI use among students and junior developers
To hear from people already riding the wave: what they gain and what they lose.
Try it yourself
- Write a short text without AI. Then write the same text with it. Do you notice a difference in the result, but also in your thinking?
- Disable autocomplete on your phone for three days. Note what comes back and what fades.
- Do a calculation in your head that you would usually write down. Note how long it takes and how much confidence you have in your own mind.
- Identify one skill AI has helped you gain this year, and one it is causing you to lose.
Which context would you anchor it in?
The tension between augmentation and deskilling plays out differently when training students, employees or creative professionals.
Higher education
Students, learning with AI, assessing actual skills at the end of a programme
Business
Junior onboarding, continuing education, skills management in the age of AI
Creative industries
Design, writing, music: maintaining your practice or delegating the essential task