Anshad Ameenza.
Human Development··Updated: Sep 30, 2026

The Cognitive Load You Now Have to Choose

AI removes the forced cognitive effort behind almost every task. What you do with the effort it frees up decides whether your mind gets sharper or softer.


A hard email used to cost you twenty minutes of drafting, cutting, and rereading. Now it costs eight seconds and one prompt. The email that comes out is fine. Better than fine, usually.

Something else came out of those twenty minutes that the eight seconds does not produce. Not the email. The version of you that gets slightly better at writing hard emails.

That difference has a name now, and you make the choice around it dozens of times a day without knowing you are making it.

1. Every task used to include a free rep

A task split into output and rep, unaided versus with AITop panel, unaided: one task box with two arrows out, one to output, one to a rep box, both solid and kept. Bottom panel, with AI: the same task box, the output arrow is solid and kept, the rep arrow is dashed and fades to a crossed-out rep box.Unaidedthe taskoutputthe repboth, every timeWith AIthe taskoutputthe repoutput, not the rep
A task always produced two things: the output, and a rep. AI is the first tool that lets you keep one without the other.

Every unaided task produces two things at once. The result you wanted, and a small, forced adjustment to the person who made it. Solve a hard problem and you get the answer, plus a mind slightly better calibrated to that category of problem. Write a difficult paragraph and you get the paragraph, plus a hand slightly more practiced at organizing a difficult thought.

That second thing is the rep. Nobody had to choose it. It arrived bundled with the task, the way exercise arrived bundled with a life that required walking somewhere, carrying something, or building something with your hands.

AI is the first tool that reliably separates the two. You can now get the output alone. Calculators did this for arithmetic. GPS did it for navigation. Spellcheck did it for spelling. Each of those unbundled one specific rep from one specific task. AI is different because it does this across writing, planning, analysis, decision-making, and synthesis simultaneously, for nearly anyone, on nearly any task, today.

2. Narrow tools took one rep. This one takes the category

Four narrow tools each removing one rep, compared with AI removing many at onceFour small labeled nodes on the left, calculator, GPS, spellcheck, search, each with a single thin arrow to one skill it replaced: mental arithmetic, spatial memory, spelling recall, fact recall. On the right, one larger AI node with six arrows fanning out to writing, planning, analysis, decisions, synthesis, and memory.calcmental arithmeticGPSspatial memoryspellspelling recallsearchfact recallAIwritingplanninganalysisdecisionssynthesismemory
Past tools each removed one rep. AI removes the category most people used to build a whole mind on.

Each narrow tool cost one specific rep and everyone accepted the trade, correctly. Nobody mourns mental long division. The trade always looked the same: give up a rep in a category small enough that losing it barely registered against everything else the mind still had to do unaided.

AI breaks that pattern because the category is not small anymore. It is most of the categories a knowledge worker used to build competence on by default, just by doing the job. That is a difference in kind, not degree, and it is why this now needs a name and a decision, where calculators never did.

3. Offloading is real, studied, and it changes what you remember

Recall of content versus recall of location, saved versus not savedTwo grouped bar pairs. Left group, expected not saved: content recall bar taller, location recall bar shorter. Right group, expected saved: content recall bar shorter, location recall bar taller. The crossover is the finding.expected not savedexpected savedcontentlocationcontentlocation
A 2011 study found people who expected to have information saved recalled it worse, and recalled where to find it better.

This is not a metaphor. A 2011 study published in the journal Science, run by the psychologists Betsy Sparrow, Jenny Liu, and Daniel Wegner, gave people trivia questions and then tested what they remembered. People who believed the answers would remain accessible later recalled the answers themselves worse, and recalled where to find them better. Facing a hard question also primed people to think of computers before anything else, a reflex the researchers measured directly.

The mechanism has a real name in cognitive science: transactive memory, the practice of storing information externally and remembering the address instead of the content. The internet had already made you a heavier user of transactive memory than any generation before you. AI does not introduce this effect. It extends it from facts into reasoning, which is a much larger and more consequential thing to store at an address instead of in your head.

4. The rep you skip is the rep you need at the worst possible time

Manual skill declining over time spent relying on automationA line starting high on the left and sloping down and to the right as automation reliance increases, with a marked point near the bottom right labeled the moment it fails and you are the backup, showing skill is lowest exactly when it is needed.time spent relying on automationthe moment it fails,and you are the backupmanual skill
Skill declines with disuse while the automation covers for it, and the automation fails right where the skill is lowest.

In 1983, the researcher Lisanne Bainbridge published a paper called Ironies of Automation that has since been cited well over a thousand times. Her argument still holds exactly. The more reliable an automated system becomes, the less a human operator practices the manual version of that skill. The operator’s job shifts from doing the work to watching the system do it, which is a worse way to stay sharp than doing it yourself. Then, on the rare occasion the system fails, the human who has to step in is the least practiced they have ever been, at the exact moment the stakes are highest.

Bainbridge wrote this about industrial and aircraft automation, long before anyone typed a prompt. The shape of the problem transfers directly. A person who has answered every hard question by asking a model has not been failing at anything. They have been quietly moving down the same curve, and they will not find out where they landed on it until a moment when the model is wrong, unavailable, or simply not the tool in front of them, and being right depends on them alone.

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The rep you skip does not disappear. It waits for the one moment you cannot skip it, and hands you back exactly the skill level you left it at.

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The reframe

5. Struggle now is the trade for skill later, but only the right struggle

Two lines crossing: performance during practice versus performance on a later test, assisted and unassistedTwo lines from left, during practice, to right, later test. The assisted line starts high and drops low. The unassisted line starts low and rises high, crossing the assisted line partway through.during practicelater, unaided testassistedunassisted
Assisted practice feels better today and tests worse later. Unassisted practice feels worse today and tests better later. The crossing line is the entire argument.

This is not a folk theory about hard work being virtuous. It is a specific, named finding in learning science. Robert Bjork, who has studied this for decades, calls it desirable difficulty: a practice condition that slows you down and feels worse right now, but produces learning that lasts and transfers to situations you have not seen before. Spacing your practice out, testing yourself instead of rereading, generating an answer instead of recognizing one. All of these make the moment feel harder and the result, later, measurably better.

Bjork’s own research includes the caveat that matters most here. A difficulty is only desirable if you can actually overcome it. Struggle that is too hard, or struggle unrelated to the skill you are trying to build, does not produce this effect. It just produces frustration. This is the honest limit of the whole argument, and it is worth sitting with before you go looking for load to add back.

6. Choosing what to keep

Two columns: tasks to buy back with AI, and tasks to keep as repsLeft column, buy back, listing high volume low stakes, output only matters, outside your core skill. Right column, keep the rep, listing builds the skill you are relying on right now, feedback is fast enough to learn from, low cost to get wrong today.Buy back with AIhigh volume, low stakesonly the output mattersoutside your core skillKeep the repbuilds the skill you arerelying on right nowfeedback fast enough to learncheap to get wrong todayeverything else is a live capabilityan emergency you have not had yet
You cannot afford to keep every rep. Keep the ones that build the specific capability you are relying on, buy back the rest.

You cannot keep every rep. Nobody has the hours, and most tasks genuinely do not deserve the effort. The choice is not more effort everywhere. It is picking, on purpose, the small set of tasks where the rep is building a capability you are actively relying on, where feedback arrives fast enough to correct you, and where being wrong today is cheap. Everything outside that set, hand to the model without a second thought. Nothing is proven by drafting a routine email by hand.

Inside that set, do it slower, on purpose, before you check what the model would have said. Not forever. Long enough that the skill stays live instead of becoming an emergency you have not had yet.

What nobody has solved

There is no dashboard that tells you which of today’s tasks were the ones worth the friction. That judgment is still yours, made task by task, and you will get it wrong sometimes in both directions: doing too much by hand out of habit, or handing over the one thing you actually needed to keep. The honest position is that this is a skill on its own, choosing the load, and like every other skill it gets better with reps you cannot outsource.

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Anshad Ameenza
About the Author

Anshad Ameenza

Lifelong Learner, Engineer, Technology Leader & Innovation Architect

20+ years of experience in technology leadership, innovation, and digital transformation. Building and scaling technology ventures.

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