The Human Upgrade, Part 2: The Attention Economy Is Eating Our Focus — and We’re Feeding It
- Angie Okhupe
- 3 days ago
- 3 min read
My phone buzzed three times while writing this sentence.
Two of those notifications were from apps powered by AI.
That’s how it starts — the slow theft of focus that feels like free choice.
Every ping, every “you might also like,” every perfectly timed reminder is the output of a model trained on me. Not people like me — me. My habits, my pauses, my midnight searches for banana bread recipes and productivity hacks.
AI has learned what captures my attention better than I have.
It’s efficient.
It’s brilliant.
And it’s exhausting.
The invisible algorithm behind every distraction
The digital world runs on one currency: attention.
But it’s AI that manages the exchange rate.
Recommendation systems decide which videos appear next.
Language models write the notifications that sound most like your friends.
Predictive feeds choose when to surface what you didn’t know you wanted.
The result?
Our curiosity becomes programmable.
We’re not just browsing the internet — the internet is browsing us.
The shrinking space between thoughts
Focus used to feel like a place you could go.
Now it’s a moving target.
Each scroll is a micro-conversation with a machine trained to keep us engaged.
The more data we feed it, the better it gets at closing the gap between one thought and the next — until there’s no space left for boredom, or reflection, or stillness.
Neuroscientists call it attentional residue — the dust left behind by half-processed thoughts. AI calls it user retention.
When your feed feels endless, it’s because it literally is.
There’s no natural stopping point in a world that predicts your next desire before you feel it.
Our brains weren’t built for this kind of precision
Human attention evolved for forests, not feeds.
We’re wired to notice change — movement, novelty, potential reward.
AI learned that trick and turned it into a business model.
Every swipe teaches the system what kind of surprise keeps you there.
Every pause in a video signals what emotion holds you longest.
It’s personalization at planetary scale — and it works.
But the more precisely the system predicts us, the less room we leave for ourselves to wander. When discovery becomes automated, curiosity starts to atrophy.
Re-training the human algorithm
I’ve started to treat attention the way AI treats data — as something valuable to train on wisely.
I ask:
What patterns am I reinforcing?
What feedback loop am I feeding?
What kind of person does this algorithm think I want to be?
Sometimes I intentionally confuse it — scroll slower, click on random things, close the app mid-prediction. It’s my quiet rebellion, reminding both of us that uncertainty is still human.
And in between the chaos, I practice small resets:
Silence notifications that “predict” my mood.
Let an hour pass without input so my thoughts can self-organize.
Replace one scroll with a notebook — a feed I control.
Because if AI is learning from me, I should decide what kind of teacher I want to be.
The real upgrade
AI isn’t stealing our attention; it’s training it.
The question is: toward what?
If we let machines design the rhythm of our minds, we risk syncing to their tempo — fast, endless, optimized.
But if we learn to design our attention with the same care they design for it, we stay in the loop as more than users — as conscious participants.
💭 Big Think, Small Word:
AI doesn’t crave your focus. It just predicts it.
The upgrade isn’t turning it off — it’s turning you back on.
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