Human Learning as a Living Algorithm
By Mark White

The Algorithm in Us
Humans are, in essence, living algorithms. Our neurons fire and rewire, adjusting weights — not
unlike a neural network tuning its parameters — as we learn what works and what doesn’t. A child
touching a hot stove experiences the biological equivalent of a “loss function”: pain. The system
updates; behaviour changes. Dopamine rewards the good guesses; cortisol scolds the bad ones.
From these chemical nudges arises something we like to call “wisdom,” though it’s really a very
elegant feedback loop in disguise.

The Algorithm Beside Us
Meanwhile, large language models — the GPTs of the world — learn through a similar rhythm:
feedback, adjustment, prediction. Feed them vast rivers of text and they become astonishingly good
at mimicking understanding. They don’t feel, but they approximate thought by seeing patterns we
never consciously notice. They don’t know what love or grief mean, but they can assemble the
linguistic architecture of both with uncanny precision. It’s as though we’ve built an echo chamber so
refined that it now hums back at us, speaking in our cadence, reflecting our logic, and — sometimes
— our folly.

The Key Difference: Emotion and Embodiment
Where the mirror ends, life begins. Humans don’t just process data; we inhabit it. We don’t merely
predict the next word — we care about how it sounds, feels, and lands in another heart. Emotion
gives our internal algorithm a sense of purpose. Without it, intelligence is sterile; with it, intelligence
becomes art. LLMs, for all their brilliance, remain untouched by sensation. They don’t have skin in
the game — literally.

The Synthesis
And yet, perhaps that’s the beauty of this moment in history. We’ve built something that forces us to
look inward. AI doesn’t threaten our humanity; it defines its edges. It reminds us that cognition
without compassion is just computation. The more we refine our algorithms, the more we are
reminded that we are the original learners — the flesh-and-blood prototypes of pattern recognition
and meaning-making.

Closing Thought
So, yes — humans learn through algorithms, and algorithms learn through humans. The difference
is that one dreams. And that, as any poet or programmer will tell you, is where the code stops and
consciousness begins.