Beyond Ubuntu: Rethinking AI Through African Time

Growing up, I never thought of time as a straight line. My grandmother used to speak of the past like it still breathed beside her — not gone, just living differently. She remembered her ancestors not as stories but as presences. Decisions weren’t only for today; they echoed forward and backward.

It’s only recently, watching how AI systems are being trained, that I realized how different that view of time truly is. And how much it matters.

The Problem with Linear Thinking

Most of the AI we see today is built on a simple logic: take data from the past, make predictions about the future, and move forward. It’s linear. Efficient. Predictable. But it’s also deeply limited.

Linear time leaves no room for memory that lingers, or futures that aren't yet profitable. It treats the past as closed and the future as a target. In that mindset, anything “old” is discarded, and anything “new” is progress. But where does that leave wisdom? Where does it leave the dead? Where does it leave the unborn?

When algorithms only optimize for the present, they risk repeating past harms and ignoring long-term consequences. Technology becomes reactive, rather than reflective. And in a world that’s rapidly changing, reflection is not a luxury — it’s a necessity.

The African Sense of Time

In many African traditions — from Akan in Ghana to Nguni in southern Africa — time isn’t just a line. It’s a circle. A spiral. A rhythm. The past isn’t “behind” us; it surrounds us. The future isn’t a blank slate — it’s a responsibility. You don’t just make decisions for yourself, but for your ancestors and your descendants.

When elders pour libations, they aren’t performing a ritual for show. They’re speaking with the ones who came before. That act alone teaches something powerful: memory is alive. It shapes the present. And the present must honor it.

This kind of time changes how we make choices. It slows things down. It invites accountability across generations. And it challenges the idea that faster is always better.

Why This Matters for AI

Imagine a machine trained not just to predict buying patterns or optimize traffic — but to respect memory. To act not only on speed, but on depth. Imagine AI models that ask, not just “What will happen next?” but “Who will be affected — even if they’re not here to speak for themselves?”

That’s not science fiction. It’s ethical design.

Right now, AI is obsessed with the future — faster processing, better performance, endless updates. But maybe what we need is an algorithm that slows down. That remembers. That treats a grandmother’s voice as data worth keeping — not because it's efficient, but because it's sacred. What if machine learning prioritized ancestral knowledge? What if it was trained to preserve, not just predict? To archive oral histories, to recognize cultural significance, to respect silence as much as noise?

I think often about the stories I’ve lost because no one wrote them down. My great-aunt’s memories. My uncle’s quiet wisdom. In the AI age, we risk forgetting even faster — because the systems we’re building don’t know how to carry memory. They discard “irrelevant” information. But culture is rarely efficient. It’s messy, emotional, full of contradictions. And if AI is going to live among us, it needs to learn how to hold those contradictions — not flatten them.

In my own journey, I’ve seen the temptation to adopt AI tools blindly — especially in African contexts where innovation is often equated with Westernization. But innovation rooted in forgetting is not progress. It’s erasure.

A Call to Build Differently

This isn’t just theory. It’s a design question:

• What if African technologists-built models around intergenerational ethics?

• What if ancestral names and rituals were encoded as knowledge, not erased as noise?

• What if the measure of “intelligence” included how well a system protected those not yet born?

We don’t need more efficient machines. We need more remembering ones. Machines that serve communities, not markets. Machines that know time isn't just a clock — it’s a promise. Our responsibility is to teach AI what it means to belong somewhere. And belonging starts with memory.

AI, as it stands, is fast. But speed isn’t always wisdom. And progress without memory is just forgetting with momentum. African time offers something rare: an ethical architecture built on presence, on reverence, and on accountability beyond one’s lifetime.

The future doesn’t need smarter machines. It needs wiser ones.

And sometimes, wisdom begins with listening to the past — as if it’s still here. Because in many ways, it is.