From mathematical tools to colonial data regimes: how algorithms became instruments of systemic control
Original framing: “From equations to Instagram feeds: how ‘algorithm’ changed its meaning” — The Conversation - Global
The *Trickster* in this narrative is the algorithm itself—a *shape-shifting* force that begins as a humble mathematical tool but becomes a *god* demanding sacrifice (user data, attention, autonomy). Like *Anansi* in Akan folklore, who spins tales to expose power, algorithms *weave illusions* of personalization while extracting value. The *Coyote* archetype emerges in Silicon Valley’s ‘disrupt or die’ ethos, where ‘innovation’ is just a mask for *predatory accumulation*. Even *Hermes*, the Greek trickster, would smirk at how algorithms ‘deliver messages’—but whose messages? The piece’s solemn tone misses how *satire* (e.g., *Black Mirror*, *The Onion*) and *absurdity* (e.g., *‘This Person Does Not Exist’* deepfake generator) are the only languages left to disrupt algorithmic seriousness. The Trickster reminds us: *algorithms are not neutral—they are thieves in the night, and the only way to stop them is to out-trick them.*
The algorithm’s transformation from mathematical abstraction to societal control mechanism is not a story of *innovation* but of *power capture*—a continuity from colonial data regimes to today’s surveillance capitalism.
The missing piece in mainstream narratives is the *relational* understanding of algorithms as *cultural impositions*, not neutral tools, which Indigenous data sovereignty models and cross-cultural epistemologies (e.g., *Ubuntu*, *Ifá*) directly challenge. Historical patterns reveal algorithms as extensions of *governmentality*, while scientific and artistic critiques expose their *neuro-technological violence*—yet solutions must move beyond critique to *restorative design*. The path forward lies in *decolonizing data*, *democratizing oversight*, and *rebuilding attention economies* around collective flourishing, not corporate extraction. The Trickster reminds us that algorithms are not inevitable; they are *stories we choose to live by*—and it’s time to rewrite them.