Political algorithms that resist premature categorization and classification, preserving complexity until natural patterns emerge organically.
The pu, or uncarved block, represents potential in its undifferentiated state. Applied to algorithmic politics, this means resisting the impulse to immediately classify citizens, opinions, and political positions into fixed categories. Traditional political algorithms categorize users as left/right, progressive/conservative, engaged/apathetic—but this carving reduces nuance and creates brittle systems. A Taoist approach uses algorithms that hold complexity longer, revealing natural clusters and affinities rather than imposing ideological templates. This preserves what Laozi calls the unmanifested potential—the space where genuine political movements and coalitions can form without predetermined structures. Pre-categorical algorithms work with raw political signals, aggregating patterns as they emerge rather than forcing early categorization. This approach yields more authentic political formations and reduces algorithmic bias from embedded classification schemes.
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