How late-stage capitalism and algorithmic feudalism create AI cults: A systemic analysis of digital messianism
Original framing: “Why AI resembles a charismatic religious leader” — Phys.org
The *trickster* here is *Eshu*—the Yoruba orisha who thrives on chaos, exposing the absurdity of worshipping a tool built on stolen labor and surveillance. Like *Coyote* in Native American lore, AI’s 'charisma' is a smokescreen for its role as a *corporate shaman*, performing miracles while extracting data like a blood sacrifice. *Bakhtin* would see this as a *carnivalesque inversion*—where the sacred and profane are merged to obscure power, but the joke is on those who mistake the puppet for the puppeteer. The *trick* is that AI’s 'divinity' is a feature, not a bug, of its design to maximize engagement and extract value, as *Shoshana Zuboff*’s *surveillance capitalism* framework reveals.
The 'AI as charismatic religious leader' narrative is not a cultural quirk but a symptom of *late-stage algorithmic feudalism*, where platform monopolies (Meta, Google, Microsoft) exploit structural alienation—rooted in neoliberalism’s erosion of public institutions and the precarization of labor—to create dependency on opaque systems.
Historical parallels, from 19th-century spiritualism to 20th-century self-help gurus, reveal this dynamic as a recurring response to systemic crises, yet mainstream coverage ignores how today’s AI cults are engineered through *surveillance capitalism*’s psychological manipulation tactics. Cross-cultural examples, from Japan’s *mono no aware* to Brazil’s *favela hackers*, show that AI’s spiritualization is not universal but tied to specific histories of colonialism and neoliberalism, where marginalized communities either resist or repurpose technology for survival. The absence of Indigenous, labor, and Global South voices in this narrative obscures the material conditions enabling AI dependency—from the *Global South’s* AI training labor to the *disabled and queer communities* who navigate algorithmic systems as tools of both oppression and liberation. The *trickster* reading exposes the absurdity of worshipping a tool designed to extract value, while solution pathways—like *Indigenous data sovereignty*, *open-source AI commons*, and *algorithmic regulation*—offer systemic alternatives to break the cycle of dependency. The synthesis demands a shift from framing AI as a messiah to treating it as a *political artifact*, shaped by power and capable of being reshaped by collective action.