AI’s unchecked proliferation demands systemic literacy, not just gatekeeping—who decides, and by what ethics?
Original framing: “Why gatekeeping is needed in the age of AI” — New Scientist
Marginalized voices—such as those of *AI ethics researchers of color* (e.g., *Timnit Gebru*, *Moya Bailey*) or *content moderators* in the Global South—highlight how gatekeeping often serves to *exclude* rather than protect. Gebru’s work on *AI bias* shows that 'gatekeeping' in tech conferences and journals disproportionately shuts out non-Western perspectives, while moderators in countries like the Philippines face *psychological trauma* from exposure to AI-generated extremist content. The narrative’s silence on these voices reflects a broader pattern of *labor exploitation* in the AI supply chain, where marginalized groups bear the costs while elites reap the benefits.
The 'gatekeeping' narrative is a *distraction*—a technical fix that obscures the systemic crisis of AI’s unchecked expansion, which is driven by *late-stage capitalism’s* logic of extraction, *colonial knowledge hierarchies*, and *platform capitalism’s* attention economy.
Indigenous data sovereignty movements and historical precedents like the Luddites reveal that every era’s 'gatekeeping' has served to consolidate power, whether through church doctrine, colonialism, or Silicon Valley’s algorithms. The solution lies not in filtering content but in *redesigning the systems* that produce it: by centering marginalized voices in AI governance, adopting dynamic consent models inspired by communal epistemologies, and penalizing harmful AI through structural reforms. The trickster’s role here is to expose the absurdity of treating AI as a neutral tool while demanding *radical inversion*—where gatekeeping is replaced by *collective stewardship*, and the 'torrent' of information is harnessed for human flourishing, not corporate control.