The End of Prediction? AI Technologies in a No-Analog World.

AI technologies mine past data to anticipate future events, and yet our world of environmental and political crisis ushers in unprecedented conditions. Mixing examples of operational environments (AI in the oil and gas industry) with insights from media, cultural, and environmental studies, this art...

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Detalles Bibliográficos
Publicado en:Substance: A Review of Theory & Literary Criticism Vol. 52; no. 2; pp. 59 - 74
Autor principal: Munn, Luke
Formato: Artículo
Publicado: Johns Hopkins University Press 2023
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Acceso en línea:Ver este registro en EBSCOhost
Descripción
Sumario:AI technologies mine past data to anticipate future events, and yet our world of environmental and political crisis ushers in unprecedented conditions. Mixing examples of operational environments (AI in the oil and gas industry) with insights from media, cultural, and environmental studies, this article explores this grappling with uncertainty. To manage uncertainty, companies strive to internalize the complexity and contingency of the real world, collecting more data, designing more accurate sensors, and developing more exhaustive models. And yet prediction is a fraught exercise that struggles with correlation versus causation, the epistemological outside (the unknown), and the ontological outside (the open-endedness of the future). In addition, technology's role in accelerating and intensifying the destructive logics of capital contributes to more volatile planetary conditions, undermining the stability and continuity that prediction requires. The article thus argues that, at a fundamental level, a highly fluid future will increasingly frustrate any meaningful degree of prediction.