Post-truth politics is framed as a meta-digital regime in which algorithmic systems quantify affect and privilege rapid decisiveness over veridical judgment, shifting computation from binary verification toward automated modulation of conduct. Reworking Heideggerian critiques of cybernetic instrumentality through histories of AI and machine learning, the text argues that contemporary deep learning operationalizes uncertainty and randomness as a transcendental instrumentality—an inhuman epistemology that both amplifies bias and generates new, mediated forms of reasoning beyond human-centered truth and fact.

Images operate as masks within an algorithmic propaganda ecology where context is stripped, truth is manufactured through virality, and the state’s visual regime merges nationalism, surveillance, and censorship to rewrite history while punishing dissent. Against the collapse of verification and the commodification of journalism, the text proposes glitch, opacity, and coded metaphor as aesthetic-political tactics that reintroduce doubt, expose the constructedness of “truth,” and contest the weaponization of representation.