Algorithmic Fear and Datafied Subjectivity: Surveillance Anxiety in Don DeLillo through Digital Humanities

Abstract

This paper examines Don DeLillo’s fiction as a prophetic literary engagement with contemporary algorithmic surveillance and data-driven governance. Moving beyond readings of postmodern paranoia and psychological anxiety, the study argues that DeLillo anticipates algorithmic fear—a systemic form of anxiety produced by media saturation, data abstraction, and predictive control. Drawing on theories of surveillance capitalism (Zuboff, 2019), algorithmic culture (Chun, 2016), media theory (McLuhan, 1964), and Digital Humanities approaches, the paper analyzes White Noise, Mao II, Underworld, and Falling Man to demonstrate how subjectivity is increasingly reshaped by informational systems rather than individual consciousness.

Through qualitative textual analysis and interdisciplinary interpretation, the study reveals that DeLillo’s characters experience fear as an effect of continuous data processing, media repetition, and invisible surveillance mechanisms. The novels represent the transformation of human experience into extractable data, the normalization of predictive governance, and the erosion of interiority under algorithmic control. By foregrounding waste, archives, media networks, and post-9/11 security regimes, DeLillo’s fiction emerges as a cultural archive of surveillance anxiety that prefigures contemporary digital realities.

The paper contributes to DeLillo scholarship by reframing his work within digital surveillance studies and advances interdisciplinary dialogue between literary criticism and Digital Humanities. Ultimately, the study positions DeLillo as a crucial literary theorist of the algorithmic age, whose fiction exposes the affective and ethical consequences of datafied modernity.