RANDOMNESS, UNCERTAINTY, AND COGNITIVE FREEDOM IN THE DATA SOCIETY
Abstract
The modern era of Big Data, in which massive volumes of information and predictive analytics serve as tools for forecasting human behavior, challenges the very notion of free will and personal autonomy. This study examines the philosophical problem of the relationship between freedom of action and control under conditions of total algorithmic prediction enabled by predictive analytics. The central question is posed: does freedom persist when every action can potentially be algorithmically anticipated? An interdisciplinary approach combining conceptual analysis and historical analogy is employed to explore the impact of algorithmic forecasting on cognitive freedom. A review of contemporary research in AI ethics, algorithmic governance, and the philosophy of technology is conducted. The evolution of the prediction society is traced—from the early efforts of demographic accounting to the present, where datafication transforms virtually every aspect of behavior into data points. Special attention is paid to the phenomenon of algorithmic normalization—the tendency of algorithms to shape expected behavioral patterns—and its influence on individual autonomy. A concept is proposed whereby uncertainty and randomness in human action are not defects but essential conditions for preserving cognitive freedom in the digital age. The conclusions argue that freedom of action remains possible even under the dominance of Big Data, but requires the active preservation of randomness and the safeguarding of spaces for unpredictability in behavior. This perspective opens new horizons for the philosophy of freedom in the digital era and challenges algorithmic ethics to recognize the value of randomness as a foundation for sustaining human autonomy. Does freedom of choice risk becoming an illusion in a world where data can not only predict but also steer personal decisions?
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