Predictive analytics and digital protentionality

On algorithmic prediction and anticipation




Probability theory, algorithms, prediction, forecasting


What do we mean when we say that algorithms are capable of predicting what is going to happen and anticipating our actions? In the following article I will analyse the phenomena of algorithmic prediction and behavioural anticipation, explaining their convergence in contemporary techniques of predictive analytics. First, I will deal with some possible misconceptions about the predictive capacities of algorithms by delving into probability theory. Secondly, I will take Bernard Stiegler’s post-phenomenological theory of algorithmic governmentality as a model to explain their capacity for behavioural anticipation. Lastly, I will present Mark Hansen’s Whiteheadian reading of predictive analytics, in which he provides a way to understand the ontological basis of the power of these algorithmic systems and also highlight their epistemological limits. Besides the theoretical purposiveness of this account, in the conclusion I will argue that this also provides us with new tools to extend Stielger’s pharmacological project further, opening up the possibility of thinking about ways in which algorithmic prediction could be implemented towards positive outcomes.


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Author Biography

  • Alan Diaz Alva, Leuphana Universität Lüneburg. Lüneburg, Alemania

    Estudiante de doctorado en la Universidad Leuphana en Lüneburg (Alemania). Con estudios previos en Arquitectura, ahora se enfoca en la investigación en los campos de la teoría crítica, filosofía de la tecnología y teoría marxista. Cuenta con estudios de maestría en 17, Instituto de Estudios Críticos de México, y en el Goldsmiths College de Londres.


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How to Cite

Predictive analytics and digital protentionality: On algorithmic prediction and anticipation. (2023). Desde El Sur, 15(2), e0021.

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