Predictive analytics and digital protentionality
On algorithmic prediction and anticipation
DOI:
https://doi.org/10.21142/DES-1502-2023-0021Keywords:
Probability theory, algorithms, prediction, forecastingAbstract
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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Esta obra está bajo una licencia http://creativecommons.org/licenses/by-nc-sa/4.0/
