From Statistical Uncertainty to Individual Prediction. Does Algorithmic Prediction Challenge the Open Future?

• In Event: The algorithmic turn of prediction - IV

Abstract

Algorithmic prediction using machine learning and big data is very different from the idea of prediction that established itself in modern society since the 18th century, oriented and guided by the calculus of probability. Whereas probability calculus offers a rational way to deal with uncertainty, algorithms claim to provide a score for individual persons or singular events. This breaks with the modern view of an open future, that is unknowable for everyone because it does not yet exist. The paper analyses the consequences of the new forms of focused prediction on the different social structures that still rely on our shared uncertainty about the future. Besides unprecedented forms of control, the use of opaque machines require a new awareness of problems of solidarity, risk and prevention.

Author

• Elena Esposito, Bielefeld University