The algorithmic turn of prediction - IV

Abstract

Throughout history, the future has been an important reference for mankind. Its role for life in the present, however, has changed significantly in the course of time. While the future was initially found to be unalterable, with the development of modern societies it became to be understood as an open horizon that stands in a causal relationship to the present – the future got shapable according to actions and decisions in the present.

This shift in terms of interpreting the future made it even more attractive than before to produce knowledge about it. Predictive strategies subsequently flourished and technologies thereby played an increasingly important role.

With the advent of modern forms of algorithmic data analysis, with machine learning and artificial intelligence gaining center stage, another shift in referring to the future is likely, presenting an exciting as well as urgent challenge for social sciences in general and STS in particular.

Before this backdrop, this panel aims to discuss the theoretical as well as empirical implications of algorithmic prediction in the datafied society. What effects does the algorithmization of prediction have on the systems, settings and situations concerned? How do algorithmic predictive technologies differ from their – allegedly less sophisticated – technological predecessors? And, last but not least, where are the analytical possibilities and limits of STS approaches regarding the algorithmic turn of prediction?

Chair

• Maximilian Heimstädt, Bielefeld University

Individual Presentations

• From Statistical Uncertainty to Individual Prediction. Does Algorithmic Prediction Challenge the Open Future? - Elena Esposito, Bielefeld University

Session Organizers

• Simon Egbert, University of Bielefeld

• Elena Esposito, Bielefeld University