Datatrust: Or, the political quest for numerical evidence and the epistemologies of Big Data

By Gernot Rieder, Judith Simon. 2016

95 citations recorded by the source corpus.

Recently, there has been renewed interest in so-called evidence-based policy making. Enticed by the grand promises of Big Data, public officials seem increasingly inclined to experiment with more data-driven forms of governance. But while the rise of Big Data and related consequences has been a major issue of concern across different disciplines, attempts to develop a better understanding of the phenomenon's historical foundations have been rare. This short commentary addresses this gap by situating the current push for numerical evidence within a broader socio-political context, demonstrating how the epistemological claims of Big Data science intersect with specific forms of trust, truth, and objectivity. We conclude by arguing that regulators' faith in numbers can be attributed to a distinct political culture, a representative democracy undermined by pervasive public distrust and uncertainty.

Subfields: Artificial Intelligence, Information Systems, Safety Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Solon Barocas
2. Samir Passi

In Information Systems

1. Solon Barocas
2. Samir Passi
3. Adrian Weller

In Safety Research

1. Solon Barocas
2. Adrian Weller
3. Ben Green

Citations in the corpus

• Problem Formulation and Fairness (2019, background): “Each of these practical choices can have profound ethical implications [10,13,24,31,40], of which data scientists are sometimes well aware.”