Aarhus University Seal / Aarhus Universitets segl

Automation & Control


Governments and companies are increasingly datafying there citizens and users, processing and deciding through algorithms, but does the developers of algorithms hold too much power?

How do we make sure that we use data in the most optimal way? Does seemingly objective processing of big data hold the truth or is it subject to (political) decisions by the developers that are kept too opaque at the moment? And if so what is the societal implications of issues such as inclusion, democracy and access, and how do we improve this?


More on this Grand Challenge


2019.11.22 | DATALAB, Algorithmic operation and control, Data sharing and privacy

A social science perspective on the Next Generation Internet

In Brisbane, Australia, DATALAB gathered internet researchers from around the world for a workshop on the development of a more human-centered internet.

2019.11.22 | DATALAB, Algorithmic operation and control, Data sharing and privacy

Machine learning and big data can challenge due process if used without consideration (in Danish)

Many people consider decisions based on data as neutral, but a case from the United States illustrate that they aren’t. Read the commentary in Jyllands-Posten from DATALAB's Simon Enni and Anja Bechmann.

2019.05.24 | DATALAB, Algorithmic operation and control

Even robots have values. And that isn't always a good thing (in Danish)

Robots with artificial intelligence can improve our lives, but they can also carry on old prejudices and discrimination. Read the commentary in Jyllands-Posten from DATALAB's Jiyoung Kim and Anja Bechmann.