The research project
The ever-increasing use of digital algorithms for the collection and interpretation of big data fundamentally changes the way in which we form opinions and make decisions – as individuals and in society. Previously, this transformation happened outside of the attention of the public, but it has now become a pressing issue of concern. Data and algorithms are not only the pervasive technological infrastructure of public debate, but also a frequent topic of such debate.
Digitalization has, in other words, become controversial and now contributes to society’s crises of trust, as technological developments accelerate tendencies like populism, polarization, conspiracy theories, and conflicts. Thus, environmental, social, political, and economic crises are interwoven with technological concerns, increasing general mistrust in the traditional institutions of democratic societies.
The ADD-project explores the reasons for this development and the possibilities for turning it around: How can data and algorithms be used to enlighten and engage citizens and to strengthen democracy? We offer explanations of and solutions to societal problems by studying controversies about digitalization as these play out on digital platforms and are shaped by digital technologies.
The project brings together researchers from six Danish universities: Aalborg University, Aarhus University, Copenhagen Business School, Roskilde University, University of Copenhagen, and University of Southern Denmark.
The subprojects
Aalborg University: The team at Aalborg University focuses on critical infrastructures, privacy, and cybersecurity. For example, when a new digital signature is implemented, how do we protect citizens from data leaks? And how do companies protect themselves and their customers from hacker attacks?
Aarhus University: The team at Aarhus University investigates the use of predictive algorithms in public administration, asking what happens when public authorities use technology to determine what citizens might do in the future.
Copenhagen Business School: The team at Copenhagen Business School explores the financial sector, asking what happens when, for instance, insurances can be calculated automatically or when an algorithm autonomously decides if a bank customer can have a loan?
Roskilde University: The team at Roskilde University looks at health. What does it mean for citizens that they have access to ever more knowledge about their personal health? And what does it mean for the health sector that artificial intelligence can diagose diseases and recommend treatments?
University of Copenhagen: The team at University of Copenhagen is based at the Department of Computer Science and explores current challenges and limitations of algorithmic technologies, aiming to create better solutions: How, for instance, do we establish ground truth approximations for algorithmic training, how do we reduce sampling bias in training data, and how do we enable out-of-sample generalizability of trained algorithms?
University of Southern Denmark: The team at University of Southern Denmark investigates the ways in which imaginaries of innovation shape current developments and also asks how new technologies also shape what innovation is and can be.