SODAS Lecture with Claes de Vreese
Automated democracy: how digital technologies and AI are challenging democracy
Digital technologies, automation, and AI are changing democratic processes and challenging (public) institutions. In this SODAS lecture, Claes de Vreese will provide an overview of these challenges and offer results from ongoing research on the implications of these changes.
Claes de Vreese is professor of political communication and currently Distinguished University professor of AI and society with a special emphasis on media and democracy at the University of Amsterdam. He is also founding director of the Centre for Digital Democracy at the University of Southern Denmark SDU. T: @claesdevreese
This spring, the theme of the SODAS lecture series is "Philosophy of the Predicted Human".
The Predicted Human
Being human in 2022 implies being the target of a vast number of predictive infrastructures. In healthcare algorithms predict not only potential pharmacological cures to disease but also their possible future incidence of those diseases. In governance, citizens are exposed to algorithms that predict - not only their day-to-day behaviors to craft better policy - but also to algorithms that attempt to predict, shape and manipulate their political attitudes and behaviors. In education, children’s emotional and intellectual development is increasingly the product of at-home and at-school interventions shaped around personalized algorithms. And humans worldwide are increasingly subject to advertising and marketing algorithms whose goal is to target them with specific products and ideas they will find palatable. Algorithms are everywhere – as are their intended as well as unintended consequences.
Predicting and manipulating the future behavior of human beings is nothing new. Most of the quantitative social sciences focus on this topic in a general sense. There are entire subfields of statistics dedicated to understanding what can be predicted and what cannot. Yet the current situation is different. Computers’ ability to analyze text and images has been revolutionized by the availability of vast datasets and new machine learning techniques. We are currently experiencing a similar shift in terms of how algorithms can predict (and manipulate) human behavior. Human beings can be algorithmically shaped, we can be hacked.
The ambition with this semester’s SODAS Lectures is to present and discuss different perspectives on human prediction. Inviting a list of distinguished scholars and speakers whose expertise ranges from traditional social sciences, over machine learning and data science to philosophy and STS, we hope to delve into some of the principles and dynamics which govern our ability to predict and control both individual and collective human behaviors.
Venue: CSS, Sodas conference room 1.2.26