SODAS Lecture with Serge Belongie

Serge Lecture

"The Pioneer Centre for Artificial Intelligence"

We are delighted to host Prof. Serge Belongie for this semester’s second SODAS lecture.


The purpose of the lecture is to introduce the new Pioneer Centre for Artificial Intelligence, which is hosted at the Department of Computer Science, University of Copenhagen, and will be located just across from SODAS in the old UCPH Observatory (currently under renovation). Funded by a DKK 352,4 million (€47 million) grant from the combined foundations: Novo Nordisk, Denmark’s National Research Foundation, Villum, Lundbeck and Carlsberg, the Pioneer Centre for Artificial Intelligence aims to stand at the international forefront and develop platforms, methods, and practices for a human centric AI. Groundbreaking fundamental AI research will be pursued within an interdisciplinary framework. Inspired by the motto Nothing About Us, Without Us (NAUWU), the center is based on the idea that no policy should be decided by any representative without the full and direct participation of members of the group(s). The center is organized into seven collaboratories structured around an AI research theme with 2-3 PIs as well as PhD students and postdocs attached. Researchers from the University of Copenhagen, Denmark’s Technical University, IT University, Aalborg University, and Aarhus University co-lead these efforts, along with Director, Professor Serge Belongie.

Speaker bio

Serge Belongie is a professor of Computer Science at the University of Copenhagen, where he also serves as the head of the Pioneer Centre for Artificial Intelligence. Previously, he was a professor of Computer Science at Cornell University, an Associate Dean at Cornell Tech, and a member of the Visiting Faculty program at Google.His research interests include Computer Vision, Machine Learning, Augmented Reality, and Human-in-the-Loop Computing. He is also a co-founder of several companies including Digital Persona, Anchovi Labs, and Orpix. He is a recipient of the NSF CAREER Award, the Alfred P. Sloan Research Fellowship, the MIT Technology Review “Innovators Under 35” Award, and the Helmholtz Prize for fundamental contributions in Computer Vision.

This fall, the theme of the SODAS lecture series is "Philosophy of the Predicted Human".

The Predicted Human

Being human in 2021 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.