Track / Overview

With the massive use of Fake News and the Cambridge Analytica scandal, the general public is aware that AI can harm democratic processes. But on its bright side, can machine learning help us to better understand and improve democracy?

The AI & Democracy track explores the challenges and opportunities that lie at the intersection of politics, law, and machine learning – beyond Fake News and Cambridge Analytica. Open Government Initiatives have opened access to vast amounts of data that political scientists, lawmakers, legal experts, journalists, and data scientists exploit to gain insights into political and legal processes.

The machine learning toolset of models and algorithms enables the processing of high-dimensional data available in unprecedented fashion. In particular, the AI & Democracy track investigates the extent to which decisions of different actors and institutions in the democratic system, from voters to judges, can be predicted. In the spirit of Nate Silver’s FiveThirtyEight data-driven statistical analysis of politics, we will explore how computational methods are being applied in the political and legal world and discuss whether they strengthen or weaken democracy.

Track / Speakers

Robert West

Professor, EPFL

Roy Gava

Assistant Professor, University of St. Gallen

Victor Kristof

PhD Student, EPFL

Steven Eichenberger

Lecturer, University of Geneva

Alexandra Siegel

Assistant Professor, University of Colorado Boulder

Lucas Leemann

Assistant Professor, University of Zürich

Rayid Ghani

Professor, Carnegie Mellon University

Sophie Achermann

Director, alliance F – Co-Founder, Stop Hate Speech

Alexander Immer

PhD student, ETH Zurich

Jacques Savoy

Professor, University of Neuchatel

Oana Goga

Research Scientist, CNRS

Christine Choirat

Chief Innovation Officer, Swiss Data Science Center (ETH Zürich/EPFL)

Arianna Ornaghi

British Academy Postdoctoral Research Fellow, University of Warwick

Irio Musskopf

Software Engineer, Independent

Track / Co-organizers

Victor Kristof

PhD Student, EPFL

Steven Eichenberger

Lecturer, University of Geneva

Roy Gava

Assistant Professor, University of St. Gallen

AMLD EPFL 2021 / Tracks & talks

AI for Risk in Financial Institutions

Ernst Oldenhof, Martin Jaggi, Paul Wang, Milica Lazic, Sacha Schwab, Jacqueline Stählin, Madan Sathe, Philipp Thomann, Prasanna Venkatesan, Aleksandra Chirkina, Luc Gerardin

09:00-12:30 September 14Online

AI & Online Business

Alessandro Nesti, Alexey Grigorev, Nicolas Mériel, André Schumacher, Xabier Rodriguez, Timo Grossenbacher, Markus Barmettler, Hakim Invernizzi, Severin Klingler, Francesco Calabrese

13:30-17:00 September 14Online

AI & Physics

Alexey Melnikov, Florent Krzakala, Giuseppe Carleo, Balaji Lakshminarayanan, Marylou Gabrié, Agnes Valenti, Gregor Kasieczka, Anna Dawid, Paolo Molignini, Roman Worschech, Diego Tapias, Aishik Ghosh, Frank Schäfer

09:00-18:15 September 30Online

AMLD / Global partners