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 / Schedule

Introduction of AMLD 2021

With Robert West

Opening remarks

With Victor Kristof

Measuring Public Opinion with Machine Learning

With Lucas Leemann

Sub-Matrix Factorization for Interpretable Real-Time Vote Prediction

With Alexander Immer

Coffee Break

User Monitoring of the US Presidential Election

With Jacques Savoy

Investigating Paths Towards Safe Online Political Advertising

With Oana Goga

Voting Predictions in Political Science

With Steven Eichenberger

Lunch Break

Opening remarks

With Roy Gava

Using Machine Learning and Open Data to Report 216 Brazilian Congresspeople for Corruption

With Irio Musskopf

Big Problem, Big Data (And Vice Versa)

With Christine Choirat

Coffee Break

Gender Attitudes in the Judiciary: Evidence from U.S. Circuit Courts

With Arianna Ornaghi

With Bot Dog Against Online Hate

With Sophie Achermann

Trumping Hate on Twitter? Online Hate Speech and White Nationalist Rhetoric in the 2016 US Election Campaign and its Aftermath

With Alexandra Siegel

Coffee Break

Using Data Science to Achieve Fair and Equitable Social Outcomes

With Rayid Ghani

Concluding remarks

With Roy Gava

Virtual Apéro and Networking Event

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

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 & Democracy

Robert West, Roy Gava, Victor Kristof, Steven Eichenberger, Alexandra Siegel, Lucas Leemann, Rayid Ghani, Sophie Achermann, Alexander Immer, Jacques Savoy, Oana Goga, Christine Choirat, Arianna Ornaghi, Irio Musskopf

10:00-18:00 January 25

AI & Food and Nutrition

Cristoph Trattner

09:00-17:00 March 01

Clinical Machine Learning

09:00-17:00 March 18

AMLD / Global partners