Track / Overview

The increasing availability of digital data sources are providing opportunities for policy makers in the sense that appropriate algorithms can digest massive amounts of data into facts and figures to support the conception, development, and implementation of new policies and associated decisions. Suitable algorithms are also contributing to the follow-up of the impact of the policies that are already in place. The algorithms do not only need to be appropriate but should also be well documented and based on scientific methods. This permits to reproduce and possibly challenge the generated facts and figures. Indeed, a strong scientific base is a fundamental condition to the acceptance of algorithms in a policy context. On the other hand, while data science has recently emerged as a new and promising scientific discipline, facts and figures extracted from data should not be solely based on approaches pursued by data driven methods because domain specific expertise and knowledge remain essential. This is also fundamental to help understanding whether the observed correlations are casual or causal.

With that in mind, the AI & Policy track aims at exploring the role and impact of AI in a policy context through an oral session followed by a panel discussion. 

Track / Schedule

Data, algorithms and data governance

With Sofia Olhede

Private synthetic data with GANs, autoencoders and minority oversampling

With Ioannis Kaloskampis

A conversational agent to support citizen interactions powered by Semantic AI

With Dennis Diefenbach

Human-centric AI challenges and opportunities

With Sabrina Kirrane

Visualisation as a mean to foster adoption of AI by policy makers

With Benoît Otjacques

AI for Earth Observation in policy support

With Christina Corbane

Poster Pitch – Predicting the outcome of votes taken by the Swiss National Council applying Machine Learning models by Daniel Müller

Break

Panel discussion – Exploring the role and impact of AI in a policy context: Challenges and opportunities for decision-making

With Joanna Bryson, Emanuele Baldacci, Steve MacFeely & Bruno Lepri

Track / Speakers

Joanna Bryson

Professor of Ethics and Technology, Hertie School of Governance Berlin

Sofia Olhede

Professor of Statistical Data Science, EPFL

Emanuele Baldacci

Director Digital Services, European Commission

Sabrina Kirrane

Senior Postdoctoral Researcher, Vienna University of Economics and Business

Bruno Lepri

Head of Research Unit, Fondazione Bruno Kessler & Chief AI Scientist Manpower Group

Dennis Diefenbach

Researcher, QAnswer

Ioannis Kaloskampis

Senior Data Scientist, Office for National Statistics UK

Benoît Otjacques

Head of Environmental Informatics, Luxembourg Institute of Science and Technology

Steve MacFeely

Head of Statistics and Information UNCTAD

Christina Corbane

European Commission, Joint Research Centre

Track / Co-organizers

Jacopo Grazzini

Statistical Officer, Eurostat - European Commission

Pierre Soille

Project Leader, Joint Research Centre of the European Commission

AMLD EPFL 2020 / Tracks & talks

AI & Nutrition

Marinka Zitnik, Marcel Salathé, Fabio Mainardi, Tome Eftimov, Barbara Koroušić Seljak, Nives Ogrinc, Aleksandra Kovachev

13:30-17:00 January 282A

AI & Policy

Joanna Bryson, Sofia Olhede, Emanuele Baldacci, Sabrina Kirrane, Bruno Lepri, Dennis Diefenbach, Ioannis Kaloskampis, Benoît Otjacques, Steve MacFeely, Christina Corbane

13:30-17:30 January 272A

Challenge Track

Danny Lange, Sunil Mallya, Marcel Salathé, Florian Laurent, Erik Nygren, Sharada Mohanty, Parth Kothari, Navid Rekabsaz, Wilhelmina Welsch, Ewan Oglethorpe, Nicholas Jones, Gokula Krishnan, Jeremy Watson, Andrew Melnik

13:30-17:00 January 284A

AMLD / Global partners