International Summer School on Bias and Discrimination in AI

JUNE 3-6, 2019 | MONTRÉAL

About

Summary

Algorithms, and the data they process, play an increasingly important role in decisions with significant consequences for human welfare. While algorithmic decision-making processes have the potential to lead to fairer and more objective decisions, emerging research suggests that they can also lead to unequal and unfair treatments and outcomes for certain groups or individuals.

This Summer School is an attempt to engage multi-disciplinary teams of researchers and practitioners to explore the social and technical dimensions of bias, discrimination and fairness in machine learning and algorithm design. The course focuses specifically (although not exclusively) on gender, race and socioeconomic based bias and data-driven predictive models leading to decisions.

The summer school will be filmed and will be available as a MOOC late 2019.

A basic understanding of machine learning is strongly recommended.

What you will learn

  • Understanding bias and discrimination
  • Exploring the harms from bias in machine learning (discriminatory effects of algorithmic decision-making)
  • Identifying the sources of bias and discrimination in machine learning
  • Mitigating bias in machine learning (strategies for addressing bias)
  • Recommendations to guide the ethical development and evaluation of algorithms

Registration

Registration will open on March 11th at 12h00.

  • Government and industry employees: $1500
  • Non-profit organization (NPO): $400
  • Student: $200

Organizing Committee

  • Jihane Lamouri, Diversity coordinator, IVADO
  • Golnoosh Farnadi, Postdoc researcher, IVADO
  • Martin Gibert, Ethics researcher, IVADO
  • Brian Moore, Training coordinator, IVADO

Confirmed Speakers

Behrouz Babaki

IVADO Postdoctoral Researcher at Polytechnique Montreal

Elizabeth Bender

Elizabeth Bender is based in New York City. She a staff attorney with the Legal Aid Society’s Decarceration Project

Jannick Bouthillette

Cofounder, Profession’ELLE

Noël Corriveau

Noel Corriveau is a lawyer with the Federal Department of Justice, Canada

Fernando Diaz

Principal Researcher and lead of the Montreal FATE Research Group at Microsoft

Audrey Durand

Audrey obtained a Master’s degree in Electrical Engineering from Université Laval…

Golnoosh Farnadi

IVADO Postdoctoral Researcher at Polytechnique Montreal

Abhishek Gupta

Founder, Montreal AI Ethics Institute

Will Hamilton

Assistant Professor in the School of Computer Science at McGill University

Yasmeen Hitti

Research Intern at Mila and co-founder of Biasly AI

Andrea Jang

Research Intern at Mila and co-founder of Biasly AI

Emre Kiciman

Principal Researcher at Microsoft Research AI

François Laviolette

Professor at Université Laval and Director of the Big Data Research Center

Nathalie de Marcellis-Warin

Full Professor, Department of Mathematical and Industrial Engineering (Polytechnique Montréal)
President and Chief Executive Officer at CIRANO

Margaret Mitchell

Senior Research Scientist, Google Research and Machine Intelligence

Petra Molnar

Lawyer and Researcher at the International Human Rights Program…

Joelle Pineau

Joelle Pineau is an Associate Professor and William Dawson Scholar at McGill University

Ravy Por

Ravy Por is a Université de Montréal graduate in mathematics with an actuarial specialization…

Bibiana Pulido

Bibiana is newly appointed as Strategic Advisor on Equity, Diversity and Inclusion for the Observatoire sur les impacts sociétaux de l’intelligence artificielle et du numérique.

Deborah Raji

Engineering Science Student, University of Toronto

Tania Saba

Professor of Industrial Relations at Université de Montréal, Chair Holder…

Pedro Saleiro

Post-Doc, Aequitas, Center for Data Science and Public Policy at the University of Chicago

Cynthia Savard Saucier

Director UX at Shopify and co-author of Tragic Design

Luke Stark

Postdoctoral Researcher at Microsoft Research Montreal

Philippe-André Tessier

President of the Commission des droits de la personne et des droits de la jeunesse

Rachel Thomas

Professor at the University of San Francisco and co-founder of fast.ai

Nicolas Vermeys

Professor of Law at Université de Montréal and Assistant Director of the Cyberjustice Laboratory

Terrence Wilkerson

Terrence has twice been wrongfully accused of serious crimes in the Bronx

RC Woodmass

Founder of Queerit and Product Designer at Crescendo

Program

Ravy Por
Moderator

9:00

Joelle Pineau
Opening remarks

9:15

Rachel Thomas
Keynote

10:30

Break

11:00

Tania Saba
Understanding bias & discrimination

11:40

Deborah Raji
The tech diversity problem

12:20

Lunch

13:30

Pedro Saleiro
Bias and Fairness in AI for Public Policy

14:45

Break

15:15

Pedro Saleiro
The Aequitas Toolkit: Case Studies & Tutorial

16:30

End of the day

Bibiana Pulido
Moderator

9:15

Emre Kiciman
Where does bias come from?

10:30

Break

11:00

Golnoosh Farnadi
Fairness definitions

11:40

François Laviolette
Bias in machine learning

12:20

Lunch

13:30

Petra Molnar
Automated decision system technologies & human rights

14:10

Noël Corriveau
Canada’s Algorithmic Impact Assessment Framework

14:45

Break

15:15

Noël Corriveau
Workshop

17:00

Cocktail

Golnoosh Farnadi
Moderator

10:30

Break

11:00

Emre Kiciman & Margaret Mitchell
Fairness-aware ML: practical challenges

12:20

Lunch

13:30

Behrouz Babaki
Learning subject to fairness constraints

14:10

Will Hamilton
Fairness constraints for graph embeddings

14:45

Break

15:15

Yasmeen Hitti & Andrea Jang
Tackling gender bias in text

16:00

Audrey Durand
AI for Health: Bias Alert

16:30

End of the day

9:15

Nicolas Vermeys
The legal perspective

10:30

Break

11:40

Nathalie de Marcellis-Warin
Montreal Declaration for responsible AI

12:20

Lunch

13:30

Cynthia Savard Saucier
The impact of bad design and how to fix it

14:10

RC Woodmass
Biulding inclusive teams

14:45

Break

15:20

Fernando Diaz & Luke Stark
Recommendations for the future

16:30

End of the day