Responsible AI

Artificial intelligence (AI) is a transformative technology, affecting all aspects of society while fundamentally changing how humans live, work and communicate. Although it presents endless opportunities, it also comes with unintended consequences and potential risks, which must be tackled at all stages in the development and rollout of AI systems.

Man holding his two daughters in a field of red-petaled flowers.

Responsible AI research explores pitfalls of the technology while seeking socio-technical solutions to make machine learning algorithms more trustworthy, safe, and fair. Mila’s researchers actively design solutions aimed at mitigating bias and discrimination, tackling the lack of epistemic humility within large language models, which can confidently state false things.

In addition, Mila’s researchers continue to explore ways of aligning and controlling AI systems, while also improving data privacy across an AI system’s lifecycle. Mila also leads a number of high-level projects through its AI4 Humanity stream. Harnessing the power of machine learning algorithms, Mila is helping to tackle major contemporary challenges such as online human trafficking, modern slavery, and sexist bias in text.

Spotlight on Equal Lab

At Equal Lab (Mila/McGill University), a team of multidisciplinary experts collaborates in the development of innovative solutions addressing algorithmic biases, in order to ensure fair and ethical AI outcomes in fields such as healthcare and finance.

Learn more

AI is a powerful tool that affects every aspect of society. Responsible AI principles seek to put in place the necessary safeguards to make sure that this power is harnessed for the common good.

Golnoosh Farnadi, Assistant Professor, McGill University, Core Academic Member, Mila

Resources

Missing links in AI governance

This book, jointly published by Mila and UNESCO, addresses the urgent need for better governance of artificial intelligence in the face of unprecedented technological change.

View the book https://unesdoc.unesco.org/ark:/48223/pf0000384787

Montréal Declaration for a Responsible Development of Artificial Intelligence

Co-created by Mila and the Université de Montréal, the Montreal Declaration is a collective work that aims to put AI development at the service of the well-being of all people.

Learn more https://montrealdeclaration-responsibleai.com/

AI & Cities: Risks, Applications and Governance

This white paper produced by Mila and UN-Habitat aim to assist governments in the appropriate and responsible use of AI in cities.

Download the report https://unhabitat.org/ai-cities-risks-applications-and-governance

In the Media

Montreal group joins call for better governance of AI (CBC)

Watch the story https://www.cbc.ca/player/play/2187185731873

Mila, UNESCO warn against use of AI in “harmful contexts” in joint book (BetaKit) on AI governance

Read the article https://betakit.com/mila-unesco-warn-against-use-of-ai-in-harmful-contexts-in-j…

Research Labs

Mila professors exploring the subject as part of their research.

Mila Faculty

Associate Academic Member

Samira Abbasgholizadeh-Rahimi

Assistant Professor, McGill University, Department of Electrical and Computer Engineering

See the details

Core Academic Member

David Ifeoluwa Adelani

McGill University

Canada CIFAR AI Chair

See the details

Associate Academic Member

Ulrich Aivodji

Assistant Professor, École de technologie supérieure (ETS), Department of Software and Information Technology Engineering

See the details

Associate Academic Member

Ian Arawjo

Assistant Professor, Université de Montréal, Department of Computer Science and Operations Research

See the details

Core Academic Member

Tal Arbel

Full Professor, McGill University, Department of Electrical and Computer Engineering

Canada CIFAR AI Chair

See the details

Core Academic Member

Pierre-Luc Bacon

Assistant Professor, Université de Montréal, Department of Computer Science and Operations Research

Canada CIFAR AI Chair

See the details

Core Industry Member

Dzmitry Bahdanau

AI Research Scientist, ServiceNow

Canada CIFAR AI Chair

See the details

Core Academic Member

Yoshua Bengio

Full Professor, Université de Montréal, Department of Computer Science and Operations Research Department

Canada CIFAR AI Chair

See the details

Core Academic Member

Danilo Bzdok

Associate Professor, McGill University, Department of Biomedical Engineering

Canada CIFAR AI Chair

See the details

Affiliate Member

Quentin Cappart

Assistant Professor, Polytechnique Montréal, Department of Computer Engineering and Software Engineering

See the details

Associate Academic Member

Margarida Carvalho

Assistant Professor, Université de Montréal, Department of Computer Science and Operations Research

See the details

Core Academic Member

Jackie Cheung

Associate Scientific Director, Mila, Associate Professor, McGill University, School of Computer Science

Canada CIFAR AI Chair

See the details

Associate Academic Member

Mark Coates

Associate Professor, McGill University, Department of Electrical and Computer Engineering

See the details

Core Academic Member

Aaron Courville

Associate Professor, Université de Montréal, Department of Computer Science and Operations Research

Canada CIFAR AI Chair

See the details

Associate Academic Member

Érick Delage

Full Professor, HEC Montréal, Department of Decision Sciences

See the details

Core Industry Member

Fernando Diaz

Research Scientist, Google Pittsburgh

See the details

Associate Academic Member

Marc-Antoine Dilhac

Associate Professor, Université de Montréal, Department of Philosophy

Canada CIFAR AI Chair

See the details

Associate Academic Member

Guillaume Dumas

Associate Professor, Université de Montréal, Department of Psychiatry and Addiction

See the details

Associate Industry Member

Gintare Karolina Dziugaite

Senior Research Scientist, Google DeepMind

See the details

Associate Academic Member

Samira Ebrahimi Kahou

Associate Professor, École de technologie supérieure (ETS), Department of Computer Engineering and Information Technology

Canada CIFAR AI Chair

See the details

Core Academic Member

Golnoosh Farnadi

Assistant Professor, McGill University, School of Computer Science

Canada CIFAR AI Chair

See the details

Associate Academic Member

Christian Gagné

Full Professor, Université Laval, Department of Electrical and Computer Engineering

Canada CIFAR AI Chair

See the details

Associate Academic Member

Pascal Germain

Assistant Professor, Université Laval, Department of Computer Science and Software Engineering

Canada CIFAR AI Chair

See the details

Core Academic Member

Gauthier Gidel

Assistant Professor, Université de Montréal, Department of Computer Science and Operations Research

Canada CIFAR AI Chair

See the details

Associate Academic Member

Jin Guo

Assistant Professor, McGill University, School of Computer Science

See the details

Associate Academic Member

Julie Hussin

Associate Professor, Université de Montréal

See the details

Affiliate Member

Khimya Khetarpal

Research Scientist, Google DeepMind

See the details

Associate Academic Member

Foutse Khomh

Professor, Polytechnique Montréal, Department of Computer Engineering and Software Engineering

Canada CIFAR AI Chair

See the details

Associate Academic Member

Eric Kolaczyk

Professor, McGill University, Department of Mathematics and Statistics

See the details

Affiliate Member

Shin (Alexandre) Koseki

Assistant Professor, Université de Montréal, School of Urban Planning and Landscape Architecture

See the details

Core Academic Member

Simon Lacoste-Julien

Associate Scientific Director, Mila, Associate Professor, Université de Montréal, Department of Computer Science and Operations Research

Canada CIFAR AI Chair

See the details

Core Academic Member

Guillaume Lajoie

Assistant Professor, Université de Montréal, Department of Mathematics and Statistics

Canada CIFAR AI Chair

See the details

Associate Academic Member

Xue (Steve) Liu

Full Professor, McGill University, School of Computer Science

See the details

Affiliate Member

Tegan Maharaj

Tenured Professor, University of Toronto

See the details

Core Academic Member

Chengzhi Mao

Assistant Professor, McGill University, Department of Electrical and Computer Engineering

See the details

Core Academic Member

AJung Moon

Assistant Professor, McGill University, Department of Electrical and Computer Engineering

See the details

Associate Academic Member

Eilif Benjamin Muller

Assistant Professor, Université de Montréal, Department of Neurosciences

Canada CIFAR AI Chair

See the details

Core Academic Member

Derek Nowrouzezahrai

Associate Professor, McGill University, Department of Electrical and Computer Engineering

Canada CIFAR AI Chair

See the details

Associate Industry Member

Alexandra Olteanu

Principal Researcher and founding members of the FATE Montréal Team, Microsoft Research, Montréal

See the details

Core Academic Member

Chris Pal

Full Professor, Polytechnique Montréal, Department of Computer Engineering and Software Engineering

Canada CIFAR AI Chair

See the details

Associate Academic Member

Pablo Piantanida

Full Professor, Université Paris-Saclay

See the details

Core Academic Member

Joelle Pineau

Associate Professor, McGill University, School of Computer Science

Canada CIFAR AI Chair

See the details

Associate Academic Member

Dan Poenaru

Professor, McGill University, Department of Pediatric Surgery

See the details

Core Academic Member

Reihaneh Rabbany

Assistant Professor, McGill University, School of Computer Science

Canada CIFAR AI Chair

See the details

Associate Academic Member

Mirco Ravanelli

Assistant Professor, Concordia University, Gina Cody School of Engineering and Computer Science

See the details

Core Academic Member

Siva Reddy

Assistant Professor, McGill University, School of Computer Science and Department of Linguistics

Canada CIFAR AI Chair

See the details

Associate Academic Member

Catherine Régis

Full Professor, Université de Montréal

Canada CIFAR AI Chair

See the details

Core Academic Member

Blake Richards

Associate Professor, McGill University, School of Computer Science and Department of Neurology and Neurosurgery

Canada CIFAR AI Chair

See the details

Core Academic Member

Irina Rish

Full Professor, Université de Montréal, Department of Computer Science and Operations Research Department

Canada CIFAR AI Chair

See the details

Core Academic Member

David Rolnick

Assistant Professor, McGill University, School of Computer Science

Canada CIFAR AI Chair

See the details

Core Industry Member

Adriana Romero Soriano

Research Scientist, Meta AI Research (FAIR)

Canada CIFAR AI Chair

See the details

Associate Industry Member

Negar Rostamzadeh

Senior Research Scientist, Google Brain Ethical AI Team

See the details

Affiliate Member

David Scott Krueger

Assistant professor, University of Cambridge, Department of Engineering, Information Engineering Division

See the details

Affiliate Member

Xujie Si

Assistant Professor, University of Toronto, Department of Computer Science

Canada CIFAR AI Chair

See the details

Core Academic Member

Dhanya Sridhar

Assistant Professor, Université de Montréal, Department of Computer Science and Operations Research

Canada CIFAR AI Chair

See the details

Associate Industry Member

Kory Wallace Mathewson

Research Scientist, DeepMind

See the details

Core Academic Member

Guy Wolf

Associate Professor, Université de Montréal, Department of Mathematics and Statistics

Canada CIFAR AI Chair

See the details

Associate Academic Member

Amal Zouaq

Associate Professor, Polytechnique Montréal, Department of Computer Engineering and Software Engineering

See the details

Publications

A Unifying Framework for Fairness-Aware Influence Maximization

Golnoosh Farnadi

Behrouz Babaki

Michel Gendreau

The problem of selecting a subset of nodes with greatest influence in a graph, commonly known as influence maximization, has been well studi… (see more)ed over the past decade. This problem has real world applications which can potentially affect lives of individuals. Algorithmic decision making in such domains raises concerns about their societal implications. One of these concerns, which surprisingly has only received limited attention so far, is algorithmic bias and fairness. We propose a flexible framework that extends and unifies the existing works in fairness-aware influence maximization. This framework is based on an integer programming formulation of the influence maximization problem. The fairness requirements are enforced by adding linear constraints or modifying the objective function. Contrary to the previous work which designs specific algorithms for each variant, we develop a formalism which is general enough for specifying different notions of fairness. A problem defined in this formalism can be then solved using efficient mixed integer programming solvers. The experimental evaluation indicates that our framework not only is general but also is competitive with existing algorithms.

2020-04-20

Companion Proceedings of the Web Conference 2020 (published)

doi.org

Managing AI Risks in an Era of Rapid Progress

Yoshua Bengio

Geoffrey E. Hinton

Andrew Yao

Dawn Song

Pieter Abbeel

Yuval Noah Harari

Ya-Qin Zhang

Lan Xue