Benjamin Prud'homme

Vice-président, Politiques publiques, sécurité et affaires mondiales, Équipe de direction

Biographie

Benjamin Prud'homme est Vice-président, Politiques publiques, sécurité et affaires mondiales. Il est membre-expert à l'OCDE (OCDE.AI), aux Nations Unies (Réseau consultatif d'experts en IA) et à l'UNESCO (AI Ethics Experts Without Borders). Il co-dirige le projet Creating Diversity and Substantive Equality in AI Ecoystems pour le Partenariat mondial sur l'IA (PMIA) et contribue au Rapport scientifique international sur la sécurité de l'IA avancée, présidé par Yoshua Bengio. En 2023, il a co-dirigé la publication Mila-UNESCO « Angles morts de la gouvernance de l'IA ». Benjamin est avocat et siège sur les conseils d'administration de l'Association canadienne des libertés civile, de l'Observatoire québécois des inégalités et de l'Aide juridique (Montréal).

Publications

International AI Safety Report: First Key Update, Capabilities and Risk Implications

Prof. Yoshua Bengio

Stephen Clare

Carina Prunkl

Maksym Andriushchenko

BEN BUCKNALL

Philip Fox

Tiancheng Hu

Cameron Jones

Sam Manning

Nestor Maslej

Vasilios Mavroudis

Conor McGlynn

Malcolm Murray

Shalaleh Rismani

Charlotte Stix

Lucia Velasco

Nicole Wheeler

Daniel Privitera

Sören Mindermann

Daron Acemoglu … (voir 36 de plus)

Thomas G. Dietterich

Fredrik Heintz

Geoffrey Hinton

Nick Jennings

Susan Leavy

Teresa Ludermir

Vidushi Marda

Helen Margetts

John McDermid

Jane Munga

Arvind Narayanan

Alondra Nelson

Clara Neppel

Sarvapali D. (Gopal) Ramchurn

Stuart Russell

Marietje Schaake

Bernhard Schölkopf

Alvaro Soto

Lee Tiedrich

Gael Varoquaux

Andrew Yao

Ya-Qin Zhang

Lambrini Das

Claire Dennis

Arianna Dini

Freya Hempleman

Samuel Kenny

Patrick King

Hannah Merchant

Jamie-Day Rawal

Rose Woolhouse

The field of AI is moving too quickly for a single yearly publication to keep pace. Significant changes can occur on a timescale of months, … (voir plus)sometimes weeks. This is why we are releasing Key Updates: shorter, focused reports that highlight the most important developments between full editions of the International AI Safety Report. With these updates, we aim to provide policymakers, researchers, and the public with up-to-date information to support wise decisions about AI governance. This first Key Update focuses on areas where especially significant changes have occurred since January 2025: advances in general-purpose AI systems' capabilities, and the implications for several critical risks. New training techniques have enabled AI systems to reason step-by-step and operate autonomously for longer periods, allowing them to tackle more kinds of work. However, these same advances create new challenges across biological risks, cyber security, and oversight of AI systems themselves. The International AI Safety Report is intended to help readers assess, anticipate, and manage risks from general-purpose AI systems. These Key Updates ensure that critical developments receive timely attention as the field rapidly evolves.

2025-10-21

SuperIntelligence - Robotics - Safety & Alignment (publié)

doi.org

International AI Safety Report

Yoshua Bengio

Bronwyn Fox

André Carlos Ponce de Leon Ferreira de Carvalho

Mona Nemer

Raquel Pezoa Rivera

Yi Zeng

Juha Heikkilä

Guillaume Avrin

Antonio Krüger

Balaraman Ravindran

Hammam Riza

Ciarán Seoighe

Ziv Katzir

Andrea Monti

Hiroaki Kitano

Nusu Mwamanzi

Fahad Albalawi

José Ramón López Portillo

Haroon Sheikh

Gill Jolly … (voir 86 de plus)

Olubunmi Ajala

Jerry Sheehan

Dominic Vincent Ligot

Kyoung Mu Lee

Crystal Rugege

Denise Wong

Nuria Oliver

Christian Busch

Ahmet Halit Hatip

Oleksii Molchanovskyi

Marwan Alserkal

Chris Johnson

Amandeep Singh Gill

Saif M. Khan

Sören Mindermann

Daniel Privitera

Tamay Besiroglu

Rishi Bommasani

Stephen Casper

Yejin Choi

Philip Fox

Ben Garfinkel

Danielle Goldfarb

Hoda Heidari

Anson Ho

Sayash Kapoor

Leila Khalatbari

Shayne Longpre

Sam Manning

Vasilios Mavroudis

Mantas Mazeika

Julian Michael

Jessica Newman

Kwan Yee Ng

Chinasa T. Okolo

Deborah Raji

Girish Sastry

Elizabeth Seger

Theodora Skeadas

Tobin South

Daron Acemoglu

Olubayo Adekanmbi

David Dalrymple

Thomas G. Dietterich

Edward W. Felten

Pascale Fung

Pierre-Olivier Gourinchas

Fredrik Heintz

Geoffrey Hinton

Nick Jennings

Andreas Krause

Susan Leavy

Percy Liang

Teresa Ludermir

Vidushi Marda

Emma Strubell

Florian Tramèr

Lucia Velasco

Nicole Wheeler

Helen Margetts

John McDermid

Jane Munga

Arvind Narayanan

Alondra Nelson

Clara Neppel

Alice Oh

Gopal Ramchurn

Stuart Russell

Marietje Schaake

Bernhard Schölkopf

Dawn Song

Alvaro Soto

Lee Tiedrich

Gael Varoquaux

Andrew Yao

Ya-Qin Zhang

Baran Acar

Ben Clifford

Lambrini Das

Claire Dennis

Freya Hempleman

Hannah Merchant

Rian Overy

Ben Snodin

Jonathan Barry

Benjamin Prud’homme

The first International AI Safety Report comprehensively synthesizes the current evidence on the capabilities, risks, and safety of advanced… (voir plus) AI systems. The report was mandated by the nations attending the AI Safety Summit in Bletchley, UK. Thirty nations, the UN, the OECD, and the EU each nominated a representative to the report's Expert Advisory Panel. A total of 100 AI experts contributed, representing diverse perspectives and disciplines. Led by the report's Chair, these independent experts collectively had full discretion over the report's content.

2024-12-31

arXiv (prépublication)

doi.org

arxiv.org

The Singapore Consensus on Global AI Safety Research Priorities

Yoshua Bengio

Tegan Maharaj

Luke Ong

Stuart Russell

Dawn Song

Max Tegmark

Lan Xue

Ya-Qin Zhang

Stephen Casper

Wan Sie Lee

Sören Mindermann

Vanessa Wilfred

Vidhisha Balachandran

Fazl Barez

Michael Belinsky

Ima Bello

Malo Bourgon

Mark Brakel

Simeon Campos

Duncan Cass-Beggs … (voir 67 de plus)

Jiahao Chen

Rumman Chowdhury

Chua Kuan Seah

Jeff Clune

Juntao Dai

Agnes Delaborde

Nouha Dziri

Francisco Eiras

Joshua Engels

Jinyu Fan

Adam Gleave

Noah Goodman

Fynn Heide

Johannes Heidecke

Dan Hendrycks

Cyrus Hodes

Bryan Low

Minlie Huang

Sami Jawhar

Jingyu Wang

Adam Kalai

Meindert Kamphuis

Mohan Kankanhalli

Subhash Kantamneni

Mathias Kirk Bonde

Thomas Kwa

Jeffrey Ladish

Kwok Yan Lam

Wan Sie Lee

Taewhi Lee

Xiaojian Li

Jiajun Liu

Chaochao Lu

Yifan Mai

Richard Mallah

Julian Michael

Nicolas Moës

Simon Moeller

Kihyuk Nam

Kwan Yee Ng

Mark Nitzberg

Besmira Nushi

Seán Ó hÉigeartaigh

Alejandro Ortega

Pierre Peigné

James Petrie

Benjamin Prud'homme

Reihaneh Rabbany

Nayat Sanchez-Pi

Sarah Schwettmann

Buck Shlegeris

SAAD SIDDIQUI

Anu Sinha

Martin Soto

Cheston Tan

Anthony Tung

William Tjhi

Robert Trager

Brian Tse

Anthony Tung

John Willes

Denise Wong

Wei Xu

Rongwu Xu

Yi Zeng

Hongjiang Zhang

Djordje Zikelic

Rapidly improving AI capabilities and autonomy hold significant promise of transformation, but are also driving vigorous debate on how to en… (voir plus)sure that AI is safe, i.e., trustworthy, reliable, and secure. Building a trusted ecosystem is therefore essential – it helps people embrace AI with confidence and gives maximal space for innovation while avoiding backlash. This requires policymakers, industry, researchers and the broader public to collectively work toward securing positive outcomes from AI’s development. AI safety research is a key dimension. Given that the state of science today for building trustworthy AI does not fully cover all risks, accelerated investment in research is required to keep pace with commercially driven growth in system capabilities. Goals: The 2025 Singapore Conference on AI (SCAI): International Scientific Exchange on AI Safety aims to support research in this important space by bringing together AI scientists across geographies to identify and synthesise research priorities in AI safety. The result, The Singapore Consensus on Global AI Safety Research Priorities, builds on the International AI Safety Report-A (IAISR) chaired by Yoshua Bengio and backed by 33 governments. By adopting a defence-in-depth model, this document organises AI safety research domains into three types: challenges with creating trustworthy AI systems (Development), challenges with evaluating their risks (Assessment), and challenges with monitoring and intervening after deployment (Control). Through the Singapore Consensus, we hope to globally facilitate meaningful conversations between AI scientists and AI policymakers for maximally beneficial outcomes. Our goal is to enable more impactful R&D efforts to rapidly develop safety and evaluation mechanisms and foster a trusted ecosystem where AI is harnessed for the public good.

2024-12-31

arXiv.org (prépublication)

doi.org

arxiv.org

Inherent privacy limitations of decentralized contact tracing apps

Yoshua Bengio

Daphne Ippolito

Richard Janda

Max Jarvie

Benjamin Prud'homme

Jean-François Rousseau

Abhinav Sharma

Yun William Yu

2020-06-24

J. Am. Medical Informatics Assoc. (publié)

doi.org

COVI White Paper - Version 1.1

Hannah Alsdurf

Yoshua Bengio

Tristan Deleu

Prateek Gupta

Daphne Ippolito

Richard Janda

Max Jarvies

Tyler Kolody

Sekoul Krastev

Tegan Maharaj

Robert Obryk

Dan Pilat

Nasim Rahaman

Jean-François Rousseau

Abhinav Sharma

Brooke Struck … (voir 3 de plus)

Jian Tang

Martin Weiss

Yun William Yu

The SARS-CoV-2 (Covid-19) pandemic has caused significant strain on public health institutions around the world. Contact tracing is an essen… (voir plus)tial tool to change the course of the Covid-19 pandemic. Manual contact tracing of Covid-19 cases has significant challenges that limit the ability of public health authorities to minimize community infections. Personalized peer-to-peer contact tracing through the use of mobile apps has the potential to shift the paradigm. Some countries have deployed centralized tracking systems, but more privacy-protecting decentralized systems offer much of the same benefit without concentrating data in the hands of a state authority or for-profit corporations. Machine learning methods can circumvent some of the limitations of standard digital tracing by incorporating many clues and their uncertainty into a more graded and precise estimation of infection risk. The estimated risk can provide early risk awareness, personalized recommendations and relevant information to the user. Finally, non-identifying risk data can inform epidemiological models trained jointly with the machine learning predictor. These models can provide statistical evidence for the importance of factors involved in disease transmission. They can also be used to monitor, evaluate and optimize health policy and (de)confinement scenarios according to medical and economic productivity indicators. However, such a strategy based on mobile apps and machine learning should proactively mitigate potential ethical and privacy risks, which could have substantial impacts on society (not only impacts on health but also impacts such as stigmatization and abuse of personal data). Here, we present an overview of the rationale, design, ethical considerations and privacy strategy of `COVI,' a Covid-19 public peer-to-peer contact tracing and risk awareness mobile application developed in Canada.

2019-12-31

arXiv (prépublication)

doi.org

arxiv.org

COVI White Paper-Version 1.1

H. Alsdurf

Yoshua Bengio

T. Deleu

Prateek Gupta

Daphne Ippolito

R. Janda

Max Jarvie