Portrait of David Scott Krueger

David Scott Krueger

Core Academic Member
kruegerd@mila.quebec
Assistant professor, Université de Montréal, Department of Computer Science and Operations Research (DIRO)
Research Topics
Deep Learning
Representation Learning
Website
Google Scholar
LinkedIn
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Biography

David Krueger is an Assistant Professor in Robust, Reasoning and Responsible AI in the Department of Computer Science and Operations Research (DIRO) at University of Montreal, and a Core Academic Member at Mila - Quebec Artificial Intelligence Institute, UC Berkeley's Center for Human-Compatible AI (CHAI), and the Center for the Study of Existential Risk (CSER). His work focuses on reducing the risk of human extinction from artificial intelligence (AI x-risk) through technical research as well as education, outreach, governance and advocacy.

His research spans many areas of Deep Learning, AI Alignment, AI Safety and AI Ethics, including alignment failure modes, algorithmic manipulation, interpretability, robustness, and understanding how AI systems learn and generalize. He has been featured in media outlets including ITV's Good Morning Britain, Al Jazeera's Inside Story, France 24, New Scientist and the Associated Press.

David completed his graduate studies at the University of Montreal and Mila - Quebec Artificial Intelligence Institute, working with Yoshua Bengio, Roland Memisevic, and Aaron Courville.

Current Students

Alan Chan
PhD - Université de Montréal
Principal supervisor :
Nicolas Le Roux
Website
Google Scholar
Brandon Jaipersaud
Collaborating researcher
Website
Github
Google Scholar

Publications

Managing extreme AI risks amid rapid progress
Yoshua Bengio
Geoffrey Hinton
Andrew Yao
Dawn Song
Pieter Abbeel
Trevor Darrell
Yuval Noah Harari
Ya-Qin Zhang
Lan Xue
Shai Shalev-Shwartz
Gillian K. Hadfield
Jeff Clune
Tegan Maharaj
Frank Hutter
Atilim Güneş Baydin
Sheila McIlraith
Qiqi Gao
Ashwin Acharya
David Scott Krueger
Anca Dragan … (see 5 more)
Philip Torr
Stuart Russell
Daniel Kahneman
Jan Brauner
Sören Mindermann
Preparation requires technical research and development, as well as adaptive, proactive governance Artificial intelligence (AI) is progressi… (see more)ng rapidly, and companies are shifting their focus to developing generalist AI systems that can autonomously act and pursue goals. Increases in capabilities and autonomy may soon massively amplify AI’s impact, with risks that include large-scale social harms, malicious uses, and an irreversible loss of human control over autonomous AI systems. Although researchers have warned of extreme risks from AI (1), there is a lack of consensus about how to manage them. Society’s response, despite promising first steps, is incommensurate with the possibility of rapid, transformative progress that is expected by many experts. AI safety research is lagging. Present governance initiatives lack the mechanisms and institutions to prevent misuse and recklessness and barely address autonomous systems. Drawing on lessons learned from other safety-critical technologies, we outline a comprehensive plan that combines technical research and development (R&D) with proactive, adaptive governance mechanisms for a more commensurate preparation.
2023-10-26
Science (published)
doi.org
Managing extreme AI risks amid rapid progress
Yoshua Bengio
Geoffrey Hinton
Andrew Yao
Dawn Song
Pieter Abbeel
Trevor Darrell
Yuval Noah Harari
Ya-Qin Zhang
Lan Xue
Shai Shalev-Shwartz
Gillian K. Hadfield
Jeff Clune
Tegan Maharaj
Frank Hutter
Atilim Güneş Baydin
Sheila McIlraith
Qiqi Gao
Ashwin Acharya
David Scott Krueger
Anca Dragan … (see 5 more)
Philip Torr
Stuart Russell
Daniel Kahneman
Jan Brauner
Sören Mindermann
2023-10-26
Science (published)
doi.org
Managing extreme AI risks amid rapid progress
Yoshua Bengio
Geoffrey Hinton
Andrew Yao
Dawn Song
Pieter Abbeel
Trevor Darrell
Yuval Noah Harari
Ya-Qin Zhang
Lan Xue
Shai Shalev-Shwartz
Gillian K. Hadfield
Jeff Clune
Tegan Maharaj
Frank Hutter
Atilim Güneş Baydin
Sheila McIlraith
Qiqi Gao
Ashwin Acharya
David Scott Krueger
Anca Dragan … (see 5 more)
Philip Torr
Stuart Russell
Daniel Kahneman
Jan Brauner
Sören Mindermann
2023-10-26
Science (published)
doi.org
Managing extreme AI risks amid rapid progress
Yoshua Bengio
Geoffrey Hinton
Andrew Yao
Dawn Song
Pieter Abbeel
Trevor Darrell
Yuval Noah Harari
Ya-Qin Zhang
Lan Xue
Shai Shalev-Shwartz
Gillian K. Hadfield
Jeff Clune
Tegan Maharaj
Frank Hutter
Atilim Güneş Baydin
Sheila McIlraith
Qiqi Gao
Ashwin Acharya
David Scott Krueger
Anca Dragan … (see 5 more)
Philip Torr
Stuart Russell
Daniel Kahneman
Jan Brauner
Sören Mindermann
Preparation requires technical research and development, as well as adaptive, proactive governance Artificial intelligence (AI) is progressi… (see more)ng rapidly, and companies are shifting their focus to developing generalist AI systems that can autonomously act and pursue goals. Increases in capabilities and autonomy may soon massively amplify AI’s impact, with risks that include large-scale social harms, malicious uses, and an irreversible loss of human control over autonomous AI systems. Although researchers have warned of extreme risks from AI (1), there is a lack of consensus about how to manage them. Society’s response, despite promising first steps, is incommensurate with the possibility of rapid, transformative progress that is expected by many experts. AI safety research is lagging. Present governance initiatives lack the mechanisms and institutions to prevent misuse and recklessness and barely address autonomous systems. Drawing on lessons learned from other safety-critical technologies, we outline a comprehensive plan that combines technical research and development (R&D) with proactive, adaptive governance mechanisms for a more commensurate preparation.
2023-10-26
Science (published)
doi.org
Managing extreme AI risks amid rapid progress
Yoshua Bengio
Geoffrey Hinton
Andrew Yao
Dawn Song
Pieter Abbeel
Trevor Darrell
Yuval Noah Harari
Ya-Qin Zhang
Lan Xue
Shai Shalev-Shwartz
Gillian K. Hadfield
Jeff Clune
Tegan Maharaj
Frank Hutter
Atilim Güneş Baydin
Sheila McIlraith
Qiqi Gao
Ashwin Acharya
David Scott Krueger
Anca Dragan … (see 5 more)
Philip Torr
Stuart Russell
Daniel Kahneman
Jan Brauner
Sören Mindermann
Preparation requires technical research and development, as well as adaptive, proactive governance Artificial intelligence (AI) is progressi… (see more)ng rapidly, and companies are shifting their focus to developing generalist AI systems that can autonomously act and pursue goals. Increases in capabilities and autonomy may soon massively amplify AI’s impact, with risks that include large-scale social harms, malicious uses, and an irreversible loss of human control over autonomous AI systems. Although researchers have warned of extreme risks from AI (1), there is a lack of consensus about how to manage them. Society’s response, despite promising first steps, is incommensurate with the possibility of rapid, transformative progress that is expected by many experts. AI safety research is lagging. Present governance initiatives lack the mechanisms and institutions to prevent misuse and recklessness and barely address autonomous systems. Drawing on lessons learned from other safety-critical technologies, we outline a comprehensive plan that combines technical research and development (R&D) with proactive, adaptive governance mechanisms for a more commensurate preparation.
2023-10-26
Science (published)
doi.org
Managing extreme AI risks amid rapid progress
Yoshua Bengio
Geoffrey Hinton
Andrew Yao
Dawn Song
Pieter Abbeel
Trevor Darrell
Yuval Noah Harari
Ya-Qin Zhang
Lan Xue
Shai Shalev-Shwartz
Gillian K. Hadfield
Jeff Clune
Tegan Maharaj
Frank Hutter
Atilim Güneş Baydin
Sheila McIlraith
Qiqi Gao
Ashwin Acharya
David Scott Krueger
Anca Dragan … (see 5 more)
Philip Torr
Stuart Russell
Daniel Kahneman
Jan Brauner
Sören Mindermann
Preparation requires technical research and development, as well as adaptive, proactive governance Artificial intelligence (AI) is progressi… (see more)ng rapidly, and companies are shifting their focus to developing generalist AI systems that can autonomously act and pursue goals. Increases in capabilities and autonomy may soon massively amplify AI’s impact, with risks that include large-scale social harms, malicious uses, and an irreversible loss of human control over autonomous AI systems. Although researchers have warned of extreme risks from AI (1), there is a lack of consensus about how to manage them. Society’s response, despite promising first steps, is incommensurate with the possibility of rapid, transformative progress that is expected by many experts. AI safety research is lagging. Present governance initiatives lack the mechanisms and institutions to prevent misuse and recklessness and barely address autonomous systems. Drawing on lessons learned from other safety-critical technologies, we outline a comprehensive plan that combines technical research and development (R&D) with proactive, adaptive governance mechanisms for a more commensurate preparation.
2023-10-26
Science (published)
doi.org
Managing AI Risks in an Era of Rapid Progress
Yoshua Bengio
Geoffrey Hinton
Andrew Yao
Dawn Song
Pieter Abbeel
Yuval Noah Harari
Ya-Qin Zhang
Lan Xue
Shai Shalev-Shwartz
Gillian K. Hadfield
Jeff Clune
Tegan Maharaj
Frank Hutter
Atilim Güneş Baydin
Sheila McIlraith
Qiqi Gao
Ashwin Acharya
David Scott Krueger
Anca Dragan
Philip Torr … (see 4 more)
Stuart Russell
Daniel Kahneman
Jan Brauner
Sören Mindermann
In this short consensus paper, we outline risks from upcoming, advanced AI systems. We examine large-scale social harms and malicious uses, … (see more)as well as an irreversible loss of human control over autonomous AI systems. In light of rapid and continuing AI progress, we propose priorities for AI R&D and governance.
2023-10-26
ArXiv (preprint)
doi.org
arxiv.org
Managing AI Risks in an Era of Rapid Progress
Yoshua Bengio
Geoffrey Hinton
Andrew Yao
Dawn Song
Pieter Abbeel
Yuval Noah Harari
Ya-Qin Zhang
Lan Xue
Shai Shalev-Shwartz
Gillian K. Hadfield
Jeff Clune
Tegan Maharaj
Frank Hutter
Atilim Güneş Baydin
Sheila McIlraith
Qiqi Gao
Ashwin Acharya
David Scott Krueger
Anca Dragan
Philip Torr … (see 4 more)
Stuart Russell
Daniel Kahneman
Jan Brauner
Sören Mindermann
In this short consensus paper, we outline risks from upcoming, advanced AI systems. We examine large-scale social harms and malicious uses, … (see more)as well as an irreversible loss of human control over autonomous AI systems. In light of rapid and continuing AI progress, we propose priorities for AI R&D and governance.
2023-10-26
ArXiv (preprint)
doi.org
arxiv.org
Managing AI Risks in an Era of Rapid Progress
Yoshua Bengio
Geoffrey Hinton
Andrew Yao
Dawn Song
Pieter Abbeel
Yuval Noah Harari
Trevor Darrell
Ya-Qin Zhang
Lan Xue
Shai Shalev-Shwartz
Gillian K. Hadfield
Jeff Clune
Tegan Maharaj
Frank Hutter
Atilim Güneş Baydin
Sheila McIlraith
Qiqi Gao
Ashwin Acharya
David Scott Krueger
Anca Dragan … (see 5 more)
Philip Torr
Stuart Russell
Daniel Kahneman
Jan Brauner
Sören Mindermann
2023-10-26
Science (published)
doi.org
arxiv.org
Managing AI Risks in an Era of Rapid Progress
Yoshua Bengio
Geoffrey Hinton
Andrew Yao
Dawn Song
Pieter Abbeel
Yuval Noah Harari
Ya-Qin Zhang
Lan Xue
Shai Shalev-Shwartz
Gillian K. Hadfield
Jeff Clune
Tegan Maharaj
Frank Hutter
Atilim Güneş Baydin
Sheila McIlraith
Qiqi Gao
Ashwin Acharya
David Scott Krueger
Anca Dragan
Philip Torr … (see 4 more)
Stuart Russell
Daniel Kahneman
Jan Brauner
Sören Mindermann
In this short consensus paper, we outline risks from upcoming, advanced AI systems. We examine large-scale social harms and malicious uses, … (see more)as well as an irreversible loss of human control over autonomous AI systems. In light of rapid and continuing AI progress, we propose priorities for AI R&D and governance.
2023-10-26
ArXiv (preprint)
doi.org
arxiv.org
Hazards from Increasingly Accessible Fine-Tuning of Downloadable Foundation Models
Alan Chan
Benjamin Bucknall
Herbie Bradley
David Scott Krueger
2023-10-23
NeurIPS.cc/2023/Workshop/SoLaR (spotlight)
openreview.net
openreview.net
Hazards from Increasingly Accessible Fine-Tuning of Downloadable Foundation Models
Alan Chan
Benjamin Bucknall
Herbie Bradley
David Scott Krueger
2023-10-23
NeurIPS.cc/2023/Workshop/SoLaR (spotlight)
doi.org
openreview.net