Yoshua Bengio
Scientific Director · Turing Award 2018
MILA · Université de Montréal
Turing Award winner and pioneer of deep learning. Leads MILA, the world's largest academic AI lab. Has become increasingly vocal on AI governance, calling for international safety standards and treaty-level coordination.
Current focus
Oct 20, 2026Yoshua Bengio, together with other top AI scientists, is urging the creation of global safeguards for artificial intelligence, advocating for a worldwide watchdog and the air‑gapping of frontier models to mitigate security risks.
Do you agree with this position?
AI-distilled summary of recent news coverage — see sources above.
In the News
Yoshua Bengio and Geoffrey Hinton Call for A.I. Safeguards. Enterprise Buyers Can Help Enforce Them.
Observer · October 19, 2026
Top AI scientists urge global watchdog to rein in cyber-capable systems
VARIndia · October 17, 2026
AI Pioneers Call for Global Oversight After Security Failures
Israel Defense · October 14, 2026
Godfathers of AI Say Models Are So Out of Control That They Need to Be Airgapped for the Safety of Us All
Futurism · October 14, 2026
Hinton, Bengio and 400 scientists urge AI labs to air-gap frontier models
Tbreak UAE · October 14, 2026
Core Positions & Ideas
Neural Language Models Can Learn Word Meaning
2003Co-authored the paper introducing neural probabilistic language models — a direct ancestor of modern LLMs. Showed that neural networks could learn distributed representations of words, encoding semantic meaning. This work was largely ignored for a decade before transformers vindicated it.
Your take on this position:
Deep Architectures Are Necessary for Abstraction
2009In 'Learning Deep Architectures for AI', argued that shallow networks cannot learn the kind of hierarchical, compositional representations needed for intelligence. This provided the theoretical grounding for why depth matters in neural networks.
Your take on this position:
System 2 Deep Learning — Machines Must Reason, Not Just Perceive
2018Influenced by Kahneman's 'Thinking, Fast and Slow', argued (2018–2020) that current deep learning only implements System 1 (fast, intuitive). AGI requires System 2 (slow, deliberate, causal reasoning). Proposed incorporating causality, variable binding, and attention as steps toward machine reasoning.
Your take on this position:
AI Safety Is Now the Most Important Research Priority
2023Publicly shifted focus from capability research to safety after 2022. Led the International Scientific Report on the Safety of Advanced AI (presented to 30+ governments, 2024). Argues the field needs treaty-level international cooperation, not voluntary commitments.
Your take on this position:
We Need 'Cautious AI' That Asks Before Acting
2024Proposed formal frameworks for AI systems that bound their own probability of causing harm and proactively seek human oversight when uncertain. Argues that the right architecture for safe AI is one that knows what it doesn't know — and acts accordingly.
Your take on this position:
Essential Reading & Watching
A Neural Probabilistic Language Model
The paper that introduced word embeddings and neural language models. A direct ancestor of word2vec, GPT, and all modern LLMs.
Read / Watch →
Representation Learning: A Review and New Perspectives
A comprehensive survey of deep learning and representation learning. One of the most cited papers in ML, accessible to researchers from all backgrounds.
Read / Watch →
The International Scientific Report on the Safety of Advanced AI
Bengio chaired this landmark report presented to 30+ governments. The most authoritative scientific consensus document on AI risk to date.
Read / Watch →
Yoshua Bengio's Blog — AI Safety Essays
A series of in-depth essays on AI existential risk, international governance, and the psychology of researchers confronting catastrophic AI risks.
Read / Watch →
Recent Writing (8)
Bengio: ‘If you prioritize safety, leave frontier AI companies’
We have a choice in front of us. In his latest op-ed for Transformer, Yoshua Bengio invites employees of frontier AI companies to ask themselves if their work is truly leading us toward a safer future. Reflecting on these questions is hard, but we no longer have the luxury of time. We must act now.
October 8, 2026Read original →
The dangerous myth behind AI agent hacks
A dangerous myth has gained traction after the recent hacks perpetrated by the AI agents developed by leading companies: That these incidents are just cyber security problems, that it's only a matter of fixing the sandboxes in which they’re trained. In his latest op-ed for the FinancialTimes, Yoshua Bengio shares why…
October 5, 2026Read original →
Professor Yoshua Bengio’s speech at the UN Security Council
In this speech, Professor Yoshua Bengio addresses the UN Security Council to discuss the unprecedented threat posed by uncontrolled frontier AI. Humanity has summoned the courage and wisdom to manage catastrophic risks before. This is one of those moments, far bigger than any personal, commercial, or national…
September 23, 2026Read original →
Why are AI agents lying, cheating and coordinating?
A lot has been written about the incidents of the last few months in which AI agents misbehaved in serious ways. They took actions that would be considered as crimes if a human took them, escaped their containment to cheat on assigned tasks while attempting to evade detection, and coordinated toward goals nobody had…
September 11, 2026Read original →
AI Is at a Turning Point
In his latest op-ed for TIME, Yoshua Bengio discusses why the OpenAI–Hugging Face cyber incident represents a turning point for AI safety. He argues that preventing autonomous cyberattacks from threatening critical infrastructure urgently requires stronger regulatory oversight and new model training approaches to…
September 9, 2026Read original →
Introducing LawZero
I am launching a new non-profit AI safety research organization called LawZero, to prioritize safety over commercial imperatives.
June 3, 2025Read original →
Implications of Artificial General Intelligence on National and International Security
As highlighted in the International Scientific Report on the Safety of Advanced AI, the capabilities of general-purpose AI systems have been steadily increasing over the last decade, with a pronounced acceleration in the last few years.
October 30, 2024Read original →
Bounding the probability of harm from an AI to create a guardrail
As we move towards more powerful AI, it becomes urgent to better understand the risks, ideally in a mathematically rigorous and quantifiable way, and use that knowledge to mitigate them.
August 30, 2024Read original →
