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Research#ai safety📝 BlogAnalyzed: Jan 3, 2026 01:45

Yoshua Bengio - Designing out Agency for Safe AI

Published:Jan 15, 2025 19:21
1 min read
ML Street Talk Pod

Analysis

This article summarizes a podcast interview with Yoshua Bengio, a leading figure in deep learning, focusing on AI safety. Bengio discusses the potential dangers of "agentic" AI, which are goal-seeking systems, and advocates for building powerful AI tools without giving them agency. The interview covers crucial topics such as reward tampering, instrumental convergence, and global AI governance. The article highlights the potential of non-agent AI to revolutionize science and medicine while mitigating existential risks. The inclusion of sponsor messages and links to Bengio's profiles and research further enriches the content.
Reference

“Bengio talks about AI safety, why goal-seeking “agentic” AIs might be dangerous, and his vision for building powerful AI tools without giving them agency.”

PermalinkML Street Talk Pod
Research#llm📝 BlogAnalyzed: Jan 3, 2026 07:52

Paris AI Safety Breakfast #3: Yoshua Bengio

Published:Oct 16, 2024 14:28
1 min read
Future of Life

Analysis

The article announces an event featuring Yoshua Bengio discussing AI safety. It highlights key topics like AI capabilities, loss-of-control scenarios, and defense strategies. The focus is on proactive versus reactive approaches to AI safety.
Reference

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PermalinkFuture of Life
Research#AI Safety📝 BlogAnalyzed: Dec 29, 2025 07:30

AI Sentience, Agency and Catastrophic Risk with Yoshua Bengio - #654

Published:Nov 6, 2023 20:50
1 min read
Practical AI

Analysis

This article from Practical AI discusses AI safety and the potential catastrophic risks associated with AI development, featuring an interview with Yoshua Bengio. The conversation focuses on the dangers of AI misuse, including manipulation, disinformation, and power concentration. It delves into the challenges of defining and understanding AI agency and sentience, key concepts in assessing AI risk. The article also explores potential solutions, such as safety guardrails, national security protections, bans on unsafe systems, and governance-driven AI development. The focus is on the ethical and societal implications of advanced AI.
Reference

“Yoshua highlights various risks and the dangers of AI being used to manipulate people, spread disinformation, cause harm, and further concentrate power in society.”

PermalinkPractical AI
AI Research#Consciousness in AI📝 BlogAnalyzed: Jan 3, 2026 07:18

ICLR 2020: Yoshua Bengio and the Nature of Consciousness

Published:May 22, 2020 21:49
1 min read
ML Street Talk Pod

Analysis

This article summarizes Yoshua Bengio's ICLR 2020 keynote, focusing on the intersection of deep learning and consciousness. It highlights key topics such as attention, sparse factor graphs, causality, and systematic generalization. The article also mentions Bengio's exploration of System 1 and System 2 thinking, drawing parallels to Daniel Kahneman's work. The provided links offer access to the talk and related research papers.
Reference

“Bengio takes on many future directions for research in Deep Learning such as the role of attention in consciousness, sparse factor graphs and causality, and the study of systematic generalization.”

PermalinkML Street Talk Pod
Ethics#AI Safety👥 CommunityAnalyzed: Jan 10, 2026 16:56

Yoshua Bengio Expresses Concerns Regarding the Future of AI

Published:Nov 19, 2018 20:40
1 min read
Hacker News

Analysis

This article highlights the growing concerns of prominent AI researchers about the potential risks associated with the rapid advancement of artificial intelligence. It's crucial to examine these perspectives to foster a more responsible development of AI technologies and mitigate potential negative impacts.
Reference

“Deep learning pioneer Yoshua Bengio is worried about AI’s future.”

PermalinkHacker News
Research#deep learning📝 BlogAnalyzed: Dec 29, 2025 17:50

Yoshua Bengio on Deep Learning

Published:Oct 20, 2018 17:02
1 min read
Lex Fridman Podcast

Analysis

This article summarizes Yoshua Bengio's significant contributions to deep learning. It highlights his role, alongside Geoffrey Hinton and Yann LeCun, as a key figure in the field's development over the past three decades. The article mentions his high citation count, indicating the impact of his work. It also provides information on where to find the video version of the podcast, directing readers to Lex Fridman's website and social media platforms for further engagement. The article serves as a brief introduction to Bengio's influence and the availability of related content.
Reference

“Cited 139,000 times, he has been integral to some of the biggest breakthroughs in AI over the past 3 decades.”

PermalinkLex Fridman Podcast