Geoffrey Hinton
Pioneer of deep learning; professor emeritus, University of Toronto
Shared the 2018 Turing Award for the neural network research behind modern AI. Since leaving Google in 2023 he has spoken often about AI risk. He keeps no blog or public account, so this links to his university page, where his papers and talks are collected.
Read them in their own words
Published elsewhere, not by me — so you get real context beyond the name and the title.
Full interview: "Godfather of AI" on hopes, fears and predictions for future of AI
The long version of the interview where he says out loud why he left Google and what worries him now.
Key arguments & positions
- Has cited a "10 to 20 percent" chance of AI-caused catastrophe over coming decades.
- Argues AI could soon surpass human intelligence in most cognitive domains.
- Calls for urgent government regulation of frontier AI safety research.
Accomplishments
- Co-developed backpropagation (1986) and Boltzmann machines (1985).
- Mentored the researchers behind the 2012 "AlexNet" breakthrough.
- Shared the 2018 ACM Turing Award and won the 2024 Nobel Prize in Physics.
- Left his Google role in 2023 specifically to speak freely about AI risk.
Papers & key writings
- "Learning representations by back-propagating errors," Nature (1986)
- "A Learning Algorithm for Boltzmann Machines" (1985)
- "Visualizing Data using t-SNE" (2008)
- Full paper list on his faculty page
Links
Jobs
What they've said in public about careers, hiring and work. Each point links to its source.
- Public position
Said AI will replace people in "mundane intellectual labour" such as call-center and paralegal work, and called joblessness an urgent short-term threat to people's wellbeing.
The Diary of a CEO podcast (YouTube), June 2025 - Career advice
Asked about careers, he said "Train to be a plumber", because AI will take a long time to match people at physical work.
The Diary of a CEO podcast (YouTube), June 2025
Timeline
- 1986Co-writes the paper that popularized backpropagation.
- 2012AlexNet, with his students, wins ImageNet and restarts deep learning.
- 2018Shares the Turing Award with Bengio and LeCun.
- 2023Leaves Google so he can speak freely about AI risk.
- 2024Shares the Nobel Prize in Physics for foundational neural network work.
In the library
Nothing of theirs is filed in the hub yet. Browse the full library.
Recommended next
Hand-picked from the hub based on what Geoffrey Hinton covers.
Yoshua Bengio
Deep learning pioneer and Turing Award winner, now focused on AI risk. His site holds papers, talks and written positions; his Google Scholar list has the full publication record, most-cited first.
Why this: Covers AI safety and research too
These Are the Most Urgent AI Risks, According to 272 Experts
MIT Sloan summary of research surveying 272 experts on which AI risks could cause the most harm in the next five years.
Why this: Covers AI safety and research too
AISafety.info
Free question-and-answer site explaining AI risk arguments in plain language, founded by Rob Miles and maintained by volunteers. Answers are organised as linked questions from beginner to advanced, covering how AI is advancing, why systems may pursue goals, alignment research and AI governance. Includes Stampy, a chatbot that answers AI safety questions with sources. Open source on GitHub; run as a project of Ashgro Inc, a US 501(c)(3) charity.
Why this: Covers AI safety and research too
Concrete Problems in AI Safety
The 2016 paper that framed AI safety as a set of specific engineering problems — side effects, reward hacking, unsafe exploration — rather than a philosophical worry. Free on arXiv.
Why this: Covers AI safety and research too