Toby Ord
As of October 2026, Toby Ord is a senior researcher at the Oxford Martin AI Governance Initiative and serves on the board of the Centre for the Governance of AI. He founded Giving What We Can in 2009, an international society whose members pledge to donate at least 10% of their income to effective charities. He was a research fellow at Oxford's Future of Humanity Institute from 2014 until 2019, and in March 2020 he published The Precipice, a book concluding that safeguarding our future is among the most pressing and neglected issues we face. In October 2025 he posted a preprint showing that a 100x gain from inference compute typically needs 10,000x more RL training compute.
- Now at
- Oxford Martin AI Governance Initiative and Centre for the Governance of AI
- Works
- 95
- Citations
- 2,331
- h-index
- 19
Publication numbers from OpenAlex, as of 15 October 2026.
Timeline
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2009
Founding Giving What We Can
Giving What We Can, an international society whose members pledge to donate at least 10% of their income to effective charities, launches in 2009.
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2014–2019
Research fellow at Oxford
At Oxford's Future of Humanity Institute, he works as a research fellow from 2014 until 2019.
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March 2020
Writing The Precipice
His book The Precipice is published in March 2020, concluding that safeguarding our future is among the most pressing and neglected issues we face.
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July 2024
Over 9,000 members
By July 2024, Giving What We Can reaches over 9,000 members, who have already donated $253 million to effective charities.
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October 2025
A preprint on RL scaling
In October 2025, he posts 'How Well Does RL Scale?', a preprint showing that a 100x gain from inference compute typically needs 10,000x more RL training compute.
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As of October 2026
Senior researcher in AI governance
He works as a senior researcher at the Oxford Martin AI Governance Initiative and serves on the board of the Centre for the Governance of AI. His work gives special focus to AI and how the world can best balance its risks with its benefits.
Sources and credits
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