Shane Legg
Co-founder and Chief AGI Scientist of Google DeepMind; leads its AGI Safety Council
- Co-Founder and Chief AGI Scientist, Google DeepMind12
Shane Legg is a co-founder of DeepMind, which Demis Hassabis wrote was founded in 2010 along with Legg and Mustafa Suleyman, and is Co-Founder and Chief AGI Scientist at Google DeepMind. Google DeepMind's responsibility page says Legg leads the AGI Safety Council, which works with the Responsibility and Safety Council to safeguard the lab's processes, systems and research against extreme risks from future AGI systems. Legg is a co-author of Universal Intelligence: A Definition of Machine Intelligence (2007), of Levels of AGI for Operationalizing Progress on the Path to AGI (ICML 2024), of the April 2025 post Taking a responsible path to AGI, and of the 2026 report From AGI to ASI.312456
Career
Shane Legg co-founded DeepMind in 2010 with Demis Hassabis and Mustafa Suleyman, and Hassabis's 2019 post describes Legg as the company's Chief Scientist. Google DeepMind now lists Legg as Co-Founder and Chief AGI Scientist.31
At Google DeepMind, Legg leads the AGI Safety Council, which analyzes AGI risk and best practices and recommends safety measures. The council works closely with the Responsibility and Safety Council to guard the lab's processes, systems and research against extreme risks from future AGI systems.12
Research
With Marcus Hutter, Legg published two 2007 papers on what intelligence means: a survey of about seventy informal definitions, and Universal Intelligence, which starts from well-known informal definitions and works toward a formal measure for machines. Legg is also among the authors of DeepMind's 2015 Nature paper on human-level control through deep reinforcement learning.748
Legg co-authored several safety papers from DeepMind, including Deep reinforcement learning from human preferences (2017), AI Safety Gridworlds (2017), a suite of environments for testing safety properties of agents, and Scalable agent alignment via reward modeling (2018), which outlines a research direction for the agent alignment problem.91011
AGI frameworks
Legg is a co-author of Levels of AGI (ICML 2024), which proposes levels of performance, generality and autonomy for comparing systems and measuring progress. Legg also co-wrote Google DeepMind's April 2025 post Taking a responsible path to AGI and the June 2026 report From AGI to ASI, which looks at how AI might keep developing after human-level AGI.526
Work
Levels of AGI for Operationalizing Progress on the Path to AGI (external site: deepmind.google)Published research
Co-author of the ICML 2024 paper, which proposes a framework of levels of AGI performance, generality and autonomy for comparing models, assessing risks and measuring progress.5
From AGI to ASI (external site: deepmind.google)Published research
Co-author of the June 2026 Google DeepMind report on routes from human-level AGI to superintelligence.6
Universal Intelligence: A Definition of Machine Intelligence (external site: arxiv.org)Published research
Co-author, with Marcus Hutter, of the 2007 paper that proposes a formal measure of machine intelligence.4
AGI Safety Council (Google DeepMind) (external site: deepmind.google)Proprietary product
Leads the AGI Safety Council, which analyzes AGI risk and best practices and makes recommendations on safety measures, according to Google DeepMind.12
Human-level control through deep reinforcement learning (external site: nature.com)Published research
Co-author of DeepMind's 2015 Nature paper on an agent that learns control policies directly from high-dimensional inputs through deep reinforcement learning.8
Deep reinforcement learning from human preferences (external site: arxiv.org)Published research
Co-author of the 2017 paper that trains reinforcement learning agents from non-expert human preferences between pairs of trajectory segments instead of access to the reward function.9
Career timeline
Jun 2007
Released A Collection of Definitions of Intelligence with Marcus Hutter.7
Dec 2007
Released Universal Intelligence, a formal definition of machine intelligence, with Marcus Hutter.4
2010
Co-founded DeepMind with Demis Hassabis and Mustafa Suleyman.3
Feb 25, 2015
Co-authored DeepMind's Nature paper on human-level control through deep reinforcement learning.8
Jun 2017
Co-authored Deep reinforcement learning from human preferences.9
Nov 2017
Co-authored AI Safety Gridworlds, a suite of environments for testing safety properties of agents.10
Nov 2018
Co-authored Scalable agent alignment via reward modeling, a proposed research direction.11
Jul 2024
Co-authored Levels of AGI for Operationalizing Progress on the Path to AGI, which appeared at ICML 2024.5
Apr 2, 2025
Co-wrote Google DeepMind's post Taking a responsible path to AGI.2
Jun 2026
Co-authored the Google DeepMind report From AGI to ASI.6
Other documented roles
Roles the sources document but that are not confirmed as current.
Related people
More sourced profiles at the same organization, in the same field, or from the same school.
- Abigail SeeAlso at Google DeepMind
- Abhimanyu DasMachine-learning theory
- Anca DraganAlso at Google DeepMind
- Adam GleaveAlso at DeepMind
- Armand JoulinAlso at Google DeepMind
- Ajeya CotraSafety and alignment
- Clément FarabetAlso at Google DeepMind
- Albert GuMachine-learning theory
- David StutzAlso at Google DeepMind
- Aleksandra MojsilovićSafety and alignment
- David WaddenAlso at Google DeepMind
- Alex GravesAlso at Google DeepMind
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