Stuart Russell

Stuart J. Russell (born 1962) is a British computer scientist, professor of computer science at the University of California, Berkeley, co-author with Peter Norvig of the textbook Artificial Intelligence: A Modern Approach, and founder of Berkeley's Center for Human-Compatible Artificial Intelligence. He is a leading proponent of a research programme on provably beneficial AI.

Russell's textbook defined the "rational agent" framing used in many university AI courses, and his later work and book Human Compatible argue that the standard model of AI, in which machines optimise a fixed objective supplied by humans, becomes risky as systems become more capable. His position is one of the better-known formulations of the alignment problem (see [SAFE-ALIGN-001]).

Russell was born in Portsmouth, England. He received a first-class BA in physics from Wadham College, Oxford (1982), and a PhD in computer science from Stanford University (1986; thesis dated 1987), supervised by Michael Genesereth (Wikipedia contributors, 2026l). He has been a professor at the University of California, Berkeley, and was an adjunct professor of neurological surgery at the University of California, San Francisco, from 2008 to 2011 (Wikipedia contributors, 2026l). His research has covered machine learning, probabilistic reasoning, planning, computer vision and inverse reinforcement learning (Wikipedia contributors, 2026l). In 2016 he founded the Center for Human-Compatible AI (CHAI) at Berkeley (Wikipedia contributors, 2026l). He gave the BBC Reith Lectures in 2021 (Wikipedia contributors, 2026l).

Textbook. With Peter Norvig, Russell wrote Artificial Intelligence: A Modern Approach (Russell & Norvig, 2020, 4th ed.), reported as used at over 1,500 universities in 135 countries (Wikipedia contributors, 2026l; this usage figure is a secondary-source claim and is dated to the source's access). The book organises AI around agents that act to maximise expected performance.

Research priorities. Russell, Dewey and Tegmark (2015) set out research priorities for robust and beneficial AI, associated with the Future of Life Institute's open letter on the subject (Wikipedia contributors, 2026l).

Provably beneficial AI. In Human Compatible (Russell, 2019), Russell argues for building systems that (i) have the objective of realising human preferences, (ii) are initially uncertain about what those preferences are, and (iii) learn about them from human behaviour. The proposal draws on inverse reinforcement learning and assistance games. The three principles as summarised in a secondary source are that the machine's only objective is to maximise the realisation of human preferences, that it is initially uncertain about those preferences, and that the ultimate source of information about them is human behaviour (Wikipedia contributors, n.d.); the book text itself was not consulted. Whether this framework can be implemented for capable general systems is an open research question (Hypothetical).

Russell collaborated with Norvig on the textbook and with Daniel Dewey and Max Tegmark on the 2015 priorities paper. His programme belongs to the technical-alignment school, in contrast with approaches that concentrate on empirical evaluation or governance (see [SAFE-ALIGN-001], [SAFE-XRISK-001]). He has also advocated for restrictions on lethal autonomous weapons and has signed open letters warning of AI risks, including, as reported by the secondary source, the Future of Life Institute letter of 22 March 2023 calling for a pause of at least six months in training AI systems more powerful than GPT-4 (Future of Life Institute, 2023) and the Statement on Superintelligence, which calls for a prohibition on developing superintelligence until there is broad scientific consensus that it can be done safely and controllably and strong public buy-in (Future of Life Institute, n.d.; Wikipedia contributors, 2026l). The signatory lists were not retrieved, so the signings rest on the secondary source. In a January 2025 Newsweek article he described the race to AGI as "a race towards the edge of a cliff" (as quoted by Wikipedia contributors, 2026l, which dates the article to 31 January 2025).

Reported honours include the IJCAI Computers and Thought Award (1995), the IJCAI Award for Research Excellence (2022), appointment as OBE (2021), fellowship of AAAI, ACM and AAAS, and, per the secondary source, election as a Fellow of the Royal Society and to the National Academy of Engineering in 2025 (Wikipedia contributors, 2026l). Further reported honours include the ACM Karl V. Karlstrom Outstanding Educator Award (2005) and Wadham College honorary fellowship (Wikipedia contributors, 2026l). These honours and years, including the 2025 Royal Society and National Academy of Engineering elections, rest on the secondary source only. CHAI is a research centre at Berkeley addressing the design of beneficial AI systems.

Critics of the human-compatible programme question whether human preferences can be defined, inferred and aggregated well enough to serve as an objective, and whether assistance-game formalisms scale to realistic systems. Others dispute the premise that advanced AI poses a large-scale risk (Contested; see [SAFE-XRISK-001]). Russell's views on risk are one position among several, and the encyclopedia treats the underlying empirical claims about future systems as Hypothetical or Forecasts, not established facts.

Russell and Norvig's textbook is a standard teaching reference (Well Supported by adoption reports). The provably-beneficial-AI agenda remains an active but unproven research area; deployed alignment practice relies largely on other techniques (see [TECH-ALIGN-001]).

No forecasts are made in this biography.

• Foundational Concepts:
  • FOUND-001 Artificial Intelligence: The rational-agent framing.
  • SAFE-ALIGN-001 The AI Alignment Problem: His main research subject.
• Related Methods & Technologies:
  • TECH-ALIGN-001 Pretraining, Fine-Tuning and RLHF: Applied alignment techniques.
  • SAFE-XRISK-001 Existential Risk: The risk debate.
• Advanced Implications & Future Trajectories:
  • ASI-001 Artificial Superintelligence: The concern motivating his programme.
  • BIO-BOSTROM-001 Nick Bostrom: Contemporary writing on superintelligence risk.