Our mission is to equip governments with an empirical understanding of the safety of advanced AI systems.
The UK Artificial Intelligence Safety Institute and U.S. Artificial Intelligence Safety Institute conducted a joint pre-deployment evaluation of Anthropic’s latest model
How to write part of a safety case showing a system does not have offensive cyber capabilities
We’re open-sourcing dozens of LLM evaluations to advance safety research in the field
The AI Safety Institute reflects on its first year
We are launching a bounty for novel evaluations and agent scaffolds to help assess dangerous capabilities in frontier AI systems.
We look into the evolving role of third-party evaluators in assessing AI safety, and explore how to design robust, impactful testing frameworks.
Calling researchers from academia, industry, and civil society to apply for up to £200,000 of funding.
Our Chief Scientist, Geoffrey Irving, on why he joined the UK AI Safety Institute and why he thinks other technical folk should too
We studied whether people want AI to be more human-like.
A common technique for quickly assessing AI capabilities is prompting models to answer hundreds of questions, then automatically scoring the answers. We share insights from months of using this method.
AISI is bringing together AI companies and researchers for an invite-only conference to accelerate the design and implementation of frontier AI safety frameworks. This post shares the call for submissions that we sent to conference attendees.
AISI funded Epoch AI to explore AI researchers’ differing predictions on the automation of AI research and development and their suggestions for how to evaluate relevant capabilities.
As a complement to our empirical evaluations of frontier AI models, AISI is planning a series of collaborations and research projects sketching safety cases for more advanced models than exist today, focusing on risks from loss of control and autonomy. By a safety case, we mean a structured argument that an AI system is safe within a particular training or deployment context.
We tested leading AI models for cyber, chemical, biological, and agent capabilities and safeguards effectiveness. Our first technical blog post shares a snapshot of our methods and results.
Since February, we released our first technical blog post, published the International Scientific Report on the Safety of Advanced AI, open-sourced our testing platform Inspect, announced our San Francisco office, announced a partnership with the Canadian AI Safety Institute, grew our technical team to >30 researchers and appointed Jade Leung as our Chief Technology Officer.
We are opening an office in San Francisco! This will enable us to hire more top talent, collaborate closely with the US AI Safety Institute and engage even more with the wider AI research community.
This is an up-to-date, evidence-based report on the science of advanced AI safety. It highlights findings about AI progress, risks, and areas of disagreement in the field. The report is chaired by Yoshua Bengio and coordinated by AISI.
We open-sourced our framework for large language model evaluation, which provides facilities for prompt engineering, tool usage, multi-turn dialogue, and model-graded evaluations.
The UK and US AI Safety Institutes signed a landmark agreement to jointly test advanced AI models, share research insights, share model access and enable expert talent transfers.
The UK AI Safety Institute and France’s Inria (The National Institute for Research in Digital Science and Technology) are partnering to advance AI safety research.
This post offers an overview of why we are doing this work, what we are testing for, how we select models, our recent demonstrations and some plans for our future work.
Since October, we have recruited leaders from DeepMind and Oxford, onboarded 23 new researchers, published the principles behind the International Scientific Report on Advanced AI Safety, and began pre-deployment testing of advanced AI systems.
At the first AI Safety Summit at Bletchley Park, world leaders and top companies agreed on the significance of advanced AI risks and the importance of testing.
Since September, we have recruited leaders from OpenAI and Humane Intelligence, tripled the capacity of our research team, announced 6 new research partnerships, and helped establish the UK’s fastest supercomputer.
In our first 11 weeks, we have recruited an advisory board of national security and ML leaders, including Yoshua Bengio, recruited top professors from Cambridge and Oxford and announced 4 research partnerships.
