Safe and Cooperative AI

Lead Research Organisation: University of Oxford


Brief description of the context of the research including potential impact
Further research into techniques for analysis and guarantees of alignment and cooperativeness
in advanced AI systems. Methods for scalable interpretability and oversight of learning systems.
This is in the context of other attempts to develop alignment and oversight techniques, as well
as the cooperative AI agenda, and potential impacts include improved safety guarantees,
better-informed decisions about training and deployment, and greater foundational
understanding of large-scale learning systems.
Aims and Objectives
- Scalable oversight of advanced AI technologies: increase ability of operators to delegate
complex tasks to AI systems and achieve desired, well-understood outcomes.
- Analysis and guarantees of alignment: empower informed decisions about training and
deployment of advanced AI systems, mitigating risk of unintended outcomes.
- Analysis and guarantees of cooperativeness: avoid negative externalities, undesirable
network effects, and conflict resulting from deployment of AI systems.
Novelty of the research methodology
We have already developed a novel analytical framework for multi-principal-multi-agent
delegation in Delegation Games (Sourbut et al forthcoming). Research methodology is expected
to comprise a mixture of theoretical analysis, algorithmic innovation, and computational
experiments (simulations, learning algorithms).
Alignment to EPSRC's strategies and research areas (which EPSRC research area the
project relates to)
Artificial Intelligence Technologies, Building a Secure and Resilient World, Theoretical Computer
Science, Verification and Correctness
Any companies or collaborators involved
Cooperative AI Foundation (CAIF) (probable)

Planned Impact

AIMS's impact will be felt across domains of acute need within the UK. We expect AIMS to benefit: UK economic performance, through start-up creation; existing UK firms, both through research and addressing skills needs; UK health, by contributing to cancer research, and quality of life, through the delivery of autonomous vehicles; UK public understanding of and policy related to the transformational societal change engendered by autonomous systems.

Autonomous systems are acknowledged by essentially all stakeholders as important to the future UK economy. PwC claim that there is a £232 billion opportunity offered by AI to the UK economy by 2030 (10% of GDP). AIMS has an excellent track record of leadership in spinout creation, and will continue to foster the commercial projects of its students, through the provision of training in IP, licensing and entrepreneurship. With the help of Oxford Science Innovation (investment fund) and Oxford University Innovation (technology transfer office), student projects will be evaluated for commercial potential.

AIMS will also concretely contribute to UK economic competitiveness by meeting the UK's needs for experts in autonomous systems. To meet this need, AIMS will train cohorts with advanced skills that span the breadth of AI, machine learning, robotics, verification and sensor systems. The relevance of the training to the needs of industry will be ensured by the industrial partnerships at the heart of AIMS. These partnerships will also ensure that AIMS will produce research that directly targets UK industrial needs. Our partners span a wide range of UK sectors, including energy, transport, infrastructure, factory automation, finance, health, space and other extreme environments.

The autonomous systems that AIMS will enable also offer the prospect of epochal change in the UK's quality of life and health. As put by former Digital Secretary Matt Hancock, "whether it's improving travel, making banking easier or helping people live longer, AI is already revolutionising our economy and our society." AIMS will help to realise this potential through its delivery of trained experts and targeted research. In particular, two of the four Grand Challenge missions in the UK Industrial Strategy highlight the positive societal impact underpinned by autonomous systems. The "Artificial Intelligence and data" challenge has as its mission to "Use data, Artificial Intelligence and innovation to transform the prevention, early diagnosis and treatment of chronic diseases by 2030". To this mission, AIMS will contribute the outputs of its research pillar on cancer research. The "Future of mobility" challenge highlights the importance the autonomous vehicles will have in making transport "safer, cleaner and better connected." To this challenge, AIMS offers the world-leading research of its robotic systems research pillar.

AIMS will further promote the positive realisation of autonomous technologies through direct influence on policy. The world-leading academics amongst AIMS's supervisory pool are well-connected to policy formation e.g. Prof Osborne serving as a Commissioner on the Independent Commission on the Future of Work. Further, Dr Dan Mawson, Head of the Economy Unit; Economy and Strategic Analysis Team at BEIS will serve as an advisor to AIMS, ensuring bidirectional influence between policy objectives and AIMS research and training.

Broad understanding of autonomous systems is crucial in making a society robust to the transformations they will engender. AIMS will foster such understanding through its provision of opportunities for AIMS students to directly engage with the public. Given the broad societal importance of getting autonomous systems right, AIMS will deliver core training on the ethical, governance, economic and societal implications of autonomous systems.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S024050/1 30/09/2019 30/03/2028
2722156 Studentship EP/S024050/1 30/09/2022 29/09/2026 Oliver Sourbut