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AI policy and data governance

Overview

Policy plays a crucial role in influencing where, how and for whose benefit machine learning systems are developed and deployed. Safe and reliable deployment of machine learning systems requires policy frameworks that embed trustworthy data governance; that promote the use of machine learning in areas where it has potential to improve public wellbeing; and that account for the wider implications of technological change on individuals and communities. Research in this theme considers what policy levers can shape the development of AI technologies.

What policy levers can shape the development of AI technologies for societal benefit? ML@CL’s policy projects identify policy interventions that can support the development of trustworthy AI technologies and that help share the benefits of AI across society. Working with partners in civil society, national government, and international organisations, our work considers:

how technological advances in AI can contribute to policy objectives;
the role of data governance and stewardship as a foundation for AI that benefits citizens and society;
what national strategies or policy frameworks are needed to support the development of trustworthy AI technologies and their deployment for societal benefit;
how to deploy data science and AI in the service of national and international policy goals.

Projects

The AI Council

The UK AI Council was an independent committee that provided advice on AI policy and strategy to the UK Government from 2018 – 2023. In 2022-23, the Council convened a series of discussions focused on the policy implications of advances in Large Language Models, with the aim of supporting rapid Government action to build national capability in Foundation Models.

The Centre for Data Ethics and Innovation

The CDEI is a government expert body enabling the trustworthy use of data and AI. Its multidisciplinary team of specialists, with expertise in data and AI policy, public engagement, computational social science and software engineering, are supported by an advisory board of world-leading experts to deliver, test and refine trustworthy approaches to data and AI governance, working with organisations across the UK.

Data Trusts Initiative

Reaping the benefits of data and digital technologies will require robust new institutions or frameworks that can allow data sharing - helping develop new data-enabled products and services - while protecting individual rights and freedoms. Data trusts offer a mechanism to achieve this goal through participatory data stewardship.

Data sharing in Africa: lessons from COVID-19

The COVID-19 pandemic intensified the need for timely and accurate data to inform policymaking. Countries across Africa have developed, and are still developing, innovative uses of data and statistics to monitor the extent of the spread of COVID-19 among their populations. Drawing from real-world examples, this projects the lessons offered by these innovations for future data policy frameworks.

European Network of AI Excellence Centres

European Learning and Intelligence Systems Excellence (ELISE) is a consortium of artificial intelligence (AI) research hubs that connects Europe’s leading researchers in machine learning and AI.

DELVE (Data Evaluation and Learning for Viral Epidemics)

DELVE is a multi-disciplinary group, convened by the Royal Society, to support a data-driven approach to learning from the different approaches countries are taking to managing the pandemic. DELVE operated through 2020, providing advice to the UK Government and SAGE.