Policy plays a crucial role in influencing where, how and for whose benefit machine learning systems are developed and deployed. By synthesising evidence for use in policy development and engaging with policymakers, ML@CL contributes to the development of policy frameworks for AI that enable safe and effective use of machine learning. Recent examples of this work are provided below.
ELISE (2021) Creating a European AI Powerhouse: A Strategic Research Agenda from the European Learning and Intelligent Systems Excellence (ELISE) consortium
Prepared by the ELISE consortium for the European Commission, this Strategic Research Agenda sets out areas in which further technology development can help create trustworthy AI systems. ML@CL synthesised expert input from consortium members to create this Agenda.
Global Partnership on AI (2020 – present)
As members of the Working Group on Data Governance, ML@CL provides expert input to scope GPAI’s work programmes.
AI Council (2019 – present)
This Council advises the UK Government’s Office for AI on the policies required to support the development of the UK’s AI industry. ML@CL provides expert input to this advisory body.
Ada Lovelace Institute and AI Council (2021) Exploring legal mechanisms for data stewardship
This review published by the Ada Lovelace Institute considers how different legal frameworks can contribute to responsible data use. Under the auspices of the Data Trusts Initiative, ML@CL contributed a chapter on the issues associated with data trusts, and provided critical feedback to shape the analysis and manuscript.
DELVE (2020) Data Evaluation and Learning for Viral Epidemics
Responding to policy needs during the first wave of the COVID-19 pandemic, DELVE convened leading data scientists, public health researchers and policy experts to provide data science-informed policy advice. Reports from the Initiative covered topics including: the use of face masks; the design of test, trace isolate programmes; control of hospital and health care acquisition of COVID-19; impact of school closures; and data readiness in emergencies. ML@CL convened research teams, contributed to drafting of papers, and coordinated policy engagement.
Royal Society (2020) Digital technology and the planet
This policy study convened by the Royal Society considers the action required to deploy digital technologies in the service of policy ambitions to tackle climate change. ML@CL provided expert input and contributed to drafting of papers.