Regulate to innovate
A route to regulation that reflects the ambition of the UK AI Strategy
The Ryder Review
Independent legal review of the governance of biometric data in England and Wales
A knotted pipeline
Data-driven systems and inequalities in health and social care
Exploring legal mechanisms for data stewardship
A joint publication with the AI Council, which explores three legal mechanisms that could help facilitate responsible data stewardship
Participatory data stewardship
A framework for involving people in the use of data
AI assurance?
Assessing and mitigating risks across the AI lifecycle
Technical methods for regulatory inspection of algorithmic systems
A survey of auditing methods for use in regulatory inspections of online harms in social media platforms
Code & conduct
How to create third-party auditing regimes for AI systems
Regulating AI in the UK
Strengthening the UK's proposals for the benefit of people and society
Who cares what the public think?
UK public attitudes to regulating data and data-driven technologies
Should more public trust in data-driven systems be the goal?
To better understand the limits of public trust in data-driven systems, we must acknowledge the role structural inequalities play in shaping trust
Can algorithms ever make the grade?
The failure of the A-level algorithm highlights the need for a more transparent, accountable and inclusive process in the deployment of algorithms.