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Algorithmic accountability for the public sector
Learning from the first wave of policy implementation
New research highlights lessons learnt from first wave of global policy mechanisms to increase algorithmic accountability in the public sector
The first global study analysing the first wave of algorithmic accountability policy for the public sector
Algorithmic accountability for the public sector
Research with AI Now and the Open Government Partnership to learn from the first wave of algorithmic accountability policy.
Algorithmic impact assessment in healthcare
A research partnership with NHS AI Lab exploring the potential for algorithmic impact assessments (AIAs) in an AI imaging case study.
Inspecting algorithms in social media platforms: bridging regulators and independent auditors
CRAFT session at the 2021 ACM Conference on Fairness, Accountability, and Transparency
Regulating for algorithm accountability: global trajectories, proposals and risks
Exploring how we can ensure that algorithmic systems and those deploying them are truly accountable
Accountability for algorithms: a response to the CDEI review into bias in algorithmic decision-making
Reviewing bias is welcome, and stopping the amplification of historic inequalities is essential.
Regulatory inspection of algorithmic systems
Establishing mechanisms and methods for regulatory inspection of algorithmic systems, sometimes known as 'algorithm audit'.
Accountability of algorithmic decision-making systems
Developing foundational tools to enable accountability of public administration algorithmic decision-making systems.
Algorithms in social media: realistic routes to regulatory inspection
Establishing systems, powers and capabilities to scrutinise algorithms and their impact.
Inspecting algorithms in social media platforms
Joint briefing with Reset, giving insights and recommendations towards a practical route forward for regulatory inspection of algorithms
Transparency mechanisms for UK public-sector algorithmic decision-making systems
Existing UK mechanisms for transparency and their relation to the implementation of algorithmic decision-making systems