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Voices in the Code: A Story about People, Their Values, and the Algorithm They Made
David G. Robinson in conversation with Professor Shannon Vallor
AI-driven biometry and the infrastructures of everyday life
Normalising the principles of oppression through discriminatory technologies
From principles to practice: what next for algorithmic impact assessments?
We are convening experts from policy, industry, healthcare and AI ethics to discuss our recent case study and the future of AIAs.
Realising the potential of algorithmic accountability mechanisms
Seven design challenges for the successful implementation of algorithmic impact assessments
Algorithmic impact assessment: a case study in healthcare
This report sets out the first-known detailed proposal for the use of an algorithmic impact assessment for data access in a healthcare context
BCS Lovelace lecture: Probabilistic model checking for the data-rich world
BCS Lovelace lecture 2020/21 with Professor Marta Kwiatkowska on probabilistic model checking for the data-rich world
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.
Why the COVID-19 shielded patient list might both compound and address inequalities
Wicked problems in the use of data-driven systems
Accountability of algorithmic decision-making systems
Developing foundational tools to enable accountability of public administration algorithmic decision-making systems.
Inspecting algorithms in social media platforms
Joint briefing with Reset, giving insights and recommendations towards a practical route forward for regulatory inspection of algorithms
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.
Facial recognition technology needs proper regulation – Court of Appeal
The appeal of R (Bridges) v Chief Constable of South Wales shows that, when it comes to facial recognition technology, the status quo cannot continue.