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Responsible AI research: challenges and opportunities
Exploring the foundational premises for delivering ‘world-leading data protection standards’ that benefit people and achieve societal goals
Redesigning fairness: concepts, contexts and complexities
Exploring the foundational premises for delivering ‘world-leading data protection standards’ that benefit people and achieve societal goals
Accountable AI: a route to effective regulation
Exploring the foundational premises for delivering ‘world-leading data protection standards’ that benefit people and achieve societal goals
Lessons learned from COVID-19: how should data usage during the pandemic shape the future?
Exploring the foundational premises for delivering ‘world-leading data protection standards’ that benefit people and achieve societal goals
Responsible innovation: what does it mean and how can we make it happen?
Exploring the foundational premises for delivering ‘world-leading data protection standards’ that benefit people and achieve societal goals
Ada Lovelace Institute hosts ‘Taking back control of data: scrutinising the UK’s plans to reform the GDPR’
Exploring the foundational premises for delivering ‘world-leading data protection standards’ that benefit people and achieve societal goals
Exploring participatory mechanisms for data stewardship – report launch event
Involving people in the design, development and use of data and AI systems
Participatory data stewardship
A framework for involving people in the use of data
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
Data trusts
Chapter one from Exploring legal mechanisms for data stewardship – a joint publication with the AI Council
Exploring legal mechanisms for data stewardship
The executive summary for a joint publication with the AI Council, which explores three legal mechanisms for responsible data stewardship
Data cooperatives
Chapter two from Exploring legal mechanisms for data stewardship – a joint publication with the AI Council