Delivering responsible data through the National Data Strategy
Examining how the commitment to responsible data in the UK's National Data Strategy could be realised and what it misses.
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Health datafication, digital phenotyping and the ‘Internet of Health’
A new report from the Ada Lovelace Institute explores the datafication of health, how it manifests and the consequences for people and society.
The Ada Lovelace Institute is an independent research institute and deliberative body, funded by the Nuffield Foundation
Our core belief is that the benefits of data and AI must be justly and equitably distributed, and must enhance individual and social wellbeing.
From the Ada blog
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.
Practising data stewardship in India, early questions
How could data stewardship help to rebalance power towards individuals and communities?
Can digital immunity certificates be introduced in a non-discriminatory way?
New forms of technology are coming. How do we ensure they’re deployed in a way that conforms to equality regulation?
Data, Compute, Labour
The monopolisation of AI is not just – or even primarily – a data issue.
How to work with us
Developing a positive vision for a world in which data and AI work for people and society is an immense task, and not one we can achieve alone.
To achieve that change, we need to catalyse conversations around the ‘should’ questions, to engage and influence people from across industry, government, civil society and communities.
Read more
Upcoming and recent events
Regulating for algorithm accountability: global trajectories, proposals and risks
Exploring how we can ensure that algorithmic systems and those deploying them are truly accountable.
Almost Future AI
An online salon exploring AI ethics and near-future fiction.
What forms of mandatory reporting can help achieve public-sector algorithmic accountability?
A look at transparency mechanisms that should be in place to enable us to scrutinise and challenge algorithmic decision-making systems.