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Algorithmic decision-making and predictive analytics in children’s social care
A one-day event to discuss the use of data analytics for delivering services within the remits of children’s social care.
New research evidences accountability, transparency and public participation for trusted use of NHS data
Benefits to patients include things like improving disease detection or developing new medicines and treatments.
What is or isn’t OK when it comes to biometrics?
Reflections from round one of the Citizens' Biometric Council.
Beginning ‘JUST AI’ – bravery and creativity for ethics in practice
Dr Alison Powell, Director of the newly established JUST AI network, on the need for bravery and creativity for ethics in practice.
New humanities-led network will put social justice at the heart of AI research
JUST AI, a network of researchers and practitioners led by Dr Alison Powell from LSE launches today.
Regulation of biometrics debated
To mark the beginning of an independent review on the governance of biometric data, Ada hosted a debate on UK biometrics regulation
Ada Lovelace Institute announces independent review of the governance of biometric data
The Ada Lovelace Institute commissions Matthew Ryder QC to lead an independent review of the governance of biometric data.
Changing the data governance ecosystem – through narratives, practices and regulations
Today the Ada Lovelace Institute launches Rethinking Data.
Health data partnerships: Amazon/Department of Health and Social Care – Ada’s view
The use of NHS health data to develop new technologies raises important questions for people and society.
How will data and AI work for people and society after the UK General Election 2019?
We've taken a look at the five largest political parties’ manifesto commitments relating to data, AI, innovation, law enforcement and human rights.
Four new board members appointed to Ada Lovelace Institute
The Nuffield Foundation has appointed four new members to the board of the Ada Lovelace Institute.
Facial recognition: defining terms to clarify challenges
Facial recognition technology is a complex area, which means the risk of misunderstandings is high.