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Introducing the Model for Responsible Innovation

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Last week, the Responsible Tech Adoption Unit (RTA) published our Model for Responsible Innovation, a practical framework for addressing the ethical risks associated with developing and deploying projects that use AI or data-driven technology. The Model sets out a vision …

Data Pipeline Challenges of Privacy-Preserving Federated Learning

Posted by: , and , Posted on: - Categories: Data, Data collection, Data-driven technology, Data-sharing, PETs Blogs

This post is part of a series on privacy-preserving federated learning. The series is a collaboration between the Responsible Technology Adoption Unit (RTA) and the US National Institute of Standards and Technology (NIST). Learn more and read all the posts …

Data protection in a borderless digital landscape

A group of the attendees from the PETs workshop

Privacy Enhancing Technologies (PETs) have become an increasingly important policy priority for governments, multilateral organisations, and the data privacy expert community. PETs refer to a range of digital technologies and techniques that enable the collection, processing, analysis, and sharing of …

Guidance for Local Authorities on Data Analytics in Children’s Social Care 

Posted by: , Posted on: - Categories: Data, Data collection, Data-sharing, Demographic data

Children’s Social Care is one of the most important functions the government carries out. Children who need help and protection deserve high quality and effective support as soon as a need is identified.   Data analytics tools, software that enables categorisation …

How AI assurance can support trustworthy AI in recruitment

A pair of hands is shown in the foreground and a laptop on a desk in the background.

Today, DSIT’s Responsible Technology Adoption Unit (RTA) is pleased to publish our guidance on Responsible AI in recruitment. This guidance aims to help organisations responsibly procure and deploy AI systems for use in recruitment processes. The guidance identifies key considerations …