Using data standards to support people at risk 

Posted by: , Posted on: - Categories: Data Standards, Data Strategy, Uncategorized
A graphic representing numerous people profiles across a digital network.

Identifying and supporting people at risk of poor health, social, or economic outcomes is a complex task. It requires coordination across a range of public sector organisations. Better data standards are essential for identifying people at risk of becoming vulnerable and ensuring they receive the right …

Secure by Design: how automation is strengthening data assurance across government

Posted by: and , Posted on: - Categories: Cyber, Data Engineering, Data Ethics, Data insights, Data Standards, Data Strategy
Digital illustration of hyper-fast data processing in a server room, showing a glowing blue and gold double helix of data funneling into a central processing cube, surrounded by holographic screens displaying real-time analytics.

Discover how GDS is using automation and secure design to improve how the government collects and analyses security assurance data.

Governance lessons from the UK-US PETs Pilot for cancer research

Posted by: , , , , and , Posted on: - Categories: Data insights, Data protection, Data Standards, Data Strategy, Guidance
This picture is made up of 9 images in rows of 3. Each row shows a different image of a pill bottle spilling out pills onto a plain surface, on yellow or white backgrounds. On one side, the image is an original photograph. The next two iterations show it getting represented in progressively larger blocks of colour.

The UK-US Privacy Enhancing Technologies (PETs) pilot demonstrates how privacy-by-design can be applied to international data sharing and provides a concrete model for future PETs projects across government. In this blog, we reflect on the governance lessons from the pilot.

Building trust in data and AI: the new Data and AI Ethics Framework and self-assessment tool

Posted by: , and , Posted on: - Categories: Data Ethics
Two people are illustrated in a warm, cartoon style, one on the left and one on the right. The person on the left, who has their back to the viewer, and is typing on a laptop which is sitting on a table. They are white, their hair is shoulder length and dark, and they are wearing a green t-shirt. The computer screen is dark with rows of coloured squares representing programming. The person on the right looks similar but their hair is now tied back in a pony tail, and they are wearing a white lab coat and safety goggles. They are reaching down to lift up an orange hazard label which is about the size of a book. The label is an orange square with a black exclamation mark in the middle. The person looks like they are being careful as they lift it.

The Responsible Data and AI team has launched an updated Data and AI Ethics Framework and self-assessment tool to help public sector teams innovate responsibly.

Strengthening and extending connectivity: what we learned from the API hub alpha

Posted by: and , Posted on: - Categories: agile, API
A person holds out their hand with a glowing graphic above it showing the word ‘API’ surrounded by blue gear icons representing technology concepts such as coding, security, networking and data.

APIs are essential to modern services, but they’re often hard to find or reuse. We're developing a central API hub to make discovery, collaboration and reuse easier across government.

Is it possible to build responsible AI tools in human resources?

Posted by: and , Posted on: - Categories: agile, Data Ethics, People and Skills, Performance Analysis
A graphic representing numerous people profiles across a digital network.

This blog builds on the recent Algorithmic Transparency Recording Standard (ATRS) publication for Succession Select - an innovative AI recruitment tool developed by the Government Digital Service for HR professionals to select Senior Civil Servants. This blog delves into the need for the tool with an emphasis on trust and ethical development.

Making the Algorithmic Transparency Recording Standard (ATRS) mandatory across government

Posted by: , , and , Posted on: - Categories: agile, Beneficial Ownership, Data Engineering, Data Ethics, Data insights, Data Standards, Data Strategy, Performance Analysis, Personal Data Exchange
Bounding boxes are commonly used in AI research to signify where a computer vision algorithm has detected an object in an image. Here the artist has played with this aesthetic: The bounding boxes are 3D-printed frames positioned in the physical environment around objects. Sometimes the objects stick out of their frame.

The use of the Algorithmic Transparency Recording Standard (ATRS) became mandatory for central government in 2024. Read about how the GDS Data and AI ethics team have rolled out the mandate across government and how they have updated the ATRS to reflect learnings from this process.