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Privacy-Preserving Federated Learning: Understanding the Costs and Benefits

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

Privacy Enhancing Technologies (PETs) could enable organisations to collaboratively use sensitive data in a privacy-preserving manner and, in doing so, create new opportunities to harness the power of data for research and development of trustworthy innovation. However, research DSIT commissioned …

Privacy Attacks in Federated Learning

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

The UK-US Blog Series on Privacy-Preserving Federated Learning: Introduction

This post is the first in a series on privacy-preserving federated learning. The series is a collaboration between CDEI and the US National Institute of Standards and Technology (NIST). Advances in machine learning and AI, fuelled by large-scale data availability …

Championing responsible innovation: reflections from the CDEI Advisory Board

Text on beige background reads reflections from the outgoing CDEI Advisory Board

The Centre for Data Ethics and Innovation leads the Government’s work to enable trustworthy innovation using data and artificial intelligence. At the CDEI, we help organisations across the public and private sectors to innovate, by developing tools to give organisations …

Working with the ICO to encourage the adoption of PETs

Posted by: , Posted on: - Categories: Algorithms, Artificial intelligence, Data, Ethical innovation

Last year, the CDEI launched a responsible data access programme to address the challenges organisations face to access data they need in a responsible way. A key component of this programme is our work to encourage adoption of Privacy-Enhancing Technologies …

Improving responsible access to demographic data to address bias

Posted by: and , Posted on: - Categories: Algorithms, Artificial intelligence, Bias, Data, Demographic data, Intermediaries, Trust

Following our review into bias in algorithmic decision-making, the CDEI has been exploring challenges around access to demographic data for detecting and mitigating bias in AI systems, and considering potential solutions to address these challenges.  Today we are publishing our …

Driving responsible innovation in self-driving vehicles

Self-driving vehicles have the potential to radically transform the UK’s roads. But to enable their benefits and achieve the government’s ambition to ‘make the UK the best place in the world to deploy connected and automated vehicles’, developers and manufacturers …