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Data collection

Data Distribution in 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 …

Privacy-Preserving Federated Learning: Understanding the Costs and Benefits

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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 …

Public attitudes on the fair use of data and algorithms in finance

Posted by: , Posted on: - Categories: Algorithms, Bias, Data collection, Decision-making

Financial companies are increasingly using complex algorithms to make decisions regarding loans or insurance - algorithms that look for patterns in data which are associated with risks of default or high insurance claims. This raises risks of bias and discrimination …