Technology moves faster than the law, but the Good Data Guide will keep you
up to speed.
Making data ethics accessible and achievable for all
What
Our Good Data Guide is a practical toolkit covering all aspects of data ethics. It is ever-evolving and expanding to keep up with technology and the complex challenges facing your organisation.
Why
We all know that data moves faster than the law, that’s why we’ve developed our guide to support you in putting the right foundations and processes in place. Prioritising ethical data practices has never been so important.
Who
To make inclusive decisions, you must have a diverse team. We try to lead by example, collating this guide over two years with support from leading industry brands, expert community voices and our Data Ethics Advisory Board↗.
The gap between developing technology and the law has been used to push the boundaries of acceptable behaviour.
This leaves us all with the responsibility to ensure that we are using data and technology ethically and transparently - with little by way of a blueprint to follow. We hope this guide can help your organisation to respond to that challenge.
A clear and actionable roadmap
Introduction
The context that you need to make good choices as the technology landscape changes. One thing will always remain the same – the need for integrity.
Foundation One - People
Avoid harmful biases and self-reinforcing approaches to data and innovation by promoting diversity & inclusion, data literacy and accountability.
Foundation Two - Beyond Compliance
Our second foundation module seeks to build on the principles and processes introduced under data protection law (GDPR).
Building Block One - Data Management And Information Security
The first of our building blocks focuses on the critical areas of data management and information security.
Building Block Two - The Data Life Cycle
Our second building block focuses on the data lifecycle - introducing the full set of lifecycle stages. Planning is central to setting ourselves up for success.
Building Block Three - Ethical Algorithms and Automation
This third building block brings us to the core of the ethical questions surrounding data analytics and especially machine learning algorithms.
Building Block Four - Algorithmic Transparency and Explainability
Our fourth building block takes a slightly different, discursive, approach to the challenges of transparency and explainability.
Application One - Working with LLMs
The first ‘application’ component of the Good Data Guide aims to support the reader on how best to approach the opportunities and risks of LLM adoption.
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Prioritising safe and considerate data use should be accessible to leaders quickly. Explore our Executive Summary for key actions and impactful takeaways.
The Good Data Guide
The people behind the guide
This ever-evolving guide has been collated by Profusion over two years with support from leading industry brands and expert community voices. Learn more in the foreword.
Need help embedding ethical practices into your organisation?