AI Assurance – an introductory guide

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The Department for Science, Innovation and Technology (DSIT) has published an Introduction to AI assurance.
The guidance “aims to provide an accessible introduction to both assurance mechanisms and global technical standards, to help industry and regulators better understand how to build and deploy responsible AI systems. It will be a living, breathing document that we keep updated over time.” Here we pick out the key points to know.
AI governance refers to “a range of mechanisms including laws, regulations, policies, institutions, and norms that can all be used to outline processes for making decisions about AI. The goal of these governance measures is to maximise and reap the benefits of AI technologies while mitigating potential risks and harms.”
AI assurance helps organisations:
AI assurance techniques may focus on the data, model(s), system(s) and broader operational context. Examples include:
Key actions for organisations:
DSIT says the key actions are:
If you have any questions or would otherwise like to discuss any of the issues raised in this article, please contact David Varney, Tom Whittaker, Liz Smith, or another member of our Technology Team. For the latest updates on AI law, regulation, and governance, see our AI blog at: AI: Burges Salmon blog (burges-salmon.com).
Artificial Intelligence (AI) is increasingly impacting how we work, live, and engage with others. AI technologies underpin the digital services we use every day and are helping to make our public services more personalised and effective, from improving health services to supporting teachers; and driving scientific breakthroughs so we can tackle climate change and cure disease. However, to fully grasp its potential benefits, AI must be developed and deployed in a safe, responsible way - Viscount Camrose , Minister for Artificial Intelligence and Intellectual Property
https://www.gov.uk/government/publications/introduction-to-ai-assurance