21 Sep 2023
by Sundeep Bhandari

Supercharging the UK’s effective use of data and AI

Guest blog from Sundeep Bhandari, Head of Digital Innovation at National Physical Laboratory (NPL). Part of techUK's #SuperchargeUKTech Week 2023.

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The UK’s journey into strengthening its approach to the development and use of AI started in early 2020 when the government published draft guidance on an AI auditing framework which was quickly followed up by guidance for how to explain decisions made by AI. Towards the end of the year there was guidance on AI and data protection which kickstarted the National Data Strategy.

Throughout 2021 and 2022, we received the Algorithmic Transparency Standard, the Centre for Data, Ethics and Innovation’s Effective AI Assurance Roadmap and the National AI action plan, against a backdrop of the Integrated Review and the Integrate Review refresh. These are just a few examples of the policies and strategies which propose standards as a way to foster innovation and regulate AI, and we are not alone in this global race to capitalise on the benefits of emerging technologies.

As a result, standards and commonly agreed technical specifications will play an increasingly significant role for advancing the governance and adoption of AI in the coming years as the range of applications of AI continues to increase. They set out best practices to ensure that AI-related products, processes and services perform as intended and can help unlock the economic potential of AI by increasing consistency and interoperability of AI technologies. 

To ensure that industry, regulators, civil society and academic researchers have the tools and knowledge to contribute to the development of such standards and make informed use of published standards to advance trustworthy and responsible AI, the AI Standards Hub was established.

The hub is an initiative, led by the Alan Turing Institute in partnership with the British Standards Institution (BSI) and the National Physical Laboratory (NPL) and supported by the Department for Science, Innovation and Technology (DSIT) and the Office for AI, which is addressing the challenges faced by stakeholders in navigating the evolving landscape of AI standardisation and aims to increase the country’s contribution to the development of international standards for AI.

Almost all of the ‘game-changing’ products, solutions and services – across various sectors and society – that will help us address major global challenges such as climate change, public health and energy resilience will rely on confidence in data and its employment in advanced, AI-driven digital technologies. 

Standards, and in NPL’s case the technical measurement standards that emanate from the metrology, the science of measurement, that we do, are however in their infancy.  To unlock and extract the maximum value from data and AI we need to have confidence.  Confidence in the quality of the data and confidence in how trustworthy, robust, safe or risky the outputs of AI tools, technologies and systems are. Traditionally, organisations such as NPL, have focused on quantification and quantitative inputs and outputs and providing confidence levels which are essential to determine a technology’s trustworthiness.  But we need to consider that the application of AI is very context specific.  What matters to me right now, may not matter to you, or, what matters to me now might not matter in 5 minutes – so if my application is either business or safety critical, how do I have confidence in such a system?

As the world transforms around us, we need to transform with it, and indeed stay ahead of it. Whilst physical infrastructure technologies have been in place for over 100 years, in this world increasingly driven by data at the speed of AI, the same cannot be said of the assets required to establish a digital measurement infrastructure, especially one that is both dynamic and complex. There is a very live discussion at the moment in regard to what quantitative AND qualitative metrics are needed to assure AI and enable the measurement when being assessed for conformity to standards – if you have an interest do please get involved.

AI Standards Hub - The New Home of the AI Standards Community

National Physical Laboratory - NPL - impact from science - NPL

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Authors

Sundeep Bhandari

Sundeep Bhandari

Head of Digital Innovation, National Physical Laboratory