Why adoption must be balanced with purpose and responsibility
Last week, Prime Minister Keir Starmer announced the UK government’s AI opportunities action plan, marking a substantial gear change in UK public sector positioning on AI technologies, and their role in government and wider society.
We took stock of the announcement and sat down with a few Hippos to get their thoughts on the plan, and discuss some important considerations around AI technologies and how to deliver the government’s ambitions.
The UK’s AI opportunity
Outlining some of the “world-leading foundations” the UK has in place already such as AI research, a vibrant startup and scaleup ecosystem, leading frontier AI companies and leadership on AI safety and governance, the plan describes three core themes to be addressed when realising this vision and strategy.
Foundational investment to enable AI
Firstly, the government’s action plan recognises the importance of foundational investment. Substantial funding for areas such as AI research, talent pool creation through institutions like the Alan Turing institute, and developing state-of-the-art computing infrastructure in the form of the National Data Library (NDL). Simultaneously, it highlights the importance of a regulatory framework that facilitates innovation while ensuring the safe and ethical development of AI technologies.
Widespread AI adoption across the economy
The plan also outlines how the adoption of AI is core to delivering its five missions. Wanting to lead by example, the government plans to implement a “Scan > Pilot > Scale” approach to integrate AI into public services. Alongside this, it plans to incentivise and support the private sector in overcoming barriers to drive growth and productivity.
Positioning the UK as a global AI leader
Finally, the action plan aims to position the UK as a leader and state partner for those building frontier AI platforms. This also involves attracting and retaining AI talent, continuing to nurture a thriving ecosystem of startups, and encouraging the development of world-class AI capabilities within the UK, with a particular focus on science and robotics.
Navigating the plan: Key considerations for the adoption and implementation of AI technologies
The plan is ambitious and will require considerable steps in both organisational and digital transformation across public sector organisations and infrastructure to deliver. In order to ensure that the adoption and implementation of AI truly serves society, several key considerations must be at the heart of the approach:
Responsible and ethical AI
It all starts with responsibility. However exciting the opportunity that AI promises may be, balancing its implementation with the need to deploy things responsibly is key. A responsible AI first approach helps build a foundation where people are at the heart of thinking and where we design systems that respect context, provide validity and reliability, and maintain accountability and transparency.
Just like applying the user-centred principles across digital transformation projects to maximise their potential, we can use this framework to create a balanced approach to AI, addressing five core dependencies: People, Context, Accountable, Valid & Reliable, and Transparent. Hippo’s responsible AI framework outlines these concepts in more detail.
Accessibility and inclusivity
The government’s vision aims to “ensure the whole of society can benefit from the opportunities offered by AI”. For this to be delivered, accessibility and inclusivity considerations must be built in from the outset and not treated as afterthoughts.
This important theme extends across multiple considerations including:
- the design of systems for impaired or disabled people ensuring that they can effectively use and benefit from AI applications;
- ensuring training data for AI systems is diverse and representative of the population the system is intended to serve, without bias or discrimination;
- the promotion of digital equality and working to address digital inclusion issues, ensuring education and training is available to all;
- involving users in the design and development of systems – a user-centred approach will be key to delivering practical and valuable services that have a positive impact on people.
Reiterating this last point, Lead User Researcher at Hippo, Ruth Taylor spoke to us about the critical role of user research in building AI solutions.
Data readiness and governance
If you can ensure that you have high quality, well governed, and structured data from the outset, the design and implementation of an AI solution will generate much stronger results. Conversely, if you start with incomplete, inconsistent or biased data to begin with, the results and outcomes you generate will be reflective of that.
Client Director, Simeon Souttar explains this in practice:
“The first thing that we like to do is take a step back and look at things like data quality, and how the data is being used across the organisation. Often what we find is that the level of maturity in that space is quite low, and we need to help those organisations to build their data quality up. We also look at connecting siloed data together and bringing that into a data platform that gives the organisation visibility across the whole landscape.
We want to help organisations implement AI through a value based approach. It’s about ensuring that the business case is there for the organisation and that the return on investment is understood. It’s important to understand the user’s needs, understand the training needs, understand how you’re going to adapt and change the processes within your organisation to fit those new technologies.”
Liz Whitefield, Co-founder and Director at Hippo highlights the combined importance of purpose and data maturity for organisations:
“It’s about getting the basics right and maximising all of the high quality data within organisations. I think what’s exciting at Hippo is that we don’t just do AI for the sake of it. When we do it, it’s because it’s the right thing and there’s a meaningful path to it. There’s a strong government agenda around AI but a lot of government departments need guidance to reach maturity. It’s important to guide them on that journey and understand what they are trying to achieve.”
AI for public good
For the AI Opportunities Action Plan to gain confidence, trust and ultimately achieve success, it must be underpinned by a purpose that benefits and serves the public. Harnessing AI technologies effectively has the potential to address societal challenges, and improve healthcare, welfare and wider public services, and ultimately enhance the quality of life for citizens.
Implementing the technology does come with its risks, however. If you forego important considerations such as embedding responsible principles and frameworks into AI projects, prioritising accessibility and inclusion, and ensuring your data is mature and well governed, these risks are exacerbated. But, if you prioritise your users, your data, and building the right thing, you can maximise the impact of your outcomes for all.
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