Executive Briefing: The UK National AI Strategy

Photo: Simon Robinson

Last month the UK Government published its first ever National AI strategy which aims to:

  1. Invest and plan for the long-term needs of the AI ecosystem to continue our leadership as a science and AI superpower;
  2. Support the transition to an AI-enabled economy, capturing the benefits of innovation in the UK, and ensuring AI benefits all sectors and regions;
  3. Ensure the UK gets the national and international governance of AI technologies right to encourage innovation, investment, and protect the public and our fundamental values.

As the strategy states:

“The National AI Strategy builds on the UK’s current strengths and represents the start of a step-change for AI in the UK, recognising that maximising the potential of AI will increase resilience, productivity, growth and innovation across the private and public sectors. Building on our strengths in AI will take a whole-of-society effort that will span the next decade. This is a top-level economic, security, health and wellbeing priority. The UK government sees being competitive in AI as vital to our national ambitions on regional prosperity and for shared global challenges such as net zero, health resilience and environmental sustainability. AI capability is therefore vital for the UK’s international influence as a global science superpower.”

We therefore decided to provide this Deep Tech Network Executive Summary which analyses various aspects which leaders should be aware of in consideration to the impact on their digital strategies.

What is our general reaction to The National AI Strategy?

We are extremely encouraged at the breadth of thinking in the strategy which recognises artificial intelligence as the fastest growing deep technology, and understands the need to accelerate research and innovation to maintain the UK as an AI superpower, while at the same time acknowledging the profound moral questions and transformations that we will experience as a society.

The unimaginable power of AI, driven by quantum computing, will transform society in ways in which we can barely imagine, impacting on every single person. The report needs to be followed up with an initiative to engage our population, light up the imagination of our next generation of entrepreneurs and designers, and be the trigger which ignites a national conversation about how humanity will cohabit our world along with sentient computers.

What are the most encouraging elements of the strategy, and where does it perhaps fall short?

Recognising the UK’s influence as a global science superpower, the report correctly takes a systemic ecosystem perspective. However, the report fails to include one of the UK’s greatest assets which is our incredible cultural creativity and our ability to fuse this creativity with technological innovation. By inviting our most imaginative artists, designers and creative organisations into the ecosystem, the UK will be able to take AI applications to an unimagined realm of innovation. AI can only ever articulate the level of consciousness of its creators, and so we need to include our British creative talent in its conception and development.

What would make Britain a “global AI superpower”? What needs to be achieved?

Current research places the UK third in the world’s list of AI superpowers, we still lag behind China and particularly the US, which dominates in terms of AI research, intellectual resources and digital infrastructure. While the UK still needs to attract a wide range of talent, the government can build on one of our major strengths by deepening its partnerships with British-based AI businesses which lead the world in their ability to embrace the disruptive ideas of deep technology.

What steps are required to reach global AI superpower status?

Economic, business and human drivers all need to be present in the AI ecosystem strategy. So firstly the UK must continue to accelerate its investment in innovation. Secondly, it can build on its major sources of competitive advantage which is its democratic values, trustworthiness and transparency. Since artificial intelligence can only ever manifest the level of ethics and consciousness of its creators, these key qualities must be present for an ecosystem to operate at the highest level of cooperation.

Which countries are leading the way with AI, why, and what can Britain learn from their success?

The two clear leaders in AI are the US and China. Their current dominance in platform-based enterprises means that they are the most prepared for the forthcoming wave of technological disruption because of their ‘platform vision’, i.e., their understanding of the underlying logic and digital architectures of the new digital economy. China especially is demonstrating long-term strategic thinking with considerable investment in countries such as Brazil for example.

What this means is that organisations such as the Department for International Trade should support British business leaders by helping them to stop drowning in data lakes and instead to develop platform vision to ensure that they have the knowledge and capacity to innovate new business models and develop new sources of value for clients, customers and international partners.

Where does Britain currently rank in terms of AI development?

When a variety of factors are taken into account, the UK currently ranks third in relation to AI development. However, the UK government should look at countries such as China, Saudi Arabia and Brazil which are rated by the World Economic Forum as the top three ‘Digital Risers’. These countries are making rapid progress in their AI capabilities by developing ambitious public-private efforts to stimulate digital entrepreneurship in deep technologies. The clear message for the British Government is the need to provide British enterprises with a blueprint to inspire them to take full commercial advantage of the UK’s current leadership in AI research and innovation.

What are the biggest barriers to progressing AI in Britain, and how does The National AI Strategy attempt to solve these challenges?

The AI strategy correctly takes a multi-dimensional approach to the acceleration of growth in AI and other deep technologies, recognising education, governance and research investment as the major barriers to achieving long-term success.

As the AI strategy points out, the UK has the third highest number of AI companies in the world after the US and China. The strategy therefore identifies key stakeholders to partner with in the development of transdisciplinary expert groups to monitor and measure its impact.

We would like to see the UK develop its focus on education much further, nurturing the next generation of AI scientists and entrepreneurs. One of the most promising aspects of the strategy is that it recognises the need for diversity and inclusion in relation to developing a deep talent pool of future game changers to fill the skills gap.

Countries such as Brazil are finding ways to discover and nurture this deep talent – people with high level technology and design skills but who do not necessarily have those traditional educational backgrounds that recruiters normally look for. Without this focus the UK runs the risk of being overtaken by Digital Risers – those countries with extremely ambitious goals to succeed commercially with AI and other deep technologies.

What mindset change is required by leaders to be more collaborative to maximise the potential of AI?

The four primary pillars of deep tech innovation are deep thinking, deep impact, deep talent and deep collaboration. Our leaders therefore need to develop purposeful organisations whose focus is society’s biggest challenges. This will only come about with a more profound form of thinking that understands the relationship between artificial intelligence and humanity systemically and in relation to universal human values. When this is developed, higher levels of collaboration can become possible, not only between participating organisations within an ecosystem, but also between those organisations and the artificial intelligence applications they are creating.

From a technology perspective we need to develop ecosystem-wide capabilities in networked intelligence in order to excel in the next frontier of human knowledge which is the maximisation of purposeful and authentic collaboration between massive-scale networked artificial intelligence and human expertise, cognition and decision-making.

Advances in computational capacity such as Cerebras System’s CS-2 AI accelerator are now making real-world scientific problems solvable. An example is the London-based company DeepMind now being able to improve the prediction of heavy storms. Their “deep generative modelling” was developed by their data researchers in collaboration with meteorologists from the Met Office. British companies will benefit greatly when this type of collaboration extends to open networked ‘computational ontologies’ — vast depositories of domain specific knowledge that is shared and available for our business and scientific communities — thereby making Sir Tim Berners-Lee’s vision of a semantic web a reality.

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