Key AI Policy Imperatives

“We can only see a short distance ahead, but we can see plenty there that needs to be done.
This is only a foretaste of what is to come, and only a shadow of what is going to be.”

Alan Turing

Father of Artificial Intelligence – 1949 & 1950

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The United Kingdom is the rightful birthplace of AI, and as such is uniquely positioned to take a leading global role at this formative but critical juncture in AI history. The exponentially increasing rate of adoption of AI in all sectors and across all aspects of life, both in UK and globally, coupled with an accelerated pace of optimisation, means focussed effort and action is required with priority and pace if this is to be achieved. AI has a staggering opportunity to be societally disruptive, and Government must be ready for both the opportunities and the challenges of what is to come. Alignment of wider Government policy, the development of UK-centric, independent AI infrastructure, whole-energy-life-cycle consideration and the adoption of humane approaches to AI design, coupled with forward-thinking globally-connected collaboration and partnerships, are all vital.

To enable this, we consider below three key areas of AI policy in respect of the development of a UK-AI strategy and policy framework.

UK-AI – making the UK a connected global AI leader whilst retaining ‘AI-sovereignty’ and reducing foreign dependence

Infrastructure

Encourage a robust UK-owned infrastructure network, including distributed data-centres and research/investment zones, with ever-reducing reliance on foreign dependency. The stated aim is to significantly reduce artificial foreign investment that inadvertently leads to a foreign capital flight and to positively protect UK job displacement and support true, localised UK economic activity.

People

AI has already created an unprecedented, highly competitive and very liquid global labour market. In addition to the obvious accelerated UK-focused education and up-skilling requirement, prioritised access to this highly competitive global workforce remains vital. Align immigration policy and ensure continuation of fast-track visa access for critical global AI talent as a minimum.

Foundational AI Models

UK-created and owned foundational models should be encouraged. Clear aims are to balance global disparity, mitigate bias and reduce a largely USA-centric dominance presently. UK models should seek to truly reflect UK societal diversity.

Ethical Energy – positively using AI to accelerate Net-Zero and ensure ethical energy application at all life-cycle stages

Global ‘Digital Energy’ Leadership

AI creates an unprecedented opportunity for a unique, global ‘digital energy exchange’. The UK should seek a leading global position, exchanging and balancing energy consumption for AI computational power to balance global energy demand, reduce surge pricing and lessen domestic energy-price fluctuations that might have wider detrimental energy-supply and social consequences.

Holistic Energy

Deeper than encouraging just green-energy usage, a holistic approach to AI-energy expansion should seek to accelerate Net-Zero and set new global benchmarks. This includes encouragement for green AI infrastructure, hardware recycling and responsible decommissioning and, crucially, heat-exchange innovation where surplus heat capture and repurposing is incentivised, reducing overall AI energy-life-cycle waste and inefficiency. UK innovations in heat-exchange and data-centre water-cooling need focus and acceleration.

Smart Grid

AI has a critical role in developing a smart UK energy grid optimised to balance load surges and reduce peak drains, with encouragement for intelligent AI-energy life-cycle usage and planning. Consider innovation in energy-tax policy to reflect the dynamic nature of the market, with global innovations such as ‘energy-surge taxing’ considered to balance power drains and incentivise smart-energy time-balancing. AI can have a very positive impact on peak-grid pricing optimisation and this should be leveraged.

Humane AI – shifting perspectives from reactive protection to proactive kindness and human-centric design

‘Humane’, Not Just ‘Safe’

Encourage a UK AI-industry paradigm shift from ‘safe’ deployments designed merely to mitigate harm, to AI infrastructure and applications that actively promote positivity, kindness and a redoubling of humanity. Think ‘human-first AI’ in all strategy formation and policy consideration.

A Force for Good and Positivity

If applied appropriately, AI presents an unprecedented opportunity to be a positive, disruptive and highly effective tool for local communities and wider society. Proper consideration should be given to non-commercial AI applications, especially those focused on playing a positively disruptive role amongst local communities and wider society, actively bringing and encouraging neighbourhood and social benefits and efficiencies. Government must address ways to leverage AI for the wider good of communities and society, both locally and nationally.

Shared Human Values

Truthfulness

Justice

Trust

Accessibility

Transparency

Accountability

De-centralise Power Concentration, Trust and Responsibility

AI has a propensity for rapid power and control concentration. Actively decentralise AI power, redistributing it to localised ownership and engagement, ensuring against single-entity control and oversight and moving to a distributed power-and-regulatory model. The UK should play a global role in reducing single-source AI concentration. Consultations and AI design should consider broader social, faith and civic inclusivity to encourage decentralisation and inclusivity.

Ethical Clarity

Whilst controlling illegal AI activity will be key and must be strengthened, legislating and enforcing against unethical AI usage will also be vital. Left unchecked, unethical AI could have far-reaching and devastating social consequences. Mitigating legal extortion must be a priority: the power of AI to illicitly and unethically extort via technically legal methods must be controlled and strictly regulated. Public trust in AI is pivotal; policies should actively encourage that trust, for example by clearly identifying where AI technologies or interaction nodes are being deployed.

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