Unlocking the UK's AI Potential: A Political Landscape Analysis

As AI evolves, the UK's major parties chart their AI policy paths. Discover their strategies, the missing pieces, and the road to global AI leadership.

Unlocking the UK's AI Potential: A Political Landscape Analysis

Artificial Intelligence (AI) has grown exponentially in the last year—from the development of large language models (LLMS) and virtual classroom assistants to self-driving cars. The potential of AI is growing by the day, with the promised capacity to transform industries, improve healthcare, and drive economic growth. However, this transformative power also brings various ethical, legal, and practical challenges. The global surge in AI has generated optimism and anxiety among politicians. Earlier this year at London Tech Week, UK Prime Minister Rishi Sunak announced his ambition to make the UK a “leader in AI”. 

Yet, if the UK wishes to lead within the AI sphere, it will need a well-structured and comprehensive AI policy to navigate this landscape effectively. 

Current Policy Positions of Major Parties

52487174f79ea5c629ac5055aeb389e6baf72188.jpgPrime Minister Rishi Sunak by UK Prime Minister is licensed under CC BY 2.0

Conservative Party: Innovating within Existing Frameworks

The Conservative Party's approach to AI policy centres around a contextual and sector-based regulatory framework, aiming to promote AI development within the existing regulatory systems. At its recent party conference, it made references to the upcoming events and frameworks. This approach considers the nuances of different sectors to ensure that AI technologies are effectively integrated. The Party's strategy is founded on implementing five key AI principles that guide the development and deployment of AI systems.

Sunak has been promoting the UK's AI capacity for a long time and sees the sector as a significant source of economic growth. As such, the Conservative Party strongly emphasises building upon existing regulations, notably the Data Protection and Digital Information Bill, which covers various aspects of information processing, privacy, and data oversight, including establishing the Information Commission. By integrating AI policies within broader legal and regulatory frameworks, the Party aims to strike a balance between fostering innovation and safeguarding the rights and privacy of individuals.

Foundation Model Taskforce and AI Safety Summit

The UK government has taken significant steps in shaping AI policy, including establishing the Frontier AI Taskforce and hosting the AI Safety Summit

  1. Foundation Model Taskforce: The Foundation Model Taskforce is a government-led effort focused on developing foundational AI models. These models form the core of AI systems and serve as building blocks for various applications. By investing in foundational models, the Conservative Party has said it wishes to foster innovation and drive AI advancements.
  2. AI Safety Summit: The AI Safety Summit is a key event that underscores the Conservative Party's recognition of the global importance of AI safety. This summit brings together experts, policymakers, and industry leaders to discuss and develop strategies for ensuring AI technologies' safety and ethical use. It serves as a platform for collaboration and knowledge sharing to address AI's challenges and opportunities.

Furthermore, the Conservative Party's Innovation First Plan is another crucial component of its AI policy. This plan reflects the Party's commitment to positioning the UK as a global AI innovation and development leader. It encompasses a multifaceted strategy that includes regulatory approaches, research investment, and fostering an ecosystem conducive to AI growth.

Labour Party: How do we get the next 12 to 18 months right?

c90b5b64a32817486157c1c21ef3cee589937c64.jpgKeir Starmer, MP for Holborn and St Pancras; Shadow Secretary of State for Exiting the European Union" by Chatham House, London is licensed under CC BY 2.0

The Labour Party didn’t make any particular promises at its recent party conference but advocates for a broader scope in the national AI policy overall. One key element seems to be a significant focus on enhancing mathematics education (which the Conservative party are also doing). This initiative appears to aim to bolster the foundational skills necessary for individuals to adapt to the evolving AI-driven job landscape. By 2030, it’s predicted that two-thirds of the UK workforce could be lacking in basic digital skills, even though 75% of jobs will require advanced digital skills in the same time frame.

The Labour Party is reportedly exploring new legislation to counter AI-generated disinformation following a 'deepfake' incident involving party leader Keir Starmer, whereby a synthetic media voice recording of the leader spread on Monday, 9th October 2023, a day before Starmer’s keynote speech. As such, Labour is also said to be contemplating the possibility of an AI bill post-election, which might involve strengthening regulatory bodies to address technological advancements.

Additionally, the Labour Party emphasises the need for accessible and affordable reskilling programs, intending to ensure that workers in industries impacted by AI have the opportunity to gain new skills. Starmer stated, "We must make retraining and upskilling readily available to workers who may be displaced by AI, providing them the chance to adapt to new job roles."

Previously at London Tech Week, Starmer’s stance was, “I think rather than sit and try to identify each and every job that might be affected, and there’s going to be many, I think it’s a sense of: what’s the infrastructure, the framework that a government needs to set up? And are we ready for the speed of this?
“Because I think there’s still a bit of a feeling that AI may affect us in five years, or six or seven years. This is more likely to be in the next 12 months to 18 months.”

This Labour proposal addresses the concerns raised by the Ada Lovelace Institute about the capability aspect of AI regulation. By prioritising education and reskilling, it seeks to enhance the workforce's adaptability and competence in the face of AI-driven transformations.

Missing Elements

While the UK's major parties are aligning on certain fundamental principles of AI policy, some crucial elements warrant further focus:

Investment

The UK lags behind global leaders in AI investment. For instance, ChatGPT's (just one of the major LLM’s) monthly computing cost is estimated at USD$40 million (£33 million). The government's initial £100 million (USD$121 million) allocation for AI development falls short of such demands. The UK’s budget for technology is modest compared to China and the US. According to Stanford’s AI Index Report 2021, China accounted for nearly one-fifth of global private investment funding in 2021, attracting $17 billion for AI start-ups alone. 

In the last two years, these figures have witnessed a substantial increase. The US has since taken the global lead in AI private investment, with $47.4 billion invested in 2022, approximately 3.5 times more than the closest contender, China, which received $13.4 billion. Additionally, the US maintains its top position in terms of the total count of newly funded AI enterprises, surpassing the European Union (EU) and the UK by 1.9 times. How can the UK aim to be the global leader in AI with such abysmal budgets? 

Computing Power

The UK lacks major clusters of Graphics Processing Units (GPUs) essential for AI data processing, which could hinder AI research and development. This comes during a global semiconductor chip shortage, which powers advanced technology. As it stands, the UK has been backing a £900 million supercomputer devoted to AI research in Bristol, but it is not expected to be online until 2026.

International Collaboration

Effective solutions to global AI challenges necessitate collaboration with international partners. Currently, the UK appears to be striving to outperform others rather than pursuing a more cooperative strategy akin to the EU’s approach. Embracing collaboration could address concerns related to workforce digital proficiency, accessibility, semiconductor chips and raw material shortages, regulatory frameworks, and ethical deliberations. Meanwhile, if successful, it would have the potential to enhance AI inclusivity, aligning it with the broader society it serves rather than a select few within the tech community.

Three further areas for consideration: 

  1. Skills Development: Investments in education and training are essential to bridge the skills gap and prepare the workforce for AI adoption.
  2. Public Trust: A concrete legal and ethical AI regulation is paramount. The UK's current approach, based on vague and voluntary principles, should evolve to ensure public trust and confidence.
  3. Inclusivity: Efforts are needed to ensure AI benefits reach underserved areas and address the digital divide.

Overall, the evolving landscape of AI policy in the UK is promising. Major political parties are striving towards crafting a comprehensive framework, but they must also recognise the missing elements. For the UK to ascend as a worldwide AI leader, it's crucial to cultivate a skilled workforce, amplify inclusivity, engage in international collaboration, and uphold stringent ethical standards. These strategic measures will guarantee that AI is a catalyst for positive change, driving societal and economic progress while preserving public trust and safeguarding individual rights.

Header Image Credit: "Artificial Intelligence & AI & Machine Learning" by mikemacmarketing is licensed under CC BY 2.0.

Author

Elle Farrell-Kingsley

Elle Farrell-Kingsley Contributor

Elle is a passionate advocate for youth policy, AI ethics, and interdisciplinary approaches. Recognised for reporting and researching emerging technologies and their impact, Elle has earned accolades such as the 100 Brilliant Women in AI Ethics™ 2024, the TechWomen100 Award, and the Lord Blunkett Award at the University of Law. Her achievements have led to a funded place on the Sustainable Finance programme at the Smith School of Enterprise and the Environment University of Oxford, a Lord Blunkett scholarship covering her Legal Technology, AI and Cyberlaw studies, and a prestigious John Schofield Fellowship with a mentor from BBC World News, enhancing her skills in broadcast media. Her work spans impactful journalism, content curation for AI search engines, and advocating for informed policies in the UK Parliament.

With a humanities and social sciences background, she offers a unique perspective that encourages readers to explore the intersection of arts, technology, policy, and society.

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