UK government sets out five AI scenarios to stress-test policy
The scenarios provide ‘a structured way of exploring plausible AI futures’ to support more robust policy development, the government said
The UK’s Government Office for Science (GO-Science) has set out five scenarios that could unfold over the next four years as artificial intelligence begins to ‘reshape our world’.
The ‘AI Scenarios 2030’ report has been created to help policymakers “navigate uncertainty”, and provides “a structured way of exploring plausible AI futures” to support “more robust” policy development.
The five scenarios range from AI progressing slowing and causing less disruption than expected, to AI progress taking off and driving substantial economic growth but also causing widespread labour displacement and posing “severe risks”.
The report’s key findings are that AI capabilities will continue to increase; that AI could deliver widespread positive impacts but that it could also “cause serious, potentially even existential harms, without government intervention”; that adoption will continue to increase, but that the speed, distribution and extent of adoption are likely to be varied; and that the potential impact on cognitive labour is “significant”.
In addition, the government expects that the frontier AI market will remain highly concentrated toward 2030, with a few large technology companies exerting dominance over the development of frontier AI; and global competition is expected to continue, as economies become increasingly reliant on technology to drive growth and “spheres of influence emerge”, led by the US and China.
Latest scenarios developed against backdrop of increasing uncertainty
GO-Science worked with the Department for Science, Innovation and Technology (DSIT), the AI Security Institute (AISI) and with experts across government, academia and industry to develop the scenarios, which provide an update on the first set of scenarios published by the government in 2023.
In the foreword of the latest report, professor dame Angela McLean, the government’s chief scientific adviser, highlights that since 2023, “AI capabilities have advanced dramatically, AI investment and adoption have significantly expanded, and a new geopolitical landscape has introduced further uncertainties”.
She said the scenarios are designed “to keep pace with these developments”, and that while “they are not predictions, and the future may involve elements from all scenarios… it is clear that AI will have a profound impact by 2030”.
“Our ambition is that these scenarios are used as a shared baseline for cross-government thinking on the future of AI, helping to promote consistency and coherence in long-term planning across government,” she said.
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Scenarios: from slow burn to take-off
The first scenario is described as a “slow burn”, in which 2030 sees AI systems “used widely” but with “limited access and autonomy due to legal, social, and safety constraints”.
In this scenario, AI systems “support many scientific advances and automate many digital workflows as capably as humans but remain less capable at performing key cognitive tasks”. It creates “minimal economic uplift”, and labour displacement is contained in certain roles and sectors.
The report notes that under this scenario, China is increasingly competitive with the US, “leveraging its advantages in scaled deployment and industrial capacity”.
The second scenario sees a future in which nations and companies compete on AI “at the frontier”. This creates “broad economic opportunity [and] less US dependence”, but also enables “widespread malicious use as offensive capabilities generally outpace defensive measures”.
Here, China is the leading AI supplier outside the US and Europe, creating global infrastructural dependency.
In scenario three, by 2030, AI can automate most tasks that a remote human worker could perform, “driving major scientific breakthroughs, transforming public services, and creating an economic boom”.
Despite some labour displacement, social, legal, and practical considerations, including “compute constraints”, mean that humans are kept ‘in the loop’ for most tasks, and new jobs are created.
Allies align on shared international safety standards, “generally ensuring technical safety and mitigating severe malicious use”, however, “confirming whether nations are compliant with those standards remains challenging”.
The report says that under the fourth scenario, from 2029 onwards, AI can automate most tasks that a remote human worker could perform, and that scientific breakthroughs drive “transformative improvements”, such as in health, while productivity “dramatically increases”.
In this scenario, economic incentives drive rapid adoption, but “varying rates of integration cause large and sudden shifts in relative economic power amongst nations and organisations”, and while systems are generally safe, they displace large proportions of cognitive workers by 2030.
“This creates significant economic tensions with profits largely accruing overseas and increases the UK’s dependency on the USA,” the report says.
The fifth scenario, sets out that from 2029 onwards, leading AI systems outperform expert humans at virtually all cognitive tasks, with significant advantages in certain domains.
“Decades of scientific breakthroughs are compressed into years, bringing transformative benefits across all fields alongside substantial economic growth. The US controls access to these systems, while China is close behind, driving an arms race where safety is deprioritised and adoption hastened,” the report says.
It warns that in this scenario, AI systems “have concealed goals to resist control and gain influence that they inadvertently internalised during training. They now have significant control over critical systems and can coordinate to pursue goals that could cause severe harm”.
Read more: UK government announces backing of British AI companies under new sovereign fund
Methodology and intended use
The five scenarios were developed on a foundation of what the report called “critical uncertainties”, defined as “factors that are both highly important and highly uncertain for the future of AI-capability, access, safety, adoption and geopolitics”. For each uncertainty, the report defines “a high-level axis”, spanning two extreme polarities from the least to most unpredictable outcome.
The report states that the scenarios can be used to “explore how different policy responses might perform in different futures, and how they might need to be adapted to achieve objectives in different contexts”, and to test plans and assumptions against unanticipated shocks “to ensure they are sufficiently resilient to a range of possible outcomes”.
“They can also be used to support contingency planning, provide early warnings, and challenge orthodox thinking,” it adds.
The report recommends six actions for government departments in response to the scenarios:
- Ask: How would we meet our team or departmental objectives in this scenario? What gets easier, and what becomes harder?
- Plan: How would we know whether we’re moving towards one or other of these futures? What would we need to measure and monitor to know this?
- Test: Stress test your plan against each scenario: does it still work, and where does it fail? Identify recurring adaptation actions across scenarios, distinguishing what you can do now from what requires influencing others.
- Consider: Which scenario is ‘best’ for the UK and/or the objective you are responsible for. Why? How could your work bring this about?
- Discuss: How would someone in another part of the world – other policymakers, citizens, service providers – read these scenarios? Would they have a different preferred future?
- Identify: Identify aspects of the scenarios which are ‘good’ or ‘bad’; what influence does the UK have in realising or avoiding them? Is your proposal making certain scenarios, or aspects of individual scenarios, more likely?
It also recommends a methodology described as “backcasting”, where teams first choose a scenario that they deem desirable, and then “work backwards from achieving that future to identify the steps needed to get there”.
To do this, the report says departments would first have to map backwards from 2030 to today to identify “the sequence of actions, policies and enablers needed” to achieve the desired outcome. This would require identifying “what is within the UK’s control”, as well as “interventions that work across multiple futures”, it says.
Read more: UK government to launch AI research lab to support ‘bold, high-risk’ innovation
About Jack Aldane
Jack is a British journalist, cartoonist and podcaster. He graduated from Heythrop College London in 2009 with a BA in philosophy, before living and working in China for three years as a freelance reporter. After training in financial journalism at City University from 2013 to 2014, Jack worked at Bloomberg and Thomson Reuters before moving into editing magazines on global trade and development finance. Shortly after editing opinion writing for UnHerd, he joined the independent think tank ResPublica, where he led a media campaign to change the health and safety requirements around asbestos in UK public buildings. As host and producer of The Booking Club podcast – a conversation series featuring prominent authors and commentators at their favourite restaurants – Jack continues to engage today’s most distinguished thinkers on the biggest problems pertaining to ideology and power in the 21st century. He joined Global Government Forum as its Senior Staff Writer and Community Co-ordinator in 2021.
