The AI Fairy, the Unicorn Kingdom, and the need for real talk

Tl;dr: Alex recently attended the Tony Blair Institute for Global Change’s Future of Britain conference, where everyone agreed that AI would be at the heart of a future government’s reforming agenda. Here, we outline how the UK political discussion is failing to engage with these ideas and is instead stuck in a fairytale world where radical reform will come at little cost or effort. Until we have a more mature political conversation about investment and procurement, the “Unicorn Kingdom” is set to remain a fantasyland.

Introduction

Duncan Robinson, The Economist’s Bagehot columnist, recently identified the ‘Reform Fairy’ as the new spirit fluttering over British politics. Robinson described it as the “fundamentally unserious” belief that it is possible to “improve public services without spending political or financial capital”. The Reform Fairy’s closely-related cousin is the ‘AI Fairy’: the mythical creature that will apply the latest breakthroughs in cutting-edge research to decades-old public services through an as-yet undefined process.

AI policy across the political spectrum has been focused on either inputs or the hypothetical regulation of outputs. This means we have long lists of small government spending commitments for a range of startups, labs, and technologies and calls to license large language models like nuclear technology from the opposition. When it comes to identifying priorities, procuring technology, and overhauling existing practices, beyond variations of “embracing the opportunities presented by AI”, the picture becomes murky.

Opening the recent Future of Britain conference, former UK Prime Minister Tony Blair provided a stark outline of how the British state was operating on an unsustainable footing. He was followed by a range of speakers covering topics from health to geopolitics, who outlined the role technology could play in addressing today’s challenges. At Air Street, we believe that AI-first companies will be at the forefront of delivering that change and have the potential to remake the public sector in the same way that they are already rewiring the private sector.

We’ve seen helpful interventions around how to make this promise more tangible from the Tony Blair Institute, Onward and other organisations that we have supported and championed in the ecosystem. Nevertheless, the public and political conversation is still far from where we need it to be if we are to get technology out of the labs and into the hands of those on the frontline. In short, we risk squandering a generational opportunity.

AI isn’t an upgrade, we need to replace an operating system that’s broken at its core

Science and technology leadership requires us to overhaul the 19th century institutions that 21st century founders have to navigate. We can see this really clearly in two areas of policy.

The application of AI will one-day significantly reduce costs across the public sector - whether that’s replacing failing tank programmes with cheap drones or a preventative approach to healthcare that reduces the number of seriously and expensively ill patients. It is, however, unserious to believe that these benefits can be realised overnight.

To take the example of healthcare, we used to hear the EY valuation of NHS data at £9.6 billion bandied around UK policy circles as proof of the NHS’s world-beating longitudinal datasets. This headline figure didn’t account for the significant amount of cleaning work required to make this data remotely usable for AI workloads. The majority of primary care (GP) practices in the UK still use paper records and 100 million of them are still largely sitting in old-fashioned medical libraries in the middle of hospitals. Past attempts at a national integrated electronic health records system have ended in disaster. Anecdotally, we hear from AI researchers working on research with the NHS that the first months of any project are consumed by data permissioning, acquisition, evaluation and cleaning work.

Meanwhile, day-to-day provision is little better. When DeepMind first started working with the NHS in 2015, they quickly pivoted away from their initial plan to focus on AI research. Why? The urgency of remedying a situation of staff relying on antiquated shared computers, pagers, and fax machines to communicate with each other was far greater than advanced diagnostic AI. We still see regular news stories of staff being found sharing patient data over WhatsApp, due to the inadequacy of approved communications systems.

In the defence world, as we see the Ukrainians wreak havoc with 3D-printed bombs and home-made drones, the UK struggles on with institutional structures and procurement processes from a different century. The delays and failures of the General Dynamics Ajax programme are well-known, but more concerning is the culture that allowed it to happen. Over 172 pages, the government’s independent review of the programme details institutional warfare across the Ministry of Defence’s various science and tech bodies, a lack of accountability, and how concerns from those on the ground were (sometimes willfully) ignored. Beyond Ajax, the MoD’s most recent Command Paper, in common with many government technology strategies, is sharp in its analysis of the importance of AI, but blurrier on actual action, rarely straying beyond repeated expressions of the need to partner more with industry.

None of these environments in their current form sound like they are ripe for smooth digital transformation.

Reform and not instead of investment

In her book recounting her work chairing the UK’s Vaccine Taskforce (VTF), Kate Bingham writes with barely concealed exasperation about having to construct a 100-page business case for the Treasury, outlining the cost-benefit ratio of discovering a Covid vaccine. She similarly faced repeated, time-consuming requests for information from the National Audit Office. In the end, she concluded that: “If I had ever been asked the question ‘What is the biggest threat to the success of the VTF?’ the honest answer would have been ‘Large parts of the rest of Whitehall’.”

This combination of overbearing process and penny-pinching has precedent in the UK, even in the context of national crisis. The UK lost valuable time in its efforts to develop the jet engine in the run up to World War II, due to reluctance by the Ministry of Air to devote even minimal funding to the project. Similarly, Tommy Flowers, the inventor of Colossus, the groundbreaking programmable computer that decrypted German messages, largely had to self-fund his work. Even after the war, the government failed to compensate him fully for the initial materials he bought.

We risk seeing exactly the same process play out in the AI race - only this time, we’re facing better-funded and equally or more-skilled competition across national boundaries.

Unfortunately, the scale of investment needed here is significantly greater than the sums required for the development of the jet engine. This funding is needed both at an individual department level (for example, reversing the collapse in NHS tech investment), but also on major national priorities.

As we’ve argued previously, moves to rectify the UK’s inadequate next-generation infrastructure like the National Compute Strategy are promising first steps, but the resource commitments don’t match the scale and urgency of the task. A national compute cluster of 3,000 GPUs in several years time will set us behind where most corporate labs are today. While the government operates on borrowing rules that don’t distinguish between investment and day-to-day spending, this seems unlikely to change at a time of national stringency.

Even if we do successfully end up developing some of these capabilities, we have to then avoid the trap of governing them through the same failed processes. For example, if the UK one day does build out sovereign compute capability that researchers or promising start-ups could tap into, we can’t govern accessing rights using the same Treasury criteria Kate Bingham fought against. We would need to operate it with the philosophy of the new San Francisco Compute Group, with its single form application, even if this would inevitably mean some capacity being used by unsuccessful projects. This would mean a radical shift in mindset.

The owners of stagecoaches aren’t going to build the railways

Proper investment, however, is only one piece of the puzzle. There’s no point increasing investment only to throw good money after bad, with the same coalition of incumbents, outsourcing companies, and legacy IT suppliers.

If the Prime Minister is serious in his aspiration to build the ‘Unicorn Kingdom’, we need to become significantly more energetic about bringing challengers into government. A 2015 analysis of feedback from SMEs trying to sell to the UK Government listed a number of killers: overly prescriptive requirements, poorly written specifications, cost and time, bureaucracy, and the perceived unfairness of the process as their most common challenges. This tallies with similar research from the Startup Coalition, which laid bare how businesses increasingly didn’t want to work with the government, or how when they did, they couldn’t find a way in.

At the moment, if you run a health startup, there is no central portal through which you can sell to the NHS. Instead you have to hope an individual hospital trust is prepared to take a chance on you. If they are, then they’ll also need to have the right infrastructure, and be willing to work through hurdles of bureaucracy required to make a partnership possible, all while trying to deliver a standard of care amid record waiting lists.

Oliver Lewis, co-founder of Rebellion Defence, described the MoD as “one of the worst customers in the world”, warning that: “It takes Herculean patience, specialist knowledge and expertise, trusted networks back into the system and, critically for tech start-ups, significant patient capital. Typically, that is a level of venture funding that is available only in the United States, even if British and European investors are close followers.” The US Department of Defense has already started exploring specific measures to help startups navigate what they term “the valley of death”. This new attitude is beginning to bear fruit, but we have not seen the same energy in the UK. This needs to change.

Failure to reform procurement means attempting to reform the state with our hands tied behind our backs. As Camilla de Coverly Veale at the Startup Coalition has pointed out, challengers provide a way to move away from bloated, ‘bespoke’ solutions. To this, we’d add that earlier-stage AI businesses have to stay at the cutting-edge of the field if they’re to stay alive, move much more quickly, and embrace community norms like interoperability (as opposed to the vendor lock-in strategies of incumbents).

Realism requires courage, courage requires trade-offs

It’s both easy and incredibly lazy to blame everything on ‘the blob’, ‘bureaucrats’, or non-specific Whitehall forces. There’s definitely more that could be done to bring in relevant expertise and a raft of individual process reforms that others have laid out in more detail. Reform’s latest report details plenty of official “eye-rolling” in response to transformation efforts from the centre. However, the fiscal fantasies of the Reform and AI Fairies, as well as the procurement horror show have another shared root.

This is a cultural aversion towards risk that comes as much from politicians as it does from officialdom. If a procurement team feels like it will be punished by its superiors and hung out to dry by their minister in the press, they will of course always opt to add in that one extra check. Similarly, the longer politicians insist on maintaining the fantasy tax-and-spend debate Duncan Robinson alluded to, the longer it will take to reach an honest account of what we need to do to enable the next generation of public services. It’s simply not good enough for elected politicians to act as if they don’t run the country and these forces are beyond their control.

These conversations would only mark the beginning of the cultural shift we’ll need to enable AI-first transformation. As the intense public reactions to attempts to rationalise GP records and health data, or past attempts to involve the private sector in service delivery, have shown, we have plenty of future difficult conversations to come. Vehicles like ARIA will be able to shield the most critical research from short-term political impulses, but there are some fights that future governments will need to be prepared to have in public. As Nathan has said before, “there’s no world where we can build high-quality, technology-first public services that don’t require any money, data, or private sector involvement”.

At Air Street, we often talk about how these discussions aren’t luxury debates about future technology - there’s a wider, urgent point about national security. In a 2008 essay about the hidden costs of additional checks, Y Combinator co-founder Paul Graham warned that: “Checks instituted by governments can cripple a country's whole economy. Up till about 1400, China was richer and more technologically advanced than Europe. One reason Europe pulled ahead was that the Chinese government restricted long trading voyages. So it was left to the Europeans to explore and eventually to dominate the rest of the world, including China.” We have a chance to stop history repeating itself in reverse - let’s not waste it.