Three Big Ideas #02

⚛️ Philip Salter, Founder

Energy is the cornerstone of progress. A strong correlation exists between per capita energy consumption and economic output, but this growth has historically come at the cost of increased carbon emissions. Small Wonders, which we released this week, argues that Small Modular Reactors (SMRs) should be part of the solution. These reactors, with a capacity of 300 MW or less, are modular by design — manufactured off-site and assembled on location.

Artificial intelligence will demand vast amounts of energy. The International Energy Agency forecasts that by 2026, electricity consumption will exceed 1,000 TWh. Just this week it was announced that Oracle is scoping out using three small nuclear reactors to power a new 1 GW AI data centre. That’s why our report advocates for the co-location of data centres with SMRs, aligning with two of the new Government’s core missions: stimulating economic growth and positioning Britain as a clean energy leader.

Looking back, the true marvel of nuclear power isn’t its potential but the decades-long delay in realising that potential. In 1956, the UK made history at Calder Hall in Cumbria by launching the world’s first full-scale nuclear power station to supply electricity to a civilian grid. As the report highlights, 18 additional nuclear power stations followed, but the most recent one – Sizewell B in Suffolk – was connected to the grid nearly 30 years ago in 1995. Since then, eight Prime Ministers have come and gone, while South Korea has brought 18 new nuclear stations online.

The report also recommends that the UK recognise nuclear regulatory approvals from allied nations. Similar precedents exist in other sectors, such as pharmaceuticals between Australia and Switzerland, food and drug regulation between Canada and the European Union, and automotive standards between the EU and the US. This can even be done unilaterally – as seen in Singapore’s recognition of pharmaceuticals from the US, EU, and UK – and wouldn’t cost the government a penny. Something for the Chancellor to keep in mind with the Budget just around the corner.

👩‍🔬 Anastasia Bektimirova, Researcher

Last week, I got a spot for a fireside chat between Matt Clifford (Entrepreneur First co-founder and ARIA Chair) and Tom Kalil (Renaissance Philanthropy CEO and former Deputy Director for Policy at the White House Office for Science and Technology under Presidents Clinton and Obama), organised by UKDayOne and TxP. 

The dialogue ranged from institutional innovation and research funding to industrial strategy and technological diffusion. But if I were to highlight just one point, it would be Tom’s answer about a skill gap between the UK and the US: 

“Many US universities are really significantly increasing the number of courses in AI, machine learning and data science. And not only people who would just focus on that, but people who are genuinely bilingual, that is, they have both deep domain expertise and this sort of computational skills as well. And it would be important for UK universities to benchmark how they are doing in this area vis-à-vis world-class peers.”

In a field like engineering biology, for example, this means that having the best biologists alone won’t cut it – we also need more people who know how to combine biology with engineering expertise (and there is evidence that the UK struggles here). Having already secured an early edge – built on a scientific pedigree and exciting companies spanning from new materials to novel foods – we can’t afford to let it slip.

Bilingualism is likely to develop fairly naturally in many disciplines, where there is a strong computational precedent. Computing principles have already been part of biological workflows for decades. Chip design is also a computational playground. In the social sciences, a shift into advanced computational methods has made economists valuable hires for tech companies. But this won’t be the case for many other fields. Especially with AI tools lowering the skill barrier, there is no excuse for not being more intentional in preventing gaps from forming. 

So, what could a game plan for a comprehensive computational shift involve? One part of it is a curriculum catch-up. This means degree programmes, starting from the undergraduate level, with training in applied computational methods and writing software for research, done in a way that is tailored to each field.

At a more advanced level, there is room for translational postdoc programmes, which, as Tom noted, some US universities are experimenting with. This, essentially, means that a PhD graduate enters a programme specifically designed to help them bring research from the lab to the marketplace. By extension, this could create a ripple effect back through the academic pipeline – for example, PhD programmes developed with this postdoc route in mind too.

Another part of it is physical social infrastructure: more cross-disciplinary research centres, institutes, and other spaces, such as co-working hubs envisioned as part of the EU’s AI Factories, which will allow startups, scientists and students “to meet and work on common ideas and projects,” creating “an environment that can attract the necessary talented human capital and build vibrant, attractive, and dynamic communities of practice.” The beauty of such spaces lies in their ability to blur traditional boundaries between the fields, with computational thinking as a common language.

💼 Eamonn Ives, Research Director

As well as providing us with cheaper takeaways and convenient rides home, one of the other key benefits that the sharing economy has given rise to is an extra way for people to earn a living. A new paper from Tucker Omberg from Jacksonville University, which analyses the impact of ridesharing on the labour market, caught my eye this week. His headline finding is that “Uber’s arrival to a city resulted in [a] decline in the unemployment rate by between a fifth and a half of a percentage point.” The good news doesn’t stop there either – Omberg also finds evidence that Uber has a positive effect on wages at the lower end of the wage distribution, which he suggests may be due to changes in how workers search for jobs or shifts in bargaining power.

Omberg’s research is one more datapoint proving the importance of the sharing economy, and the tangible consequences it has for consumers and workers alike. It gives us further reason to ensure that the rules that govern it – from worker’s rights to matters of taxation – are fit for purpose. And with the Labour Party about to descend on Liverpool for their annual conference, chatter about the future direction of travel on these issues is gearing up.

Prior to the election, Labour published their ‘Plan to Make Work Pay’. Among many other things, it contained a promise to end the three-tier system for employment status, which classifies people as either employees, self-employed or ‘workers.’ Removing the worker definition, however, could pose significant challenges – as platforms would then likely be on the hook for offering things like statutory sick pay or redundancy rights, while workers using them would be subject to National Insurance Contributions on their earnings. Indeed, according to the Financial Times (paywall), there are fears even from worker unions themselves that an unintended consequence of Labour’s plan could be businesses simply hiring staff as contractors or casual workers.

As was previously noted in research by the APPG for Entrepreneurship, the sharing economy is a unique segment of the overall economy and one deserving of bespoke policy attention. Though the Labour high command promised to table an Employment Bill within their first 100 days in office, it’s critical that enough time is taken to work out the specifics. Even the best intentioned legislation can end up causing trouble if it’s rushed through.

Three Big Ideas #01

🚗 Eamonn Ives, Research Director

Everything’s bigger in America, so the saying goes, and that certainly applies to their cars. An obvious problem with all that extra weight, as a recent article in The Economist explains, is that while supersized vehicles are safer for those inside them, they can pose lethal consequences for anyone else who isn’t. After analysing ten year’s worth of US crash data, they conclude that for every life saved by the heaviest 1% of SUVs and trucks, there are more than a dozen lost in other vehicles. 

People don’t buy bulky cars to deliberately jeopardise their fellow motorists though. Bigger models are roomier and thus more pleasant to sit in. Part of the extra weight that modern cars have gained is due to modcons like climate control, electric windows and sunroofs. An inconvenient truth about electric vehicles is that they can often be heavier than their gasoline-powered equivalents because of their hefty battery packs. So calls to simply ‘mandate lightness’ would come at a cost to consumer welfare and possibly delay progress towards environmental objectives. 

Fortunately, a technological solution is (safely) hurtling down the road – autonomous vehicles (AVs). Driverless cars promise to eliminate the vast majority of crashes – after all, just 2% of collisions in the UK are due to vehicle defects. The computers that control them don’t get aggressive, tired or drunk – but they are able to talk to each other remotely and have much faster reaction times than humans ever could. An enormous productivity boost could ensue if AVs enable more efficient transportation of both goods and workers. (Say goodbye to the commute as you know it.)  

Earlier this year, the Autonomous Vehicles Act received Royal Assent, which means AVs could be driving on Britain’s roads by 2026. At the end of last month, British AV-startup Wayve announced a partnership with Uber, in which they will integrate their AI into vehicles using the ride-hailing firm’s platform. 

Good news like this should encourage us that a safer, more prosperous future is possible – but let’s not take it for granted. Writing for the Greater London Project, Shakeel Hashim does a great job of sketching out some of the Cheems (for the uninitiated, read this) reasons why AVs might find themselves stuck at a metaphorical red light in Britain. He argues that, despite the AV Act being passed in May, there are still legislative hoops to be jumped through before we can expect driverless cars to be whisking us around. Given the gains that stand to be made, the responsible civil servants must have their feet firmly on the accelerator.

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🎨 Anastasia Bektimirova, Researcher

Sci-fi author Ted Chiang penned an essay for The New Yorker arguing that “AI isn’t going to make art”, really ever. He writes that “art is something that results from making a lot of choices” and that AI “is a fundamentally dehumanizing technology because it treats us as less than what we are: creators and apprehenders of meaning.” In response, the commentary on social media got so loud it bordered the HR territory for some.

Unlike the caricature that Chiang’s piece sketches, the reality of AI art is more nuanced than typing a prompt into a machine. Like cameras or brushes, AI tools are instruments shaped and put to use by humans to assist in the creative process. It still requires artistic direction and iteration–that is, a lot of choices–and the initial output is rarely the final product. Such works can take days, weeks or longer to refine. The creative core remains human: people shape the message and use AI to express their vision. We don’t think of photos taken with digital cameras, where computer interfaces unlock hundreds of sophisticated and increasingly automated manipulations, as lesser creations than film photos. The medium isn’t the message here, and its choice is neither a yardstick for a work’s artistic merit nor a boundary of what it means to be creative. So is the case with AI – it is simply an evolution of the artist’s toolkit.

AI introduces a new dimension to creativity. And this dimension is an innovative space for human-machine collaboration and hybrid work. Refik Anadol, whose AI-generated art was on display at London’s Serpentine North Gallery this February, described AI as “a thinking brush that doesn’t forget, that can remember anything and everything,” and said he would “invite that AI to my studio, and host and cocreate” with it. Over at the Sydney Opera House, AI-generated choreography instructions keep dancers on their toes, creating a unique performance each night. From Pollock's drip paintings and Arp’s gravity-led collages to Cage's chance operations, there is something about chance that has long fascinated artists, and AI offers a new way to embrace it.

Beyond the “what counts as art” debate lie hard policy questions. No one is under the illusion that permission from every single artist whose work feeds into an AI tool lands in developers’ inboxes. Policymakers will have to grapple with what to do about this. Judging by recent copyright infringement court cases, this won’t be an easy fix. AI-assisted output is usually sufficiently transformed, but using this as a basis for policy is unlikely to satisfy many. One way forward might be infrastructure for detecting content ownership and providing compensation. But this is likely to be hard to implement in practice, especially at scale. As O’Reilly founder and CEO puts it, we need “a virtuous circle of ongoing value creation, an ecosystem in which everyone benefits.” There is a possibility that, when the dust settles, norms might end up shifting. On aesthetic grounds, there is still a long way to go before most AI art is worthy of the name. But the excitement of a new medium in its early days is an opportunity space to be leveraged not binned.

For the road, I’m leaving you with this piece by Vera Molnár, who is considered to have paved the way for generative art. Back in the 1960s, she was one of the first artists to produce computer-assisted drawings.

Vera Molnár, (Dés)ordres ((Dis)orders), 1973. Plotter drawing, ink on paper. Photo: Galerie Oniris, Rennes. Courtesy of Vera Molnár/Galerie Oniris

🌎 Philip Salter, Founder

Our latest report,  Job Creators 2024, reveals that 39% of Britain’s fastest-growing companies have at least one foreign-born founder, with ​​32% of all founders across these companies coming from overseas. Given the UK’s immigrant population is less than half of this, we can confidently conclude – and we do – that immigrant founders are a critical component of Britain’s flourishing entrepreneurial ecosystem.

Debates around immigration can become emotional. But facts matter, and they really don’t care about your feelings. That so many of the UK’s most innovative companies are started by immigrants reveals that we are reliant on them for innovation, jobs and economic growth. It also suggests a path to more growth, if we can attract and retain more immigrants like them. The report has eight policy recommendations aimed to target them.

You can measure immigrant entrepreneurship in all sorts of ways. Before our work, the most common approach was to look at the percentage of those born outside the UK who are registered as directors of companies. The claim here was that the higher percentage proves immigrants are more entrepreneurial.

However, Governments understandably care about jobs and productivity and this measure doesn’t account for the economic impact of these businesses. Also, some of this could be ‘necessity entrepreneurship’, which might include immigrants who are excluded from employment due to discrimination. This certainly wouldn’t be something to celebrate.

The methodology we used was inspired by another report in which SyndicateRoom partnered with Beauhurst to track the 100 startups that have seen the greatest growth in valuation. In other words, a list of companies which private markets have taken the biggest bet on. Critically, unlike many lists of top companies that are put together with additional motives, e.g. PR,business development, it passed the smell test, including the likes of Darktrace, Deliveroo and Monzo.

Statistics can have a memetic quality – Rishi Sunak regularly quoted our finding that in 2019 that half of fastest-growing companies had an immigrant founder. That’s now dropped to 39%. Luckily, we know how to get it back up where it belongs and what that would mean for economic growth.