Three Big Ideas #2
Nuclear innovation, bilingual science, and the impact of the sharing economy
Welcome to our weekly Three Big Ideas roundup, in which we serve up a curated selection of ideas (and our takes on them) in entrepreneurship, innovation, science and technology, handpicked by the team.
⚛️ 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.