Science policy – Soft Machines

Research and Innovation in a Labour government

Above all, growth. The new government knows that none of its ambitions will be achievable without a recovery from the last decade and a half’s economic stagnation. Everything will be judged by the contribution it can make to that goal, and research and innovation will be no exception.

The immediate shadow that lies over UK public sector research and innovation is the university funding crisis. The UK’s public R&D system is dependent on universities to an extent that’s unusual by international standards, and university research depends on a substantial cross-subsidy, largely from overseas student fees, which amounted to £4.9 bn in 2020. The crisis in HE is on Sue Gray’s list of unexploded bombs for the new government to deal with.

But it’s vital for HE to be perceived, not just as a problem to be fixed, but as central to the need to get the economy growing again. This is the first of the new Government’s missions, as described in the Manifesto: “Kickstart economic growth to secure the highest sustained growth in the G7 – with good jobs and productivity growth in every part of the country making everyone, not just a few, better off.”

To understand how the government intends to go about this, we need to go back to the Mais Lecture, given this March by the new Chancellor of the Exchequer. As I discussed in an earlier post, the questions Reeves poses in her Mais Lecture are the following: “how Britain can pay its way in the world; of our productive capacity; of how to drive innovation and diffusion throughout our economy; of the regional distribution of work and opportunity; of how to mobilise investment, develop skills and tackle inefficiencies to modernise a sclerotic economy; and of energy security”.

Reeves calls her approach to answering these questions “securonomics”; this owes much to what the US economist Dani Rodrik calls “productivism”. At the centre of this will be an industrial strategy, with both a sector focus and a regional focus.

The sector focus is familiar, supporting areas of UK comparative advantage: “our approach will back what makes Britain great: our excellent research institutions, professional services, advanced manufacturing, and creative industries”.

The regional aspect aims to develop clusters and seeking to unlock the potential agglomeration benefits in our underperforming big cities, and connects to a wider agenda of further English regional devolution, building on the Mayoral Combined Authority model.

There is “a new statutory requirement for Local Growth Plans that cover towns and cities across the country. Local leaders will work with major employers, universities, colleges, and industry bodies to produce long-term plans that identify growth sectors and put in place the programmes and infrastructure they need to thrive. These will align with our national industrial strategy.”

Universities need to at the heart of this. The pressure will be on them, not just to produce more spin-outs and work with industry, but also to support the diffusion of innovation across their regional economies. There are no promises of extra money for science – instead, as in other areas, the implicit suggestion seems to be that policy stability itself will yield better value:

“Labour will scrap short funding cycles for key R&D institutions in favour of ten-year budgets that allow meaningful partnerships with industry to keep the UK at the forefront of global innovation. We will work with universities to support spinouts; and work with industry to ensure start-ups have the access to finance they need to grow. We will also simplify the procurement process to support innovation and reduce micromanagement with a mission-driven approach.”

Beyond the government’s growth imperative, its priorities are defined by its other four missions; in clean energy, tackling crime, widening opportunities for people, and rebuilding the healthcare system. Research and Innovation, and the HE sector more widely, need to play a central role in at least three of these missions.

A commitment to cheap, zero carbon electricity by 2030 is a very stretching target, despite some advantages: “our long coast-line, high winds, shallow waters, universities, and skilled offshore workforce combined with our extensive technological and engineering capabilities.” Here the “strategy” part of industrial strategy is going to be vital – getting the balance right between the technologies that the UK will develop itself and those it imports from international balance will be vital. The call is to double onshore wind, triple solar, and quadruple offshore wind. There is a commitment to new nuclear build, including small modular reactors, and recognition of the importance of upgrading the grid and improving home insulation. R&D will need to be focused to support renewables, new nuclear and grid upgrades.

In health, commitments to address health inequalities imply higher priority on prevention, with high hopes placed on data and AI: “the revolution taking place in data and life sciences has the potential to transform our nation’s healthcare. The Covid-19 pandemic showed how a strong mission-driven industrial strategy, involving government partnering with industry and academia, could turn the tide on a pandemic. This is the approach we will take in government.” This statement gains more significance following the appointment of Sir Patrick Vallance as Science Minister, as I’ll discuss below.

There’s long been a tension between the high hopes that a succession of UK governments have placed on a strong life sciences sector, and a perception that the NHS is an organisation that’s not particularly innovative. So it’s unsurprising to read that “as part of Labour’s life sciences plan, we will develop an NHS innovation and adoption strategy in England. This will include a plan for procurement, giving a clearer route to get products into the NHS coupled with reformed incentive structures to drive innovation and faster regulatory approval for new technology and medicines.” I am sure this is correct in principle, and many such opportunities exist, but it will be difficult to take this forward until the immediate funding crisis faced by most parts of the NHS is overcome.

The new government’s fourth mission is to “break down barriers to opportunity”. A big part of this is to reform post-16 education (in England, one should add, as education is a devolved responsibility in Wales, Scotland and Northern Ireland). Universities will need to get used to there being more focus on the neglected FE sector, from which specialised “Technical Excellence Colleges” will be created, and should ready themselves for a more collaborative relationship with their neighbouring FE colleges: “to better integrate further and higher education, and ensure high-quality teaching, Labour’s post-16 skills strategy will set out the role for different providers, and how students can move between institutions, as well as strengthening regulation.”

There’s one important priority that wasn’t in the original list of five missions, but can’t now be ignored: the threatening geopolitical situation inevitably means a renewed focus on defence. The new government is explicit about the role of the defence industrial base in this:

“Strengthening Britain’s security requires a long-term partnership with our domestic defence industry. Labour will bring forward a defence industrial strategy aligning our security and economic priorities. We will ensure a strong defence sector and resilient supply chains, including steel, across the whole of the UK. We will establish long-term partnerships between business and government, promote innovation, and improve resilience.”

As the MoD budget grows, defence R&D will grow in importance. It’s perhaps not widely enough appreciated how much, following the end of the Cold War, the major focus of the UK’s research effort switched from defence to health and life sciences, so this will represent a partial turn-around of a decades-long trend.

How is the new government actually going to achieve these ambitious goals? Much stock is being placed on “mission led government”, in which Whitehall departments effortlessly collaborate to deliver goals which cross the boundaries between departments. In its first day, the new government made one unexpected announcement, which I think offers a clue as to how serious it is about this. That was the appointment of Sir Patrick Vallance as Science Minister.

Vallance, of course, has an outstanding background to be a Science Minister, as a highly successful researcher who then led R&D at one of the UK’s few world-class innovation led multinationals, GlaxoSmithKline. But, in the context of the new government’s ambitions, I think his most significant achievement, as Government Chief Scientific Advisor in the covid pandemic, was to set-up the Vaccine Task Force. If that’s going to be a model for how “mission led government” might work, we might see some exciting and rapid developments.

Research and innovation has a huge part to play in addressing the pressing challenges that face the new government, which necessarily cross Whitehall fiefdoms. The ambition in setting up the Department of Science, Innovation and Technology was to have a department coordinating science and innovation across the whole of government; it’s difficult to imagine anyone better qualified to realise this ambition than Vallance.

Quotations from the 2024 Labour Manifesto.

How much can artificial intelligence and machine learning accelerate polymer science?

I’ve been at the annual High Polymer Research Group meeting at Pott Shrigley this week; this year it had the very timely theme “Polymers in the age of data”. Some great talks have really brought home to me both the promise of machine learning and laboratory automation in polymer science, as well as some of the practical barriers. Given the general interest in accelerated materials discovery using artificial intelligence, it’s interesting to focus on this specific class of materials to get a sense of the promise – and the pitfalls – of these techniques.

Debra Audis, from the USA’s National Institute of Standards and Technology, started the meeting off with a great talk on how to use machine learning to make predictions of polymer properties given information about molecular structure. She described three difficulties for machine learning – availability of enough reliable data, the problem of extrapolation outside the parameter space of the training set, and the problem of explainability.

A striking feature of Debra’s talk for me was its exploration of the interaction between old-fashioned theory, and new-fangled machine learning (ML). This goes in two directions – on the one hand, Debra demonstrated that incorporating knowledge from theory can greatly speed up the training of a ML model, as well as improving its ability to extrapolate beyond the training set. But given a trained ML model – essentially a black box of weights for your neural network, Debra emphasised the value of symbolic regression to convert the black box to a closed form expression of simple functional forms of the kind a theorist would hope to be able to derive from some physical principles, providing something a scientist might recognise as an explanation of the regularities that the machine learning model encapsulates.

But any machine learning model needs data – lots of data – so where does that data come from? One answer is to look at the records of experiments done in the past – the huge corpus of experimental data contained within the scientific literature. Jacqui Cole from Cambridge has developed software to extract numerical data, chemical reaction schemes, and to analyse images from the scientific data. For specific classes of (non-polymeric) materials she’s been able to create data sets with thousands of entries, using automated natural language processing to extract some of the contextual information that makes the data useful. Jacqui conceded that polymeric materials are particularly challenging for this approach; they have complex properties that are difficult to pin down to a single number, and what to the outsider may seem to be a single material (polyethylene for example) may actually be a category that encompasses molecules with a wider variety of subtle variations arising from different synthesis methods and reaction conditions. And Debra and Jacqui shared some sighs of exasperation at the horribly inconsistent naming conventions used by polymer science researchers.

My suspicion on this (informed a little by the outcomes of a large scale collaboration with a multinational materials company that I’ve been part of over the last five years) is that the limitations of existing data sets mean that the full potential of machine learning will only be unlocked by the production of new, large scale datasets designed specifically for the problem in hand. For most functional materials the parameter space to be explored is vast and multidimensional, so considerable thought needs to be given to how best to sample this parameter space to provide the training data that a good machine learning model needs. In some circumstances theory can help here – Kim Jelfs from Imperial described an approach where the outputs from very sophisticated, compute intensive theoretical models were used to train a ML model that could then interpolate properties at much lower compute cost. But we will always need to connect to the physical world and make some stuff.

This means we will need automated chemical synthesis – the ability to synthesise many different materials with systematic variation of the reactants and reaction conditions, and then rapidly determine the properties of this library of materials. How do you automate a synthetic chemistry lab? Currently, a synthesis laboratory consists of a human measuring out materials, setting up the right reaction conditions, then analysing and purifying the products, finally determining their properties. There’s a fundamental choice here – you can automate the glassware, or automate the researcher. In the UK, Lee Cronin at Glasgow (not at the meeting) has been a pioneer of the former approach, while Andy Cooper at Liverpool has championed the latter. Andy’s approach involves using commercial industrial robots to carry out the tasks a human researcher would do, while using minimally adapted synthesis and analytical equipment. His argument in favour of this approach is essentially an economic one – the world market for general purpose industrial robots is huge, leading to substantial falls in price, while custom built automated chemistry labs represent a smaller market, so one should expect slower progress and higher prices.

Some aspects of automating the equipment are already commercially available. Automatic liquid handling systems are widely available, allowing one, for example to pipette reactants into multiwell plates, so if one’s synthesis isn’t sensitive to air one can use this approach to do combinatorial chemistry. Adam Gormley from Rutgers described this approach for making a library of copolymers by an oxygen-tolerant adaptation of reversible addition−fragmentation chain-transfer polymerisation (RAFT), to produce libraries of copolymers with varying polymer molecular weight and composition. Another approach uses flow chemistry, in which reactions take place not in a fixed piece of glassware, but as the solvents containing the reactants travel down pipes, as described by Tanja Junkers from Monash, and Nick Warren from Leeds. This approach allows in-line reaction monitoring, so it’s possible to build in a feedback loop, adjusting the ingredients and reaction conditions on the fly in response to what is being produced.

It seems to me, as a non-chemist, that there is still a lot of specific work to be done to adapt the automation approach to any particular synthetic method, so we are still some way from a universal synthesis machine. Andy Cooper’s talk title perhaps alluded to this: “The mobile robotic polymer chemist: nice, but does it do RAFT?” This may be a chemist’s joke.

But whatever approach one has realised to be able to produce a library of molecules with different characteristics, and analyse their properties, there remains the question of how to sample what is likely to be a huge parameter space in order to provide the most effective training set for machine learning. We were reminded by the odd heckle from a very distinguished industrial scientist in the audience that there is a very classical body of theory to underpin this kind of experimental strategy – the Design of Experiments methodology. In these approaches, one selects the optimum set of different parameters in order most effectively to span parameter space.

But an automated laboratory offers the possibility of adapting the sampling strategy in response to the results as one gets them. Kim Jelfs set out the possible approaches very clearly. You can take the brute force approach, and just calculate everything – but this is usually prohibitively expensive in compute. You can use an evolutionary algorithm, using mutation and crossover steps to find a way through parameter space that optimises the output. Bayesian optimisation is popular, and generative models can be useful for taking a few more random leaps. Whatever the details, there needs to be a balance between optimisation and exploration – between taking a good formulation and making it better, and searching widely across parameter space for a possibly unexpected set of conditions that provides a step-change in the properties one is looking for.

It’s this combination of automated chemical synthesis and analysis, with algorithms for directing a search through parameter space, that some people call a “self-driving lab”. I think the progress we’re seeing now suggests that this isn’t an unrealistic aspiration. My somewhat tentative conclusions from all this:

We’re still a long way from an automated lab that can flexibly handle many different types of chemistry, so for a while its going to be a question of designing specific set-ups for particular synthetic problems (though of course there will be a lot of transferrable learning).
There is still lot of craft in designing algorithms to search parameter space effectively.
Theory still has its uses, both in accelerating the training of machine learning models, and in providing satisfactory explanations of their output.
It’s going to take significant effort, computing resource and money to develop these methods further, so it’s going to be important to select use cases where the value of an optimised molecule makes the investment worthwhile. Amongst the applications discussed in the meeting were drug excipients, membranes for gas separation, fuel cells and batteries, optoelectronic polymers.
Finally, the physical world matters – there’s value in the existing scientific literature, but it’s not going to be enough just to process words and text; for artificial intelligence to fulfil its promise for accelerating materials discovery you need to make stuff and test its properties.

Implications of Rachel Reeves’s Mais Lecture for Science & Innovation Policy

There will be a general election in the UK this year, and it is not impossible (to say the least) that the Labour opposition will form the next government. What might such a government’s policies imply for science and innovation policy? There are some important clues in a recent, lengthy speech – the 2024 Mais Lecture – given by the Shadow Chancellor of the Exchequer, Rachel Reeves, in which she sets out her economic priors.

In the speech, Reeves sets out in her view, the underlying problems of the UK economy – slow productivity growth leading to wage stagnation, low investment levels, poor skills (especially intermediate and technical) and “vast regional disparities, with all of England’s biggest cities outside London having productivity levels below the national average”. I think this analysis is now approaching being a consensus view – see, for example, this recent publication – The Productivity Agenda – from The Productivity Institute.

Interestingly, Reeves resists the temptation to blame everything on the current government, stressing that this situation reflects long-standing weaknesses, which began in the early 1990’s, which were not sufficiently challenged by the Labour governments of the late 90’s and 00’s, and then were made much worse in the 2010’s by Austerity, Brexit, and post-pandemic policy instability. Singling out Conservative Chancellor of the Exchequer Nigel Lawson as the author of policies that were both wrong in principle and badly executed, she identifies this period as the root of “an unprecedented surge in inequality between places and people which endures today. The decline or disappearance of whole industries, leaving enduring social and economic costs and hollowing out our industrial strength. And – crucially – diminishing returns for growth and productivity.”

To add to our problems, Reeves stresses that the external environment the UK now faces is much more challenging than in previous decades, with geopolitical instability reviving the basic question of national security, uncertainties from new technologies like AI, and the challenges of climate instability and the net zero energy transition. She is blunt in saying “globalisation, as we once knew it, is dead” – “a growth model reliant on geopolitical stability is a growth model resting on increasingly shallow foundations.”

What comes next? For Reeves, the new questions are “how Britain can pay its way in the world; of our productive capacity; of how to drive innovation and diffusion throughout our economy; of the regional distribution of work and opportunity; of how to mobilise investment, develop skills and tackle inefficiencies to modernise a sclerotic economy; and of energy security”, and the answers are to be found what economist Dani Rodrik calls “productivism”.

In practise, this means an industrial strategy which, recognising the limits of central government’s information and capacity to act, works in partnership. This needs to have both a sector focus – building on the UK’s existing areas of comparative advantage and its strategic needs – and a regional focus, working with local and regional government to support the development of clusters and the realisation of agglomeration benefits.

In terms of the mechanics of the approach, Reeves anticipates that this central mission of government – restoring economic growth – will be driven from the Treasury, through a a beefed up “Enterprise and Growth” unit. To realise these ambitions, she identifies three areas of focus – recreating macroeconomic stability, investment – particularly in partnership with the private sector, and reform – of the planning system, housing, skills, the labour market and regional governance.

Innovation is a central part of Reeves’s vision for increased investment, partly through the familiar call for more capital to flow to university spin-outs. But there is also a call for more focus on the diffusion of new technologies across the whole economy, including what Reeves has long called the “everyday economy”. In my view, this is correct, but will need new institutions, or the adaptation of existing ones (as I argued, with Eoin O’Sullivan: “What’s missing in the UK’s R&D landscape – institutions to build innovation capacity”). There is a very sensible commitment to a ten year funding cycle for R&D institutions, essential not least because some confidence in the longevity of programmes is essential to give the private sector the confidence to co-invest.

This was quite a dense speech, and the commentary around it – including the pre-briefing from Labour – was particularly misleading. I think it would be a mistake to underestimate how much of a break it represents from the conventional economic wisdom of the past three decades, though the details of the policy programme remain to be filled in, and, as many have commented, its implementation in a very tough fiscal environment is going to be challenging. Our current R&D landscape isn’t ideally configured to support these aspirations and the UK’s current challenges (as I argue in my long piece “Science and innovation policy for hard times: an overview of the UK’s Research and Development landscape”); I’d anticipate some reshaping to support the “missions” that are intended to give some structure to the Labour programme. And, as Reeves says unequivocally, of these missions, the goal of restoring productivity and economic growth is foundational.

Science and Innovation in the 2023 Autumn Statement

On the 22nd November, the Government published its Autumn Statement. This piece, published in Research Professional under the title Economic clouds cast gloom over the UK’s ambitions for R&D, offers my somewhat gloomy perspective on the implications of the statement for science and innovation.

This government has always placed a strong rhetorical emphasis on the centrality of science and innovation in its plans for the nation, though with three different Prime Ministers, there’ve been some changes in emphasis.

This continues in the Autumn Statement: a whole section is devoted to “Supporting the UK’s scientists and innovators”, building on the March 2023 publication of a “UK Science and Technology Framework”, which recommitted to increasing total public spending on research to £20 billion in FY 2024/25. But before going into detail on the new science-related announcements in the Autumn Statement, let’s step back to look at the wider economic context in which innovation strategy is being made.

There are two giant clouds in the economic backdrop the Autumn Statement. One is inflation; the other is economic growth – or, to be more precise, the lack of it.

Inflation, in some senses, is good for governments. It allows them to raise taxes without the need for embarrassing announcements, as people’s cost-of-living wage rises take them into higher tax brackets. And by simply failing to raise budgets in line with inflation, public spending cuts can be imposed by default. But if it’s good for governments, it’s bad for politicians, because people notice rising prices, and they don’t like it. And the real effect of stealth public spending cuts do, nonetheless, materialise.

The effect of the inflation we’ve seen since 2021 is a rise in price levels of around 20%; while the inflation rate peak has surely passed, prices will continue to rise. We can already see the effect on the science budget. Back in 2021, the Comprehensive Spending Review announced a significant increase in the overall government research budget, from £15 billion to £20 billion in 24/25. By next year, though, the effect of inflation will have been to erode that increase in real terms, from £5 billion to less than £2 billion in 2021 money. The effect on Core Research is even more dramatic; in effect inflation will have almost totally wiped out the increase promised in 2021.

Our other problem is persistent slow economic growth, as I discussed here. The underlying cause of this is the dramatic decrease in productivity growth since the financial crisis of 2008. The consequence is the prospect of two full decades without any real growth in wages, and, for the government, the need to simultaneously increase the tax burden and squeeze public services in an attempt to stabilise public debt.

The detailed causes of the productivity slowdown are much debated, but the root of it seems to be the UK’s persistent lack of investment, both public and private (see The Productivity Agenda for a broad discussion). Relatively low levels of R&D are part of this. The most significant policy change in the Autumn Statement does recognise this – it is a tax break allowing companies to set the full cost of new plant and machinery against corporation tax. On the government side, though, the plans are essentially for overall flat capital spending – i.e., taking into account inflation, a real terms cut. Government R&D spending falls in this overall envelope, so is likely to be under pressure.

Instead, the government is putting their hopes on the private sector stepping up to fill the gap, with a continuing emphasis on measures such as R&D tax credits to incentivise private sector R&D, and reforms to the pension system – including the “Long-term Investment for Technology and Science (LIFTS)” initiative – to bring more private money into the research system. The ambition for the UK to be a “Science Superpower” remains, but the government would prefer not to have to pay for it.

One significant set of announcements – on the “Advanced Manufacturing Plan” – marks the next phase in the Conservatives’ off-again, on-again relationship with industrial strategy. Commitments to support advanced manufacturing sectors such as aerospace, automobiles and pharmaceuticals, as well as the “Made Smarter” programme for innovation diffusion, are very welcome. The sums themselves perhaps shouldn’t be taken too seriously; the current government can’t bind its successor, whatever its colour, and anyway this money will have to be found within the overall spending envelope produced by the next Comprehensive Spending Review. But it is very welcome that, after the split-up of the Department of Business, Energy and Industrial Strategy, that the successor Department of Business and International Trade still maintains an interest in research and innovation in support of mainstream business sectors, rather than assuming that is all now to be left to its sister Department of Science, Innovation and Technology.

For all the efforts to create a tax-cutting headline, the economic backdrop for this Autumn statement is truly grim. There is no rosy scenario for the research community to benefit from; the question we face instead is how to fulfil the promises we have been making that R&D can indeed lead to productivity growth and economic benefit.

As times change, the UK’s R&D landscape needs to change too

I took part in a panel discussion last Thursday at the Royal Society, about the UK’s R&D landscape. The other panelists were Anna Dickinson from the think tank Onward, and Ben Johnson, Policy Advisor at the Department of Science, Innovation and Technology, and our chair was Athene Donald. This is a much expanded and tidied version of my opening remarks.

What is the optimum shape of the research and development landscape for the UK? The interesting and important questions here are:

What kind of R&D is being done?
In what kind of institution is R&D being done?
What kind of people do R&D?
Who sets the priorities?
Who pays for it?

I’m a physicist, but I want to start with lessons from history and geography.

If there’s one lesson we should learn from history, it’s that the way things are now, isn’t the way they always have been. And we should be curious about different countries arrange their R&D landscapes – not just in the Anglophone countries and our European partners and neighbours that we are so familiar with, but in the East Asian countries that have been so economically successful recently.

The particular form that a nation’s R&D landscape takes arises from a set of political, economic circumstances, influenced by the outcome of ideological arguments that take place both within the science community and in wider society.

I’ve just read Iwan Rhys Morus’s fascinating and engaging book on 19th century Science and Technology: “How the Victorians took us to the Moon”. It’s fitting that the book begins with a discussion of just such an ideological debate – about the future orientation of the Royal Society after the death of Sir Joseph Banks in 1820, at the end of his autocratic – and aristocratic – 41 year rule over the Society. The R&D landscape that emerged from these struggles was the one appropriate for the United Kingdom in the Victorian era – a nation going through an industrial revolution, and acquiring an world empire. That landscape was dominated by men of science (and they were men), who believed, above all, in the idea of progress. They valued self-discipline, self-confidence, precision and systematic thinking, while sharing assumptions about gender, class and race that would no longer be acceptable in today’s world.

Morus argues that many of the attitudes, assumptions and institutions of the science community that led to the great technological advances of the 20th century were laid down in the Victorian period. As someone who received their training in one of those great Victorian institutions – Cambridge’s Cavendish Laboratory, that rings true to me. I vividly remember as a graduate student that the great physicist Sir Sam Edwards had a habit of dismissing some rival theorist with the words “it was all done by Lord Rayleigh”. Lots of it probably was.

But also, learning how to do science in the mid-1980’s, I was just at the tail end of another era – what David Edgerton calls the Warfare State. The UK was a nation in which science had been subservient to the defence needs of two world wars, and a Cold War in which technology was the front line. The state ran a huge defence research establishment, and an associated nuclear complex where the lines between civil nuclear power and the nuclear weapons programme were blurred. This was a corporatist world, in which the boundaries between big, national companies like GEC and ICI and the state were themselves not clear. And there was a lot of R&D being done – in 1980, the UK was one of the most R&D intensive countries in the world.

We live in a very different world now. R&D in the private sector still dominates, but now pretty much half of it is done in the labs of overseas owned multinationals. In a world in which R&D is truly globalised, it doesn’t make a lot of sense to talk about UK plc. There’s much more emphasis on the role of spin-outs and start-ups – venture capital supported companies based on protected intellectual property. This too is globalised – we agonise about how few of these companies, even when they are successful, stay to scale up in the UK rather than moving to Germany or the USA. The big corporate laboratories of the past, where use-inspired basic research co-existed with more applied work, are a shadow of their former selves or gone entirely, eroded by a new focus on shareholder value.

Meanwhile, we have seen UK governments systematically withdraw support from applied research, as Jon Agar’s work has documented. After a couple of decades in which university research had been squeezed, the 2000’s saw a significant increase in support through the research councils, but this came at the cost of continual erosion of public sector research establishments. This has left the research councils in a much more dominant position in the government funding landscape – the fraction of government R&D funding allocated through research councils has increased from about 12% in the mid-1980’s to around 30% now. But the biggest rise in government support for R&D has come through the non-specific subsidy for private sector – the R&D tax credit – whose cost rose from just over £1 billion in 2010 to more than £7 billion in 2019.

These dramatic changes in the R&D landscape that have unfolded between the 1980s and now should be understood in the context of the wider changes in the UK’s political economy over that period, often characterised as the dominance of neoliberalism and globalisation. There has been an insistence on the primacy of market mechanisms, and the full integration of the UK in a global free-trading environment, together with a rejection of any idea of state planning or industrial strategy. The shape of the UK economy changed very dramatically, with a dramatic shrinking of the manufacturing sector, the exacerbation of regional economic imbalances, and a persistent trade deficit with the rest of the world. The rise and fall of North Sea Oil and the development of a bubble in financial services has contributed to these trends.

The world looks very different now. The pandemic taught us that global supply chains can be very fragile in a crisis, while the Ukraine war reminded us that state security still, ultimately, depends on high technology and productive capacity. The slower crisis of climate change continues – we face a wrenching economic transition to move our energy economy to a zero carbon basis, while the already emerging effects of climate disruption will be challenging. In the UK, we have a failing economy, where productivity growth has flat-lined since 2008; the consequences are that wages have stagnated to a degree unprecedented in living memory and public services have deteriorated to politically unacceptable levels.

In place of globalisation, we see a retreat to trading blocks. Industrial strategy has returned to the USA at scale $50 bn from the CHIPS act to rebuild its semiconductor industry, and $370 bn for a green transition. The EU is responding. Of course in East Asia and China industrial strategy never went away.

So the question we face now is whether our R&D landscape is the right one for the times we live in now? I don’t think so. Of course, our values are different from those both of the Victorians and mid-20th century technocrats, and our circumstances are different too. Many of the assumptions of the post-1980’s political settlement are now in question. So how must the landscape evolve?

The new R&D landscape needs to more focused on the pressing problems we face: the net zero transition, the productivity slowdown, poor health outcomes, the security of the state. Here in the Royal Society, I don’t need to make the case for the importance of basic science, exploratory research, the unfettered inquiries of our most creative scientists. But in addition , we need more applied R&D, it needs to be more geographically dispersed, more inclusive. It has to build on the existing strengths of the country – but by itself that is not enough, and we will have to rebuild some of the innovation and manufacturing capacity that we have lost. And I think this manufacturing and innovation capacity is important for basic science too, because it’s this technological capacity that allows us to implement and benefit from the basic science. For example, one can be excited by the opportunities of quantum computing, but to make it work it’s probably going to rely on manufacturing technologies already implemented for semiconductors.

The national R&D landscape we have has evolved as the material conditions and ideological assumptions of the nation have changed, and as those conditions and assumptions change, so must the national R&D landscape change in response.

“Science Superpower: the UK’s Global Science Strategy beyond Horizon Europe”

Last Wednesday the Science Minister, George Freeman MP, gave a wide ranging speech with this title, on the current state of UK science policy at the think-tank Onward. A video of the speech can be watched on YouTube here. As a response to the speech, there was a panel discussion the following day, featuring Prof Sir John Bell, Lord David Willetts, James Phillips, Tabitha Goldstaub, Priya Guha and and myself, chaired by Onward’s Adam Hawksbee. This is also available to watch on YouTube. This, more or less, is what I said in my opening statement.

Hello. I’m Richard Jones, talking to you from Oldham Town Hall – which I think is very on-brand for Onward, and indeed for myself…

I want to start where the Minister finished – what are we talking about, when we talk about being a “Science Superpower”? This is part of that broader question of how the UK finds its place in the world.

The UK represents a little less than 3% of the world’s high tech economy. It’s not the USA, it’s not China. But the UK does have a real potential competitive advantage in the strength of its science base – it is genuinely outperforming, at least (and this qualification is important) when it is judged on purely academic metrics.

The challenge – and this is the “Innovation Nation” aspect that the Minister stresses – is applying that science strength to the critical issues the UK – and the world – faces. These challenges include:

The UK’s more than a decade long stagnation in productivity growth;
The wrenching economic transition we face to achieve a net zero energy economy;
Ensuring good health outcomes for our citizens;
National security in an increasingly dangerous world.

To begin with productivity, it can’t be stressed too much how the stagnation of productivity growth after 2008 underlies pretty much all the difficulties the country faces – stagnant wages, the persistent fiscal deficit, the difficulties we’re seeing in funding public services to the standard people expect

As the Minister said, to get economic growth back we need to be accelerating progress in high tech sectors

But there’s a paradox here – the economist Diane Coyle, from the Productivity Institute, has analysed the productivity slowdown, and finds the biggest contributors to the slowdown are precisely those high-tech sectors that we think should be our strength. [Source: Coyle & Mei, Diagnosing the UK Productivity Slowdown: Which Sectors Matter and Why?]

In Pharmaceuticals, productivity growth was 0.6% a year on average between 1998 and 2008. But between 2009-2019 pharma industry productivity actually fell, by 0.2% a year on average.

So, we need to do things differently.

Money is important, and the government’s spending uplift is real, significant in scale, and to be welcomed.

I welcome ARIA as a chance to try and experiment with different funding mechanisms.

But from the perspective of Oldham, the biggest and most welcome change the minister talked about was the new focus on place and clusters across the UK

The UK is two nations – a high performing Northern European economy in the Greater Southeast. And beyond, in the North, The Midlands, Wales – we have places with economies comparable to southern Italy or Portugal. Our big cities – like Birmingham, Greater Manchester and Glasgow – have productivity below the UK average. This isn’t normal – in most developed countries, its the big cities that drive the national economy. Why can’t Manchester be more like Munich, a similar size city, that’s one of Germany’s innovation hubs? If it was, it would generate about £40 billion a year more value for the UK.

This is a huge waste of potential. We need to identify nascent clusters, and work with those places to build up their innovation capacity, build industrial R&D, attract in investment from outside, and give people in places like Oldham the opportunity that the Minister talks about to take part in this high tech economy.

But money isn’t everything. For example, we do health research to support the health of our citizens as well as to create economic value. The Oxford vaccine was a brilliant example of this.

But even pre-pandemic, a man born in Oldham 2016-2018 could expect to live in good health for 58 years. For a man in Oxfordshire, healthy life expectancy was 68.3 years! [Source: Health state life expectancy at birth and at age 65 years by local areas, UK, ONS.]

Ten lost years for Oldhamites! The human cost of those years of ill-health and premature death is huge. But so is the economic cost – this ill-health is a major contributor to the productivity gap in Oldham and places like it, all across the UK

That’s something R&D should do something about – this truly would be “innovation for the nation”.

We have to do things differently. We need to apply our science to address the big strategic problems the UK faces, and we need that to be an effort that the whole nation takes part in – and benefits from.

None of this should take away from the power of great research centres like Cambridge and Oxford – that really is a supercluster, a massive asset for the nation.

The question is, how can we build on that and spread the benefits across the rest of the country? There are plenty of great spin-outs from Cambridge and Oxford. We need them to scale-up in the UK, and not feel they have to move to Germany, or California, to succeed. So why shouldn’t their first factory be in Rochdale or Rotherham, or Dudley or Stoke-on-Trent?

So yes, let’s aspire to be an innovation nation, but to build that, we need innovation cities and innovation regions all across the UK.

For (much) more on this, see my Productivity Institute paper Science and innovation policy for hard times: an overview of the UK’s Research and Development landscape.

Science and innovation policy for hard times: an overview of the UK’s Research and Development landscape

A revised and tidied up version of my blogpost series, An Index of Issues in UK Science and Innovation Policy, has now been published as a Productivity Insights Paper under the auspices of The Productivity Institute. My thanks to Bart van Ark for encouraging me to do this, and to Krystyna Rudzki for editing the draft.

Download the PDF here: Science and innovation policy for hard times: an overview of the UK’s Research and Development landscape

Science and innovation policy for hard times

This is the concluding section of my 8-part survey of the issues facing the UK’s science and innovation system, An Index of Issues in UK Science and Innovation Policy.

The earlier sections were:
1. The Strategic Context
2. Some Overarching Questions
3. The Institutional Landscape
4. Science priorities: who decides?
5. UK Research and Innovation
6. UK Government Departmental Research
7. Horizon Europe (and what might replace it) and ARIA

8.1. A “science superpower”? Understanding the UK’s place in the world.

The idea that the UK is a “science superpower” has been a feature of government rhetoric for some time, most recently repeated in the Autumn Statement speech. What might this mean?

If we measure superpower status by the share of world resources devoted to R&D (both public and private) by single countries, there are only two science superpowers today – the USA and China, with a 30% and 24% share of science spending (OECD MSTI figures for 2019 adjusted for purchasing power parity, including all OECD countries plus China, Taiwan, Russia, Singapore, Argentina and Romania). If we take the EU as a single entity, that might add a third, with a 16% share (2019 figure, but excluding UK). The UK’s share is 2.5% – thus a respectable medium size science power, less than Japan (8.2%) and Korea (4.8%), between France (3.1%) and Canada (1.4%).

It’s often argued, though, that the UK achieves better results from a given amount of science investment than other countries. The primary outputs of academic science are scientific papers, and we can make an estimate of a paper’s significance by asking how often it is cited by other papers. So another measure of the UK’s scientific impact – the most flattering to the UK, it turns out – is to ask what fraction of the world’s most highly cited papers originate from the UK.

By this measure, the two leading scientific superpowers are, once again, the USA and China, with 32% and 24% shares respectively; on this measure the EU collectively, at 29%, does better than China. The UK scores well by this measure, at 13.4%, doing substantially better than higher spending countries like Japan (3.1%) and Korea (2.7%).

A strong science enterprise – however measured – doesn’t necessarily by itself translate into wider kinds of national and state power. Before taking the “science superpower” rhetoric serious we need to ask how these measures of scientific activity and scientific activity translate into other measures of power, hard or soft.

Even though measuring the success of our academic enterprise by its impact on other academics may seem somewhat self-referential, it does have some consequences in supporting the global reputation of the UK’s universities. This attracts overseas students, in turn bringing three benefits: a direct and material economic contribution to the balance of payments, worth £17.6 bn in 2019, a substantial subsidy to the research enterprise itself, and, for those students who stay, a source of talented immigrants who subsequently contribute positively to the economy.

The transnational nature of science is also significant here; having a strong national scientific enterprise provides a connection to this wider international network and strengthens the nation’s ability to benefit from insight and discoveries made elsewhere.

But how effective is the UK at converting its science prowess into hard economic power? One measure of this is the share of world economic value added in knowledge and technology intensive businesses. According to the USA’s NSF, the UK’s share of value added in this set of high productivity manufacturing and services industries that rely on science and technology is 2.6%. We can compare this with the USA (25%), China (25%), and the EU (18%). Other comparator countries include Japan (7.9%), Korea (3.7%) and Canada (1.2%).

Does it make sense to call the UK a science superpower? Both on the input measure of the fraction of the world’s science resources devoted to science, and on the size of the industry base this science underpins, the UK is an order of magnitude smaller than the world leaders. In the historian David Edgerton’s very apt formulation, the UK is a large Canada, not a small USA.

Where the UK does outperform is in the academic impact of its scientific output. This does confer some non-negligible soft power benefits of itself. The question to ask now is whether more can be done to deploy this advantage to address the big challenges the nation now faces.

8.2. The UK can’t do everything

The UK’s current problems are multidimensional and its resources are constrained. With less than 3% of the world’s research and development resources, no matter how effectively these resources are deployed, the UK will have to be selective in the strategic choices it makes about research priorities.

In some areas, the UK may have some special advantages, either because the problems/opportunities are specific to the UK, or because history has given the UK a comparative advantage in a particular area. One example of the former might be the development of technologies for exploiting deep-water floating offshore wind power. In the latter category, I believe the UK does retain an absolute advantage in researching nuclear fusion power.

In other areas, the UK will do best by being part of larger transnational research efforts. At the applied end, these can be in effect led by multinational companies with a significant presence in the UK. Formal inter-governmental collaborations are effective in areas of “big science” – which combine fundamental science goals with large scale technology development. For example, in high energy physics the UK has an important presence in CERN, and in radio astronomy the Square Kilometer Array is based in the UK. Horizon Europe offered the opportunity to take part in trans-European public/private collaborations on a number of different scales, and if the UK isn’t able to associate with Horizon Europe other ways of developing international collaborations will have to be built.

But there will remain areas of technology where the UK has lost so much capability that the prospect of catching up with the world frontier is probably unrealistic. Perhaps the hardware side of CMOS silicon technology is in this category (though significant capability in design remains).

8.3. Some pitfalls of strategic and “mission driven” R&D in the UK

One recently influential approach to defining research priorities links them to large-scale “missions”, connected to significant areas of societal need – for example, adapting to climate change, or ensuring food security. This has been a significant new element in the design of the current EU Horizon Programme (see EU Missions in Horizon Europe).

For this approach to succeed, there needs to be a match between the science policy “missions” and a wider, long term, national strategy. In my view, there also needs to be a connection to the specific and concrete engineering outcomes that are needed to make an impact on wider society.

In the UK, there have been some moves in this direction. The research councils in 2011 collectively defined six major cross-council themes (Digital Economy; Energy; Global Food Security; Global Uncertainties; Lifelong Health and Wellbeing; Living with Environmental Change), and steered research resources into (mostly interdisciplinary) projects in these areas. More recently, UKRI’s Industrial Strategy Challenge Fund was funded from a “National Productivity Investment Fund” introduced in the 2016 Autumn Statement and explicitly linked to the Industrial Strategy.

These previous initiatives illustrate three pitfalls of strategic or “mission driven” R&D policy.

The areas of focus may be explicitly attached to a national strategy, but that strategy proves to be too short-lived, and the research programmes it inspires outlive the strategy itself. The Industrial Strategy Challenge Fund was linked to the 2017 Industrial Strategy, but this strategy was scrapped in 2021, despite the fact that the government was still controlled by the same political party.
Research priorities may be connected to a lasting national priority, but the areas of focus within that priority are not sufficiently specified. This leads to a research effort that risks being too diffuse, lacking a commitment to a few specific technologies and not sufficiently connected to implementation at scale. In my view, this has probably been the case in too much research in support of low-carbon energy.
In the absence of a well-articulated strategy from central government, agencies such as Research Councils and Innovate UK guess what they think the national strategy ought to be, and create programmes in support of that guess. This then risks lacking legitimacy, longevity, and wider join-up across government.

In summary, mission driven science and innovation policy needs to be informed by carefully thought through national strategy that commands wide support, is applied across government, and is sustained over the long-term.

8.4. Getting serious about national strategy

The UK won’t be able to use the strengths of its R&D system to solve its problems unless there is a settled, long-term view about what it wants to achieve. What kind of country does the UK want to be in 2050? How does it see its place in the world? In short, it needs a strategy.

A national strategy needs to cut across a number of areas. There needs to be an industrial strategy, about how the country makes a living in the world, how it ensures the prosperity of its citizens and generates the funds needed to pay for its public services. An energy strategy is needed to navigate the wrenching economic transition that the 2050 Net Zero target implies. As our health and social care system buckles under the short-term aftermath of the pandemic, and faces the long-term challenge of an ageing population, a health and well-being strategy will be needed to define the technological and organisational innovation needed to yield an affordable and humane health and social care system. And, after the lull that followed the end of the cold war, a strategy to ensure national security in an increasingly threatening world must return to prominence.

These strategies need to reflect the real challenges that the UK faces, as outlined in the first part of this series. The goals of industrial strategy must be to restore productivity growth and to address the UK’s regional economic imbalances. Innovation and skills must be a central part of this, and given the condition large parts of the UK find themselves in, there need to be conscious efforts to rebuild innovation and manufacturing capacity in economically lagging regions. There needs to be a focus on increasing the volume of high value exports (both goods and services) that are competitive on world markets. The goal here should be to start to close the balance of payments gap, but in addition international competitive pressure will also bring productivity improvements.

An energy strategy needs to address both the supply and demand side to achieve a net zero system by 2050, and to guarantee security of supply. It needs to take a whole systems view at the outset, and to be discriminating in deciding which aspects of the necessary technologies can be developed in the UK, and which will be sourced externally. Again, the key will be specificity. For example, it is not enough to simply promote hydrogen as a solution to the net zero problem – it’s a question of specifying how it is made, what it is used for, and identifying which technological problems are the ones that the UK is in a good position to focus on and benefit from, whether that might be electrolysis, manufacture of synthetic aviation fuel, or whatever.

A health and well-being strategy needs to clarify the existing conceptual confusion about whether the purpose of a “Life Sciences Strategy” is to create high value products for export, or to improve the delivery of health and social care services to the citizens of the UK. Both are important, and in a well-thought through strategy each can support the other. But they are distinct purposes, and success in one does not necessarily translate to success in the other.

Finally, a security strategy should build on the welcome recognition of the 2021 Integrated Review that UK national security needs to be underpinned by science and technology. The traditional focus of security strategy is on hard power, and this year’s international events remind us that this remains important. But we have also learnt that the resilience of the material base of economy can’t be taken for granted. We need a better understanding of the vulnerabilities of the supply chains for critical goods (including food and essential commodities).

The structure of government leads to a tendency for strategies in each of these areas to be developed independently of each other. But it’s important to understand the way these strategies interact with each other. We won’t have any industry if we don’t have reliable and affordable low carbon energy sources. Places can’t improve their economic performance if large fractions of their citizens can’t take part in the labour market due to long-term ill-health. Strategic investments in the defence industry can have much wider economic spillover benefits.

For this reason it is not enough for individual strategies to be left to individual government departments. Nor is our highly centralised, London-based government in a position to understand the specific needs and opportunities to be found in different parts of the country – there needs to be more involvement of devolved nation and city-region governments. The strategy needs to be truly national.

8.5. Being prepared for the unexpected

Not all science should be driven by a mission-driven strategy. It is important to maintain the health of the basic disciplines, because this provides resilience in the face of unwelcome surprises. In 2019, we didn’t realise how important it would be to have some epidemiologists to turn to. Continuing support for the core disciplines of physical, biological and medical science, engineering, social science and the humanities should remain a core mission of the research councils, the strength of our universities is something we should preserve and be proud of, and their role in training the researchers of the future will remain central.

Science and innovation policy also needs to be able to create the conditions that produce welcome surprises, and then exploit them. We do need to be able to experiment in funding mechanisms and in institutional forms. We need to support creative and driven individuals, and to recognise the new opportunities that new discoveries anywhere in the world might offer. We do need to be flexible in finding ways to translate new discoveries into implemented engineering solutions, into systems that work in the world. This spirit of experimentation could be at the heart of the new agency ARIA, while the rest of the system should be flexible enough to adapt and scale up any new ways of working that emerge from these experiments.

8.7 Building a national strategy that endures

A national strategy of the kind I called for above isn’t something that can be designed by the research community; it needs a much wider range of perspectives if, as is necessary, it’s going to be supported by a wide consensus across the political system and wider society. But innovation will play a key role in overcoming our difficulties, so there needs to be some structure to make sure insights from the R&D system are central to the formulation and execution of this strategy.

The new National Science and Technology Council, supported by the Office for Science and Technology Strategy, could play an important role here. Its position at the heart of government could give it the necessary weight to coordinate activities across all government departments. It would be a positive step if there was a cross-party commitment to keep this body at the heart of government; it was unfortunate that with the Prime Ministerial changes over the summer and autumn the body was downgraded and subsequently restored. To work effectively its relationships with the Government Office for Science, the Council for Science and Technology need to be clarified.

UKRI should be able to act as an important two-way conduit between the research and development community and the National Science and Technology Council. It should be a powerful mechanism for conveying the latest insights and results from science and technology to inform the development of national strategy. In turn, its own priorities for the research it supports should be driven by that national strategy. To fulfil this function, UKRI will be have to develop the strategic coherence that the Grant Review has found to be currently lacking.

The 2017 Industrial Strategy introduced the Industrial Strategy Council as an advisory body; this was abruptly wound up in 2021. There is a proposal to reconstitute the Industrial Strategy Council as a statutory body, with a similar status, official but independent of government, to the Office of Budgetary Responsibility or the Climate Change Committee. This would be a positive way of subjecting policy to a degree of independent scrutiny, holding the government of the day to account, and ensuring some of the continuity that has been lacking in recent years.

8.8 A science and innovation system for hard times

Internationally, the last few years have seen a jolting series of shocks to the optimism that had set in after the end of the cold war. We’ve had a worldwide pandemic, there’s an ongoing war in Europe involving a nuclear armed state, we’ve seen demonstrations of the fragility of global supply chains, while the effects of climate change are becoming ever more obvious.

The economic statistics show decreasing rates of productivity growth in all developed countries; there’s a sense of the worldwide innovation system beginning to stall. And yet one can’t fail to be excited by rapid progress in many areas of technology; in artificial intelligence, in the rapid development and deployment of mRNA vaccines, in the promise of new quantum technologies, to give just a few examples. The promise of new technology remains, yet the connection to the economic growth and rising living standards that we came to take for granted in the post-war period seems to be broken.

The UK demonstrates this contrast acutely. Despite some real strengths in its R&D system, its economic performance has fallen well behind key comparator nations. Shortcomings in its infrastructure and its healthcare system are all too obvious, while its energy security looks more precarious than for many years. There are profound disparities in regional economic performance, which hold back the whole country.

If there was ever a time when we could think of science as being an ornament to a prosperous society, those times have passed. Instead, we need to think of science and technology as the means by which our society becomes more prosperous and secure – and adapt our science and technology system so it is best able to achieve that goal.

An index of issues in UK science and innovation policy – part 6: UK Government Departmental Research

In the first part of this series attempting to sum up the issues facing UK science and innovation policy, I tried to set the context by laying out the wider challenges the UK government faces, asking what problems we need our science and innovation system to contribute to solving.

In the second part of the series, I posed some of the big questions about how the UK’s science and innovation system works, considering how R&D intensive the UK economy should be, the balance between basic and applied research, and the geographical distribution of R&D.

In the third part, I discussed the institutional landscape of R&D in the UK, looking at where R&D gets done in the UK.

In the fourth part, looking at the funding system, I considered who pays for R&D, and how decisions are made about what R&D to do.

In the fifth part, I looked in more detail at UK Research and Innovation, the government’s main agency for funding academic science.

There’s a tendency for analyses of the UK public R&D system to focus on the research councils that make up UKRI, because they are the most visible. But the UK government funds R&D in a number of other ways – for example through government departments – and it’s these other funding routes that I turn to in this section.

6.1. Other departmental science

Despite the systematic shift of UK government supported R&D from government applied research to “curiosity driven” research in HE between 1980 to 2010 that I described in part 2 of this series, a a substantial amount of government R&D is still routed through government departments, in support of those departments’ priorities.

Departmental science has always been vulnerable to budget cuts. The effects of cutting a research budget will only show up at some unspecified time in the future, so the temptation will always be for a department to sacrifice science in favour of immediate operating expenses. The 2010-2015 policy of austerity produced some dramatic falls in already small departmental research budgets. For the environment, the DEFRA R&D budget fell by 58% in real terms between 2010 and 2015, to £82 m/year, and since then has fallen further to £58m/yr. Transport R&D saw a 22% real terms cut, Education 53%, and the Home Office 60%, over the duration of the Coalition Government. It’s difficult to argue that all necessary innovation in these areas has already been done.

However, the biggest departmental spenders remain Defence, Health, and Business, Energy and Industrial Strategy (outside the latter’s formal responsibility for the UKRI budget). These departments hold key responsibilities for the big challenges I outlined at the start of the series – productivity, energy/net zero, security and health, so it’s worth focusing on them in more detail.

6.2 The Ministry of Defence

The Ministry of Defence has a 20/21 R&D budget of £1.1 bn, and this is expected to rise substantially as the overall Defence budget itself increases. In Defence R&D, there’s a distinction between more long-ranged science and technology, and the expense of development and deployment of systems that are closer to application.

The 2020 Ministry of Defence science and technology strategy committed to spending 1.2% of the overall defence budget on science and technology, under the control of the MoD Chief Scientific Advisor. The total defence budget is projected to increase from £41.2 bn in 20/21 to £47.7bn in 24/25, so this implies a 15% increase in the science and technology budget, to £570m. One should also mention rising sums of money for R&D in the security services – with an allocation of £695m over 3 years.

As I wrote in an earlier blogpost Science and innovation policy in a new age of insecurity, it’s inevitable that in a more threatening world, we’ll see a return to higher direct spending directly on R&D for defense in its broadest sense. So the question now should be, are these increases enough, and are they directed in the right areas?

I don’t know the answer to this. A recent article in Nature highlighted some interesting comparisons. According to this,
the USA spent about $80 bn in 2020 on defence R&D, a factor of 60-fold larger than the UK. The USA’s economy is about 8 times larger than the UK, but this remains a massive gap.

A country that the UK would more commonly compare itself, both in the overall size of its economy and the importance it attaches to defence, is France. France spent €5.6 bn on defence R&D in 2020, more than four times the UK figure, despite roughly comparable overall expenditures on defence.

Definitions of the boundary between R&D and deployment make comparisons difficult, but it’s tempting to interpret this as a consequence of France’s traditionally more Gaullist approach to defence, preferring to develop its own systems rather than relying on allies. In an increasingly uncertain world, it’s going to be important to get this balance right.

6.3. Department of Health and Social Care

As defence R&D was run down, the relative beneficiary was research for health and life sciences. One big institutional manifestation of this shift was the foundation in 2006 of the National Institute of Health Research, to bring together R&D funded directly through the Department of Health in association with NHS England. This remains distinct from the Medical Research Council, which is now incorporated in UK Research and Innovation; NIHR’s focus on England means that the devolved nations have their own budgets. For health research. NIHR is now a major component of the public R&D system – in 19/20 it spent £1.1 bn on research, infrastructure and research training, accounting for about 90% of DHSC’s research spend.

The mission of NIHR is “to improve the health and wealth of the nation through research.” This statement neatly encapsulates the twin goals of the UK’s overall Life Sciences strategy, to improve the delivery of health and social care to the nation’s citizens, on the one hand, and to support the pharma, biotech and medical technology sectors on the other. As I’ve discussed elsewhere, these goals are often not sufficiently differentiated, meaning that the potential tensions between them are not resolved. In my view, NIHR’s close relationship with the National Health Service should mean that NIHR’s focus should remain on improving the health outcomes of the UK’s citizens, with the support of any commercial opportunities that flow from this a secondary goal.

Health R&D was a big beneficiary of the 2021 Spending Review, and if NIHR’s budget rises in line with the overall DHSC R&D budget, this should bring a £730m uplift in NIHR funding compared to flat cash.

One issue that could be addressed in the context of this overall funding uplift is the geographical concentration of NIHR research, which historically has been even more focused on the Golden Triangle (and, within that, on London in particular) than research council funding. In 2018, around 52% of NIHR funding went to London and the Southeast, with 35% of that in London, whose share of England’s population is 16% (Source: UK Health Research Analysis).

NIHR has a vision of a population ‘actively involved in research to improve health and wellbeing for themselves, their families and their communities’. It’s obviously impossible to deliver this vision with such great geographical concentration, particularly given the mismatch between the parts of the country with the worst health outcomes and the geographical location of much of NIHR’s research.

It’s good, therefore, to see in NIHR’s latest strategy document Best Research for Best Health: The Next Chapter, recognition that ‘people in regions and communities where the burden of need is greatest are often under-served by research’, and a commitment to ‘Bringing clinical and applied research to under-served regions and communities with major health needs’.

To achieve this will require the development of research capacity outside the Golden Triangle. It’s good, therefore, to see a commitment to ‘nurture new NHS and non-NHS research sites located in regions that have high health and social care needs and have historically been less active in research, introducing new initiatives to enhance their capacity and capabilities.’

It’s important that NIHR follows through on these welcome commitments; the UK’s health inequalities are, in my view, unacceptable in principle, but also a serious drag on the productivity of those regions where health outcomes are worst. The strengthening of existing and emerging clusters of life sciences and health technology industries outside the Greater Southeast will be an additional benefit.

6.4. Business, Energy and Industrial Strategy (excluding UKRI)

BEIS has the largest R&D budget of all departments, but this is because it is the official department sponsor for UK Research and Innovation, which I discussed in part 5 of this series. Nonetheless, it does have a significant R&D budget of its own, outside UKRI. In 2020, this amounted to just over £1 billion.

In part, this is used to support some important remaining components of state R&D infrastructure. The National Physical Laboratory is responsible for the standards and metrology that underpin commerce and industry, for example maintaining the national system for measuring and defining time accurately. The Met Office produces increasingly accurate weather forecasts, relying on the processing of massive amounts of data and high performance computing, and is increasingly concerned with modelling the effects of climate change. The UK Atomic Energy Authority, much shrunk in scale since the 1980s, is now exclusively concerned with research to develop nuclear fusion as a source of electricity. UKAEA is one of the few remaining parts of civil government that retains the capacity to undertake large scale, complex engineering projects at the frontiers of technology.

As its name suggests, BEIS is responsible for applied R&D in support of industrial strategy. Following the 2017 White Paper, the government established “sector deals” in support of specific sectors, often involving R&D programmes jointly funded by government and industry. The Aerospace sector deal is possibly the most mature, with the Aerospace Technology Institute established as the vehicle for that joint research programme. The future of the “sector deal” approach seems to be in doubt now; the 2017 Industrial Strategy was superseded in 2021 by a new, HM Treasury driven, Plan for Growth, which turned away from so-called “vertical” strategy focused on specific sectors. (discussed in my blogpost “What next for Industrial Strategy”).

BEIS took over responsibility for energy and climate change in 2016, when the formerly free standing Department of Energy and Climate Change was amalgamated with the department. Thus it inherited the DECC R&D budget, which at that time stood at £47 m. Given the scale of the challenge of moving to net zero, and the need for innovation to make what will be a wrenching economic transition affordable, this seems a small level of funding.

It’s worth stressing just how low the UK government’s spending on energy research fell in the 1990s. The low point, of just £30m, was in 2001. The scale of the collapse in state spending is made clear in my plot, which shows total government spending Research, development and demonstration as a fraction of GDP. The reasons for this fall are explored in an earlier post of mine, We sold out our energy future. In short, I suspect it arose from a combination of the complacency that arose from having discovered a large supply of oil and gas, and an ideological conviction that energy supply could and should be entirely left to the market.

UK government spending on energy research, development and demonstration as a faction of GDP. Data: International Energy Agency.

These totals include the UK Atomic Energy Authority’s spending on fusion research, together with more upstream research funded by the research councils (mainly EPSRC). It’s good that they are increasing again; the government now has a Net Zero Research and Innovation Framework
and a Net Zero Innovation Portfolio supporting the UK Government’s “Ten point plan for a green industrial revolution” (see my earlier blogpost for a more detailed analysis of this)

We’ll see how this plan develops.

Up next…

In the next (and, I hope, penultimate) part of this series, I’ll look at the EU Horizon programme (and what might replace it), and the new agency ARIA.

In the past, the UK government has funded R&D indirectly through the EU Horizon programme. Following Brexit, this is in question, despite the UK government’s stated desire to associate with Horizon in the future. I’ll discuss the distinctive roles of EU funding, and what might replace it in the increasingly likely scenario that the UK is not able to associate. Finally, I’ll mention the new agency ARIA (the Advanced Research and Innovation Agency), with some early thoughts about the role this might play in the overall system.

William: on The shifting sands of UK Government technology prioritisation
Douglas Robertson: on The shifting sands of UK Government technology prioritisation
Matt Cliffe: on When did the UK’s productivity slowdown begin?
Zelah: on What the UK should – and should not – do about semiconductors
Richard Jones: on “Science Superpower: the UK’s Global Science Strategy beyond Horizon Europe”