The public funding system for science in the UK is currently going through a major transition. It’s moving from a predominantly discipline-based way of organising funding, to a new threefold categorisation. Lord Vallance’s “three buckets” distinguish between discovery and curiosity-driven research, strategic government and societal priorities, and supporting innovative companies to start, scale and stay in the UK.
Last week, the government department overseeing most of the science budget, the Department of Science, Innovation and Technology, was abolished. Responsibility for science funding has been transferred to an expanded Department of Business and Trade (now the Department of Business, Innovation, Science and Trade) – one motivation for this must be to make a stronger link between the priorities for science funding and the government’s industrial strategy.
Does this mean, as some fear, that we’re seeing a systematic shift from pure science to applied science? There’s certainly more pressure to demonstrate outcomes from the R&D the government supports. The political consensus in support of science funding is crumbling in the face of continuing economic stagnation and fractious politics, and in an earlier piece I’ve argued that UK science must deliver on its promise of economic growth.
But we should take a deeper look at the underlying assumption here, that science is very different from technology, and that it makes sense to distinguish between pure science and applied science. The idea of a one-way trajectory, with applied science emerging from pure science, and then being translated into technology is seductive, but misleading. In this view, pure science is the seed corn from which future technologies emerge – but this neglects the way that technology itself can seed new fundamental discoveries.
We focus a lot on the effectiveness – or lack of it – of our system for translating fundamental science into new, economically valuable technologies. But maybe we should think more about the process of reverse translation – the way in which new science can arise from developments in technology. In the postwar world, it was in the great corporate laboratories, like Bell Labs and IBM, and, in the UK, ICI and GEC, that this reverse translation happened. This relied on having those industrial laboratories employing outstanding researchers working on basic science, alongside more applied scientists and technologists. But that world has largely gone, leaving a giant gap in the institutional R&D landscape. That gap needs to be filled.
The entangled history of science and technology
Historians of science tell us that the origin of the distinction between science and technology goes back to the ancient Greeks. They distinguished between episteme, which is probably best translated as natural philosophy, and techne, translated as craft. Our word technology derives from techne, but careful scholars remind us that technology actually refers to writing about craft, rather than doing the craft itself. They would prefer to call the actual business of making machines and gadgets technique (in the same way as the Germans call it technik), rather than technology. Of course, for a long time nobody wrote about technique at all, so there was in this literal sense no technology. Craft skills were regarded as secrets, to be handed down in person from master to apprentice, who were from a lower social class than the literate philosophers considering more weighty questions about the nature of reality.
The sixteenth century saw some light being thrown on the mysteries of technique with books (often beautifully illustrated) being published about topic like machines and metal mining. But one could argue that the biggest change came with the development of what was called then experimental philosophy, which we see now as being the beginnings of modern science. The experimental philosophers certainly had to engage with craftsman and instrument makers to do their experiments, but what was perhaps more important was the need to commit the experimental details to writing so that their counterparts and correspondents elsewhere in the country or elsewhere in Europe could reliably replicate the experiments. Complex pieces of scientific apparatus, like Robert Boyle’s air-pump, certainly were some of the most advanced (and expensive) pieces of technology of the day. And, conversely, it’s no accident that James Watt, who more than anyone else made the industrial revolution possible with his improved steam engine, learned his engineering as an instrument maker at the University of Glasgow.
But surely there’s a difference between making a piece of experimental apparatus to help unravel the ultimate nature of reality, and making an engine to pump a mine out? In this view, the aim of science is to understand the ultimate fundamental nature of reality, while technology seeks merely to alter the world in some way, with its success being judged simply by whether it does its intended job. In actuality, the aspect of science as natural philosophy, with its claims to deep understanding of reality, has always coexisted with a much more instrumental type of science whose success is judged by the power over nature it gives us (Peter Dear’s book The Intelligibility of Nature is a fascinating reflection on the history of this dual character of science). Even the keenest defenders of science’s claim to make reliable truth-claims about the ultimate nature of reality – often resort to entirely instrumental arguments – “if you’re so sceptical about science”, they’ll ask a relativist or social constructionist, “why do you fly in airplanes or use antibiotics?”
It’s certainly true that different branches of science are, to a different degree, applicable to practical problems. But which science is an applied science and which is a pure science depends as much on what problems society, at a particular time and in a particular place, needs solving, as on the character of the science itself. In the sixteenth and seventeenth centuries astronomy was a strategic subject of huge importance to the growing naval powers of the time, and was one of the first recipients of large scale state funding. The late nineteenth and early twentieth centuries were the heyday of chemistry, with new discoveries in explosives, dyes and fertilizers making fortunes and transforming the world only a few years after their discoveries in the laboratory. A contrarian might even be tempted to say “a pure science is an applied science that has outlived its usefulness”.
Another way of seeing the problems of a supposed divide between pure science, applied science and technology is to ask what it is that scientists actually do in their working lives. A scientist building a detector for CERN or writing an image analysis program for some radio astronomy data may be doing the purest of pure science in terms of their goals – understanding particle physics or the distant universe – but what they’re actually doing day to day will look very similar indeed to their applied scientist counterparts designing medical imaging hardware or software for interpreting CCTV footage for the police. Of course, this is the origin of the argument that we should support pure science for the spin-offs it produces (such as the World Wide Web, as the particle physicists continually remind us). A counter-argument would say, why not simply get these scientists to work on medical imaging (say) in the first place, rather than trying to look for practical applications for the technologies they develop in support of their “pure” science? Possible answers to this might point to the fact that the brightest people are motivated to solve deep problems in a way that might not apply to more immediately practical issues, or that our economic system doesn’t provide reliable returns for the most advanced technology developed on a speculative basis.
Vannevar Bush and The Endless Frontier
If it was ever possible to think that pure science could exist as a separate province from the grubby world of application, like Hesse’s “The Glass Bead Game”, that illusion was shattered in the second world war. The purest of physicists delivered radar and the fission bomb, and in the cold war we emerged into it seemed that the final destiny of the world was going to be decided by the atomic physicists. In the west, the implications of this for science policy was set out by Vannevar Bush. Bush, an engineer and perhaps the pre-eminent science administrator of the war, set out the framework for government funding of science in the USA in his report “Science: the endless frontier”.
Bush’s report emphasised, not “pure” research, but “basic” research. The distinction between basic research and applied research was not to be understood in terms of whether it was useful or not, but in terms of the motivations of the people doing it. “Basic research is performed without thought of practical ends” – but those practical ends do, nonetheless, follow (albeit unpredictably), and it’s the job of applied research to fill in the gaps. It had in the past been possible for a country to make technological progress without generating its own basic science (as the USA did in the 19th century) but, Bush asserted, the modern situation was different, and “A nation which depends upon others for its new basic scientific knowledge will be slow in its industrial progress and weak in its competitive position in world trade”.
Bush thus left us with three ideas that form the core of the postwar consensus on science policy. The first was that basic research should be carried out in isolation from thoughts of potential use – that it should result from ” the free play of free intellects, working on subjects of their own choice, in the manner dictated by their curiosity for exploration of the unknown”. The second was that, even though the scientists who produced this basic knowledge weren’t motivated by practical applications, these applications would follow, by a process in which potential applications were picked out and developed by applied scientists, and then converted into new products and processes by engineers and technologists. This one-way flow of ideas from science into application is what innovation theorists call the linear model of innovation. Bush’s third assertion was that a country that invested in basic science would recoup that investment through capturing the rewards from new technologies.
Pasteur’s quadrant, and beyond
All three of these assertions have subsequently been extensively criticised, though the basic picture has a persistent hold on our thinking about science. One influential critique came in a book by Donald Stokes called Pasteur’s quadrant. Stokes argued from history that the separation of basic research from thoughts of potential use often didn’t happen; his key example was Louis Pasteur, who created a new field of microbiology in his quest to understand the spoilage of milk and the fermentation of wine. Rather than thinking about a linear continuum between basic and applied research, he thought in terms of two dimensions – the degree to which research was motivated by a quest for fundamental understanding, and the degree to which it was motivated by applications. Some research was driven solely by the quest for understanding, typified by Bohr, while an engineer like Edison typified a search for practical results untainted by any deeper curiosity. But, the example of Pasteur showed us that the two motivations could coexist. He suggested that research in this “Pasteur’s quadrant” – use-inspired basic research – should be a priority for public support.
This line of argument was elaborated and extended by Venkatesh Narayanamurti and Jeffrey Tsao, in their book The Genesis of Technoscientific Revolutions: Rethinking the Nature and Nurture of Research and a subsequent paper: How technoscientific knowledge advances: A Bell-Labs-inspired architecture.
Like Stokes, Narayanamurti and Tsao distinguish between pure science, motivated entirely by scientific problems, as exemplified by Bohr, and technological progress carried out in an entirely empirical way, as exemplified by Edison. But they go on to pick apart the interaction between scientific advances and technological progress in much more detail and specificity.
One example of technological progress arising from scientific curiosity is provided by the discovery of the maser and laser by Charles Townes. For a long time, this was famously described as “a solution looking for a problem” – but now, lasers are among the most ubiquitous and important technological devices, underpinning modern communications in a way that was unimaginable when the initial discoveries were made.
But the story of the interplay between science and technology is usually more complicated than that. For Narayanamurti and Tsao, the missing ingredient is reverse translation – the identification of new scientific problems, and subsequent scientific progress, from the needs of advanced technologies. This scientific progress can, in turn, be translated into new technology, leading to a virtuous cycle of tightly coupled scientific discovery and technological advance.
The heyday, and subsequent demise, of the great corporate laboratories
The exemplary institution for this coupling of scientific discovery and technological advance was Bell Laboratories, in its heyday between the 1930s and 1980s. It’s no exaggeration to say that much of the technology of the modern world was invented at Bell, from transistors, the photovoltaic cell and the laser, to UNIX and the foundations of cryptography. But in addition to these technological advances, Bell Labs produced many foundational scientific discoveries, many of which won their discoverers Nobel Prizes.
To give just a few examples, the field of radio astronomy was founded by Karl Jansky; this followed his investigation of the source of static noise on the transatlantic radio-telephone. A few years later, Penzias and Wilson discovered the cosmic microwave background, using a piece of equipment built for early satellite communication trials. More recently the fractional quantum Hall effect was discovered by Störmer and Tsui, as a side-effect of their work on ultra-high mobility transistors, and explained theoretically by Robert Laughlin in terms of fractionally charged quasi-particles arising in strongly correlated systems.
Narayanamurti and Tsao focus in some detail on what made Bell Labs so effective at coupling scientific discovery and technological advance, unsurprisingly given that Narayanamurti worked at Bell for nearly 20 years, holding senior positions. But Bell Labs was by no means the only US corporate laboratory where important scientific discoveries were made. The General Electric laboratory, founded in 1900, was where Irving Langmuir carried out the work in surface chemistry that won him a Nobel prize. More recently, the laboratories of IBM produced Nobel prizes for the discovery of the scanning tunnelling microscope and high temperature superconductivity.
Nor was this coupling of scientific discovery and technological advance a purely American phenomenon. The devices in which the original (integral) quantum Hall effect was observed were made in the corporate laboratories of the UK electronics firm GEC, and many consider that their maker, Mike Pepper, was unlucky not to share Klaus von Klitzing’s Nobel Prize for this discovery.
Much less well known is the role of the Leeds-based Wool Industry Research Association in creating the foundations of molecular biology, through their support of the work of William Astbury, a pioneer in applying x-ray diffraction in structural studies of proteins and DNA, as described in this piece by Tom Forth.
In my own field of polymer physics, I would highlight the crucial role of Geoffrey Gee, in the British Rubber Producers Research Association, and Geoffrey Allen, who held a joint appointment between Manchester University and ICI’s corporate research lab at Runcorn, in developing the statistical mechanical foundations of polymer physics. Perhaps even more importantly, they were able to persuade the great theoretical physicist Sam Edwards, then based at Manchester University, to take an interest in the subject, leading to his huge contributions to the theory of disordered systems, including theory of rubbers, the replica method, spin-glasses, and the Doi-Edwards theory of polymer viscoelasticity.
This world has gone. Private corporations still carry out research and development, and this does sometimes lead to important fundamental discoveries (DeepMind’s AlphaFold programme being a significant recent example). But the sense that the great industrial labs of the postwar era are either no longer in existence, or much reduced in their scientific impact, is backed up by a quantitative study by Arish Aurora and coworkers – The decline of science in corporate R&D
https://ueaeprints.uea.ac.uk/id/eprint/65090/1/Accepted_manuscript.pdf – showing a significant decline in the number of publications produced by corporations between 1980 and 2006, with the biggest decline happening for the most high impact papers.
What’s the cause of this decline? The nature of the forms of capitalism prevalent in the USA, UK and Europe have made corporations believe that supporting fundamental science is a luxury they can no longer afford. In the case of Bell Labs, there was a very specific trigger for the decline – the breakup of the Bell System in 1984. This meant the end of the monopoly rents that, in effect, supported the less directly applicable work of the laboratory.
More widely, the movement to shareholder capitalism led to a tendency to short-termism and financialisation, perhaps most visibly in the tenure of Jack Welch at General Electric. In the UK, both GEC and ICI succumbed to ill-advised and poorly timed merger and divestiture activity. I’ve mentioned two of the Industrial Research Associations, founded from the 1920s on as laboratories funded by a combination of contributions from industry and a contribution from the state. These are a much-neglected feature of the UK innovation landscape; they didn’t survive the decision of the Thatcher government to withdraw their state funding contribution, as part of a wider withdrawal by the government from applied research.
Can we create a new Bell Labs?
What have we lost by the withdrawal of corporate laboratories from basic science? There is a danger that science, isolated from the demands of technology and the new problems that produces, becomes self-referential, an echo-chamber. Dan Sarewitz made this case very forcefully in his piece Saving Science, arguing “that’s why the symbiosis between science and technology is so powerful: the technology provides focus and discipline for the science.” A related argument is that the kind of science that is inspired by the demands of technology is more likely, in turn, to translate into new technologies, precisely because of its adjacency to existing technologies.
Another danger arises when academic scientists respond to pressure to change their research direction in more applied directions, but don’t have enough knowledge of the current state of existing technologies and the markets they serve. The risk then is that we end up supporting research that’s neither fundamentally important nor practically useful. The influence of basic scientists working in industry on their academic colleagues is important in avoiding this pitfall. This influence is exerted both formally, through their participation in funding allocation systems, and informally, through their participation in the scientific community, so the diminishing pool of such scientists in industry has a negative effect on science more widely.
If we accept that we have lost something from this change, what can we do about it? How can we encourage more basic research to be carried out in close proximity to the problem-rich environment of a technology intensive company? How can we build institutions that create more porosity, more interaction between science progress and technological advance?
I think a starting point is to have a greater recognition of the importance of building stuff and making things – scientific equipment, software tools, new devices, new materials. We need to find different ways of recognising the social value of research carried out in a corporate environment, beyond the value that can be captured by the firm, perhaps through new kinds of public/private partnerships.
Finally, in the UK, we have a specific problem, of not having enough technology-intensive companies operating at scale, that would be in a position to host such partnerships. That is another, very important, discussion, that I will return to.