Basic Science and Technological Innovation: the linear model and its limits

Although we are unaware of this most of the time, our common sense about science is ingrained in certain myths about how research takes place and how scientific knowledge interacts with technology. One such myth is that basic science and applied science are researches of essentially different natures, another states that technology would be the result of the mere application of scientific knowledge. But have you ever wondered where these ideas came from and how they came to have such influence on our collective imaginary? And are the relationships between science and innovation really so simple?

In today’s post, we present the history of this model of the relationship between science and innovation, as well as the criticisms to which it has been subjected in recent decades.

Science, the Endless Frontier: Vannevar Bush and the linear model

At the end of 1944, months before the end of World War II, US President Franklin Roosevelt ordered a report presenting a perspective on the country’s peacetime scientific policy. The person responsible for the document, an engineer named Vannevar Bush, was someone especially well placed for the task: he had headed the federal government’s Office of Scientific Research and Development during the war, and played an important role in the development of innovations such as the atomic bomb.

Titled Science, the Endless Frontier, the text examined the relationships between basic research – a term coined by Bush – applied science, technological innovation, and development. Bush’s vision would become deeply influential in the postwar period, when the cultural impact of the atomic explosion and US protagonism in scientific research favored the circulation and legitimation of his ideas. His theorizing has greatly influenced the media and institutional discourses of various countries, becoming part of the social imaginary about science.

The report has two main theses, both with decisive implications for the debate on which science and technology policy should be adopted by countries:

The first one states that “basic research is performed without thought of practical ends.” According to this thesis, there is an essential opposition between the ends of basic science and those of applied science. While basic research is intended to broaden the understanding of the phenomena of a certain field without worrying about the applications of the knowledge generated, applied science turns to solving some concrete problem or demand of individuals or collectives. For Bush, approaching one implies moving away from the other, therefore a scientific endeavor can never aspire to be both, for “applied research invariably drives out pure”.

An illustration of the first thesis

The second thesis, known as the linear model, states that “basic research is the pacemaker of technological progress.” In this model, the main source of innovation is basic science, because by mapping the functioning of reality, it broadens the scope of what is technically possible. Then applied science makes such possibilities actual for some practical purpose, generating innovations. Finally, society systematically implements these solutions to increase its productive efficiency. Thus each stage would be successive and conditioned by the previous one.

An illustration of the linear model

Scientific research in practice

Despite the immense success Bush’s theses enjoyed during the Cold War, his assumptions became the target of much criticism at the end of the twentieth century. Science historians and economists of innovation have become skeptical of the effectiveness of these ideas in actually representing the empirical reality of scientific research, its relations to technological progress, and its effects on development. Let’s take a closer look at some of these objections.

In his book “Pasteur’s Quadrant”, political scientist Donald Stokes considers a number of historical case studies that demonstrate how advances in the history of science stem from research in which it is not possible to distinguish clearly between theoretical and practical ends throughout the research. The best known of these is Louis Pasteur, a biologist known for laying the groundwork on the later development of the pasteurization technique. His studies on the alcoholic fermentation of beet juice aimed both at increasing the productivity of the beet makers and at understanding the impact of the presence or absence of air on certain categories of microorganisms. Likewise, his findings contributed significantly to both the beet juice industry and the consolidation of theoretical microbiology in the 19th century.

Stokes points to several other examples of research contexts in which purposes would not be easily classifiable in either category, because epistemological concerns mingled with considerations of use and practical interests. The studies Kelvin sought at the same time to advance the understanding of the laws of thermodynamics and to favor the industrial domain of the British Empire. Research by nineteenth-century German chemists aimed at understanding the structure and fundamental properties of organic compounds as well as favoring the national aniline industry and, later, the pharmacological sector. The emergence of the geosciences has been partly inspired by concerns about possible natural disasters, and its contemporary research agenda is closely related to the socio-environmental effects of climate change caused by human action.

In the human sciences, too, great theoretical contributions are often informed by practical interests. Stokes cites the case of Keynesianism, which aimed both to reduce inequalities and to explain fundamental economic dynamics. He also mentions Caribbean economist Arthur Lewis, the first black person to win the Nobel Prize in economics, whose main scientific contribution was developed, in part, to favor the development of peripheral countries in the global economy. We can think of other examples: the impact of Michel Foucault’s research on the history of madness for antimanicomial struggles, the implications of Simone de Beauvoir’s reflections on women’s rights, the theoretical contributions and practical effects of Karl Marx’s work to the analysis of labor relations.

Is technological innovation applied science?

Another aspect of Bush’s approach that is often questioned is his second thesis, the linear model in which basic science is the main driver of technological advance. The work of science and technology historian Robert P. Muthaulf is often cited as a counterpoint to this idea. In his classic article ‘The Scientist and the’ Improver ‘of Technology’, he demonstrates that for most of history, technological innovation came not from scientists but from ‘enhancers’ of technology, individuals who knew little or nothing about science. More frequently, it is precisely the transfer of knowledge in the opposite direction that is observed, as Stokes reports in commenting on the work:

‘There was indeed a notable reverse flow, from technology to science, from the time of Bacon to the second industrial revolution, with scientists modeling successful technology but doing little to improve it. Multhaulf notes that the eighteenth-century physicists were “more often found endeavoring to explain the workings of some existing machine that suggesting improvements in it”. THis other-way-round influence is called the oldest type of interaction of science and technology by Thomas S. Kuhn, who notes that Johannes Kepler helped invent the calculus of variations by studying the dimensions of wine casks without being able to tell their makers how to improve their already optimal design – and that Sadi Carnot took an important step toward thermodynamics by studying steam engines but found that engineering practice had anticipated the prescriptions from the theory he worked out.’

Although the professionalization of engineering during the Second Industrial Revolution instituted an obviously greater role of science in technological development, this role does not correspond to the way it was theorized in the linear model. Economist Chris Freeman, coordinator of one of the most important studies on the subject – which evaluated 58 attempts at innovation in chemicals and scientific instruments in the twentieth century – notes that “[…] there remains in the modern science-related industries a strong reciprocal interaction between all these activities (Soete and Arundel, 1993) and in particular a powerful influence of technology upon science”.

In his influential paper titled “How exogenous is science?”, economist of innovation Nathan Rosenberg also criticizes Bush’s conception of science as exogenous to technology, analyzing the different ways in which technological development influences scientific progress. First, the high operating costs of science in the twentieth century often condition the continuity of a research agenda to the prior commercial success of some technology associated with it, and this innovation is often only partially explained by the science that supported its manufacture. Moreover, it is only through a long time of use that certain problems and aspects of a material (fracture, degradation, contamination, corrosion, etc.) become exploitable. Moreover, as the material is exposed to new environments, unobserved behaviors and related theoretical problems of unprecedented content arise.

Conclusion

As previously stated, the success that the linear model enjoyed during the Cold War period was related to the centrality of US science in this context, as well as to the cultural impact of the atomic bomb explosion in reinforcing the country’s epistemological authority on scientific policy. . The cultural strength of these premises does not, however, imply that they are consistent with empirical reality, only that they have successfully imposed themselves as the dominant ideology in our scientific imaginary. More recent reassessments of Bush’s theses have consistently demonstrated their misconceptions in characterizing both the reality of scientific research itself and the relationship between basic science and technological innovation.

This does not mean that we should abandon the notions of basic science or applied science, but recognizing that these concepts are just that: concepts, theoretical instruments that help us analyze and intervene on reality. As such, they can be questioned, reformulated and refined. Similarly, it is not a matter of disregarding the role of scientific knowledge in the innovative process, but of understanding the objective complexity of the relationships between them beyond the reductionism that the linear model establishes between science and technology. In this way we can produce more accurate analyzes and base more effective interventions on reality.

Interested in history of science and its relationships to the economics of innovation? Check out our post on how geoeconomic disputes are influencing innovations in artificial intelligence.

The views and opinions expressed in this article are those of the authors.
Illustration by Freepik