“It’s still difficult to conclusively say what really happened with many things, scientifically”
| Photo Credit: Getty Images/iStockphoto

Many of us want to know how the SARS-CoV-2 virus originated. To do that, right now we need to unravel its evolution from its bat coronavirus ancestor by sequencing the genomes of animals and viruses near the outbreak site and we need to effect China’s cooperation to check whether SARS-CoV-2 could have ‘leaked’ from a lab. Where the virus came from was once singularly important because the answer could have pointed the way to avoiding similar outbreaks in future. But today, there is good reason for this question to take the back seat.

We don’t know where or how the virus originated. If it did in a lab, we would have to re-examine how we regulate research facilities and their safeguards and the manner of political oversight that won’t curtail research freedom. If the virus is au naturel, we would have to institute and/or expand pathogen surveillance, eliminate wildlife trafficking, and improve social security measures to ensure populations can withstand outbreaks without becoming distressed. But even as these possibilities aren’t equally likely (according to scientists I trust), the origin of SARS-CoV-2 is less important than it once was because the COVID-19 pandemic caused us to implement all these outcomes to varying degrees.

SARS-CoV-2 isn’t special of course: it’s still difficult to conclusively say what really happened with many things, scientifically. In 1977, a telescope in the U.S. recorded a signal from outer space that remains strange to this day. We don’t have a physical explanation for the “spooky” result of an experiment Anton Zeilinger and co. conducted in 1998. We lack a complete understanding of how general anaesthesia works its magic on the brain. Not even their makers fully know how powerful AI models work the way they do. No existing theory of nature can say what happens in intervals shorter than 10^(-43) seconds.

In fact, not knowing is ubiquitous. To quote philosopher Nicholas Rescher, “no one can say in advance what questions natural science can and cannot answer.” But science communication has taught me not all of us can know everything unless we invest considerable, perhaps even impossible, resources. Years ago, the philosopher Daniel Sarewitz wrote an article that changed my relationship with science. He argued that while we may know about the Higgs boson particle and that it gives other elementary particles their masses, we can’t truly know any of this until we learn the complicated mathematics required to make sense of it. Until then, we just have faith in the physicists who know. This relationship goes for most technical information in our lives.

Science journalists like me communicate science by providing for scientists’ claims, to quote Rescher, “the backing of a rationale that renders [their] correctness evident”, but I still demand a considerable amount of faith from readers. At some point faith also becomes trust but trust still isn’t understanding. (This said, the system of sanctions should they err provides a reasonable backstop for trust in scientists’ and journalists’ work.) The general idea here is that you pick someone you trust and you believe what they say to be true. Let’s call this the social character of scientific knowledge.

When people encounter a weighty concept scientists aren’t able to explain fully, the social character becomes more apparent than it normally is. Some people trust impassioned scientists unwilling to consider extra-scientific possibilities. Some lean towards authority figures who don’t trust science to provide the answer. Historically, people have turned to faith in the face of the unknown. The problems arise when we don’t know, or choose to overlook, where science ends and faith/trust begins. Then we fixate on answers that may never matter at the expense of answers that are already useful.

mukunth.v@thehindu.co.in

The National Research Foundation (NRF) is a new research funding agency that the Union Cabinet recently approved. It has a budget of Rs 50,000 crore over five years and was set up to help boost research and innovation in India by providing more funding, streamlining the research funding process, and strengthening linkages between academia, industry, society, and government.

Following the announcement, there has been discussion among scientists around the kind of research that the NRF should fund such that the outcomes are innovative solutions to practical challenges. This is a difficult task due to an academic culture that is mainly directed by internal academic priorities and incentives, but not generally related to social problems and challenges.

Vannevar Bush’s argument

One prominent narrative on funding rationales is that the ‘relevance’ and/or the ‘utility’ of research work should not matter. This has been echoed in the NRF debate, with some commentators arguing that, since scientific advancements often arise unexpectedly, research shouldn’t be prescriptive or directed. Other experts have highlighted the importance of forging ties between academic scholars and other key players within the science, technology, and innovation (STI) system. This includes liaison with line ministries and the relevant industrial sectors right from the inception of the problem statement. Finally, a few experts have emphasised the importance of including societal stakeholders in thinking about both the issues and research pathways that STI should address.

The first argument rests on the unpredictable and accidental nature of many discoveries and contends that – in the words of Vannevar Bush’s 1945 advocacy paper ‘Science: The Endless Frontier’ – we ought to let “the free play of free intellects … dictated by their curiosity” drive innovation.

This linear, or pipeline, model assumes that new knowledge will automatically lead to new technology and innovation, fueling economic growth and addressing market gaps in knowledge creation. So the government should invest in scientific research because scientific breakthroughs will ‘naturally’ find their way into practical applications, via private sector innovation.

Many important technologies have benefited from discoveries driven by curiosity, including genome-sequencing, medical diagnostics, and several materials used in construction and various goods.

Daniel Sarewitz’s counterargument

But this argument has long been challenged. In his 2016 essay ‘Saving Science’, Arizona State University professor of science and society Daniel Sarewitz wrote that many key inventions in postwar U.S. were the product less of curiosity and more of the technological demands of the Department of Defense (DOD). Sarewitz contended that the DOD’s engagements with science illustrated that the “free play of free intellects” was not the main path followed in most instances of innovation.

The DOD provided critical investment and direction for fundamental research in diverse fields, from physics to molecular biology. Its investments influenced the rapid development of computers in the 1950s, and nurtured the growth of computer science as an academic discipline by funding research in institutions like the Massachusetts Institute of Technology and Stanford University.

This acceleration in turn paved the way for the World Wide Web, which later led – after similar guidance and material support from the U.S. National Science Foundation (NSF) – to companies like Google.

Revisiting the penicillin story

Even the narrative of the discovery of penicillin is less serendipitous than it is often depicted to be. In 1928, Alexander Fleming, a bacteriologist at St. Mary’s Hospital in London, unexpectedly observed that a mould, later identified as Penicillium notatum, had inhibited the growth of Staphylococcus, a bacterial genus responsible for ailments such as sore throat.

Fleming’s subsequent publication in the British Journal of Experimental Pathology in June 1929 only hinted at the potential therapeutic benefits of penicillin. Yet the actual substance was isolated by a team at the Sir William Dunn School of Pathology at the University of Oxford. Their target-driven endeavour from 1939, a decade after Fleming’s note, and subsequent industrial involvement in its production is what transformed penicillin into the life-saving drug it is today. Similarly, military foresight pushed for the first jet engines, which went on to transform civil and commercial aviation.

Many pieces of modern technology owe their existence to government-led innovations, as the economist Mariana Mazzucato has argued in her book The Entrepreneurial State (2011). This is to say that the ‘free play of intellects’ is a romantic notion that is not borne out in a closer reading of the history of science.

More realistic models of innovation

A new innovation model emerged in the 1980s called the ‘national innovation system’. This model is based on the idea that innovation to flourish a country needs fostering connections, promoting learning within systems, and empowering entrepreneurship. Countries like Japan and South Korea owe their innovation-led economic growth to the successful implementation of an interconnected innovation system, e.g. between automobiles companies and part suppliers, even though their basic science was not particularly strong in the 1970s-80s.

In the STI domain, these two frameworks to support and science have historically governed the policy discourses of funding agencies worldwide: the pipeline model rooted in the post-war era, emphasising the role of basic research and assuming automatic translation to innovation and economic growth, and the techno-nationalist system from the 1980s, focused on building interconnectedness among universities, research institutes, companies and governments.

Now, a third innovation model, focusing on transformative change towards sustainability is emerging: there is consensus across countries spanning various levels of economic development that STI shouldn’t only foster growth, but that it also needs to transform society to make it environmentally and socially sustainable. To achieve this, citizen science and stakeholders participation help in informing science regarding the types of knowledge that can transform society towards sustainability.

Wind power in Denmark offers an example of the third model. In the face of the energy crises of the 1970s, Denmark’s grassroots environmental movement created local cooperatives and small firms that experimented with wind turbines, with support from national technological institutes and policies (feed-in tariffs). This coalition eventually led Denmark to become one of the leading exporters of wind-turbines, contributing to its transition to green energy. 

Historically, research funding by Indian agencies has preferred the pipeline model, allowing ‘free intellects’ to guide national progress in STI. The formation of the NRF now gives the country the opportunity to revisit its STI policies. While support to basic research is always an important part of the science policy-mix, there is now the opportunity to revisit our affiliation with the pipeline model and chart the way towards the newer models of innovation. These emphasise the importance of creativity led by social challenges and stakeholder participation  to achieve transformative innovation towards a more just and sustainable future.

Moumita Koley is an STI Policy Researcher, DST-CPR, IISc, and Consultant, International Science Council. Ismael Rafols is a senior researcher at CWTS University Leiden and UNESCO Chair on Diversity and Inclusion in Global Science.