Science and innovation for development: a cultural movement
Some fifty five years after John Ziman launched the discussion on Public Knowledge and forty five years after his work on Reliable Knowledge , to appreciate the significance of scientific knowledge one must understand the nature of science as a complex whole. In Real Science , we are reminded that “science is social”, referring to “the whole network of social and epistemic practices where scientific beliefs actually emerge and are sustained”.
Overall, because science- and technology-based innovation is a socio-cultural process, science and innovation for development is best served when we understand the importance of tradition (including ancestral knowledge), as well as of critical links across communities in the creation of new innovative practices. Therefore, there is much to believe from the study of past experiences about the role of economic and social conditions in contributing to the success of technical innovations and diffusion of new technologies in developing societies. Many new technologies result from the reuse of old innovations in new contexts. Thus, we shall stress the importance of historical and cultural backgrounds, as a source of guidance and inspiration for innovation.
Joseph Henrich (2016)  , among others, have clarified that the “secret of our species´ success resides not in the power of our individual minds, but in the collective brains of our communities. Our collective brains arise from the synthesis of our cultural and social natures – form the fact that we readly learn from others (are cultural) and can, with the right norms, live in large and widely interconnected groups (are social)”. He shows that larger and more interconnect societies produce more “know-how” and that “the challenge has always been how to pevent communities from fragmenting and social networks from dissolving”.
It is under this context that K4P Alliances aim to foster a cultural movement based on collaborative innovation and a trans-disciplinary approach that joins people at large and citizens at local levels with scientists and engineers, as well as with artists, historians, social scientists and other academics; researchers with entrepreneurs and professionals, and students with experienced academicians in a range of research and teaching initiatives on the interface between theoretical analysis and hands-on practices.
Understanding humans as “cultural species” and their collective development as a “cultural process” require understanding the social norms under which different societies evolve. It requires, above all, understanding that science and innovation for development depend on the ability to encourage people and institutions to produce and difuse ideas, insights and practices in every sinngle region (Joseph Henrich, 2016).
In addition, it should be recognized that the potential new opportunities for science and innovation for development in the increasing digital era are associated with the ability to create scalable environments for learning that engages the tacit and the explicit dimensions of knowledge. The term that Brown and Douglas (2010)  have used for this, borrowed from Michael Polanyi is “indwelling”. Understanding this notion requires to connect experience, embodiment, and learning:
- First, the world is increasingly characterized by a sense of constant change, which demands rethinking the notions of interaction with new knowledge towards a deeper understanding of participation (“knowing”);
- Second, the notion of experience (and participation) within new media contexts has shifted from a traditional sense of experiencing content to using content as context to construct a social world with others (“making”);
- Third, understanding the means by which networked media supports a kind of play that allows people to navigate the complexities of a constantly shifting world (“playing”).
What may be most important to understand is that each of these dimensions of learning is in the process of evolving in response to societal demands . In our societies, knowing, making, and playing emerge as critical components of “becoming”. In relation to this, the development of local capacities to foster learning (including by students) requires training of a robust and flexible teaching body that can be easily adapted to satisfy changing contextual and learning requirements while making use of new technological opportunities .
The implications for many regions and developing countries is the need to give constant priority to people and knowledge in a way that provides networks of institutions with the necessary critical mass to foster adequate learning paths. A particular attention is to be given to Sub-Saharan Africa, as the world´s youngest region, with 60% of its population under the age of 25. By 2030, the continent´s working age population is set to increase by two thirds, from about 370 million adults in 2010 to over 600 million in 2030 .
In addition, that priority needs to be driven by endogenous sources. In other words, it requires understanding local mechanisms and policies that may drive endogenous growth of knowledge networks and related sources of social, cultural and economic support. Following Joseph Ki-Zerbo , a well-known African historian, it requires the adequate lightning of the historical path of each region, as well as the full responsibilities of local actors. In the specific case of Africa, it certainly requires a major task force to set knowledge networks that will consider the endogenous development of local institutions and gradually reverse the long-term process of brain drain affecting the full continent for many centuries .
Recent literature also suggests that learning how to manage uncertainty is necessary, including forms of institutional corruption. This has also become part of the main challenges facing adequate instituional frameworks promoting science and innovation for development. In this sense, “illities” represent a movement of “rupture”, emphasizing forms of thinking and action that go beyond the immediate temporal frame, apparent functionality or success, and the constraint to fundament decisions solely on what is measurable .
Inspired and conditioned by a myriad of global, national and local challenges that implicitly or explicitly rely on knowledge and learning for potential solutions, institutions are required to be both increasingly adaptable and resilient (two important illities). Thus, institutions at large have to consider accommodating new configurations of knowledge production by establishing alliances with an increasingly large range of “knowledgeable” institutions . Moreover, they require to secure a sufficiently stable environment to train and supply talented people, including researchers, for that growing range of “knowledgeable” institutions. This leads to the need, more relevant than ever, for public policies promoting effective institutional autonomy and integrity (i.e., two other important illities) of modern institutional frameworks. This is particularly relevant as institutional partnerships gain significant prominence.
In order to achieve this goal, the projects to be considered under K4P Alliances will emphasize the need and scope for improving the learning capabilities of young adults in ways that foster socio-economic resilience through better integrating social and human values in technical education, in a society increasingly dependent on technology and knowledge.
Knowledge networks and their inherent complexity relate to interactions between people and organizations, which influence economic development and political relationships . This resides increasingly in the capacity to access and use knowledge and technologies in distributed knowledge bases, which are increasingly spread through a wide network of sources . It is under this context that democratizing higher education maybe used as a catalyzer of knowledge-based developments, by promoting the exposure of emerging societies to experts and other communities aimed to foster processes of inclusive development.
The issue is certainly how far we all take advantage of opportunities that arise with the increasingly dynamic and globally distributed geography of innovation, as well as how it fosters a new global order and help others to use similar advantages at local levels.
This is because one must take up the challenge of probing deeper into the relationships between knowledge and the development of our societies at a global scale. Our inspiration comes from, among others, the seminal work of Lundvall and Johnson , who challenge the commonplace by introducing the simple, but powerful, idea of learning. Lundvall and Johnson speak of a “learning economy”, not of a “knowledge economy”. The fundamental difference is to do with a dynamic perspective. In their view, some knowledge does indeed become more important, but some also becomes less important. There is both knowledge creation and knowledge destruction. By forcing us to look at the process, rather than the mere accumulation of knowledge, they add a dimension that makes the discussion more complex and more uncertain, but also more interesting and intellectually fertile in an international context .
The richness of the concept of the learning economy has been demonstrated in recent decades throughout the world, by both leading scholars and policy makers. It has been addressed in the Global South. For example, MGK Menon, former Indian Minister of S&T wrote about the conditions necessary for innovation to thrive, which require specific local action through a process of “communitization”.
This closely follows the lessons Eric von Hippel, a well-known professor at MIT, has provided based on the American experience that user-centered innovation is a powerful and general phenomenon . It is based on the fact that users of products and services - both firms and individual consumers - are increasingly able to innovate for themselves. It is clear that this is growing rapidly due to continuing advances in computing and communication technologies and is becoming both an important rival to and an important feedstock for manufacturer-centered innovation in many fields .
Eric von Hippel has also shown that the trend toward democratization of innovation applies to information products such as software and also to physical products, and is being driven by two related technical trends: first, the steadily improving design capabilities (i.e., innovation toolkits) that advances in computer hardware and software give to users; and second, the steadily improving ability of individual users to combine and coordinate their innovation-related efforts via new communication media such as the Internet.
In other words, beyond suitable technical infrastructure, the process of “democratization of innovation” at a global scale requires people with the ability to engage in knowledge-based networks without borders. It is about people and knowledge beyond national borders, and this constant interaction has gained particular importance in recent years .
It is clear that the emerging patterns of innovation require new perspectives for public policies, which in the US and other developed countries have in the past relied on supporting manufacturers and their intellectual property. Certainly, we need to move on from those days and consider better ways to integrate policies for the Global South, as well as to diversify them at a global scale to better consider “win-all” approaches. A potential way to achieve this is to avoid overemphasizing current rival sectors and competitive strategies, but rather to look at science, education and innovation policies towards new challenges that require a strong collaborative approach across disciplines and among different and diversified institutions.
The question that does arise is how far can we help transforming R&D and human capital into productivity gains everywhere and, in particular, in the Global South?
It is not a trivial matter to understand the processes that enable investments in R&D and human capital to be transformed into productivity gains everywhere, at a global scale. Actually, there is a widespread view among economists in many world regions that this kind of investment is too costly for the economic efficiency gains it provides.
This however is a too naïve and superficial approach. Viewed from a wider perspective, in the longer-term R&D and human capital investments do matter and are probably the most important factor in explaining economic growth. However, the naïve view has a point: the transition of human capital to growth is not automatic. Specific policies and actions are needed to make this transition happen successfully.
As mentioned above, this challenge is particularly true in what concerns small and transition economies worldwide and, above all, developing countries without knowledge-intensive critical masses.
 J. Ziman (1968), Public Knowledge: The Social Dimension of Science, Cambridge University Press.
 J. Ziman (1978), Reliable Knowledge: an exploration of the grounds for belief in science, Cambridge University Press.
 J. Ziman (2000), Real Science: What it is, and what it means, Cambridge University Press.
 J. Henrich (2016), “The secret of our success: how culture is driving human evolution, domesticating our species, and making us smarter”, Princeton University Press.
 Brown, J. S. and Douglas, T. (2010), A New Culture of Learning: Cultivating the Imagination for a World of Constant Change, CreateSpace 2011.
 Polanyi, M. (1958), “Personal Knowledge. Towards a post-critical philosophy”, Routledge & K. Paul. See also, M. Polanyi (1939), The rights and duties of Science, Contempt of Freedom; M. Polanyi (1962), The Republic of Science, Minerva; M. Polanyi (1966), The Tacit Dimension, Doubleday.
 Thomas, D. and Brown, J.S. (2011), A New Culture of Learning – cultivating imagination for a world of constant change, Authors edition.
 Bellanca, J. and Brandt, R. (2010), 21st century skills – rethinking how students learn, Solution Tree Press, Bloomington.
 See, for example, WEF (2017), “The future of jobs and skills in Africa – preparing the region for the fourth industrial revolution”, World Economic Forum, 2017. Also, https://skillsafrica.org/ .
 Joseph Ki-Zerbo (2003), “À quando l´Àfrique: entertien avec René Holestein”, Paris, Édition de l’Aube, Collection Essai.
 Ki-Zerbo, Joseph (1990), “Éduquer ou périr”, Paris, L’Harmattan.
 Rouse, W. and Serban, N. (2014), Understanding and Managing the Complexity of Healthcare, Cambridge: MIT Press.
 Nowotny, H., Scott, P., and Gibbons, M. (2001) Rethinking science: knowledge in an age of uncertainty, Cambridge: Polity.
 Hidalgo, C.A. and Hausmann, R. (2009), ‘The building blocks of economic complexity’, Proceedings of the National Academy of Sciences of the United States of America, vol. 106, no. 26, pp. 10570-10575.
 Conceição, P., Heitor, M. and Veloso, F. (2003), ‘Infrastructures, Incentives and Institutions: fostering distributed knowledge bases for the Learning Society’, Technology Forecasting and Social Change, vol. 70, no. 7, pp. 583-617.
 B.-Å. Lundvall and B. Johnson (1994), “The Learning Economy”, Journal of Industry Studies, 1/2: 23-42.
 Lundvall, B.A: (2011), “The Changing Global Knowledge Landscape and the Need for a Transatlantic Vision and a New Pragmatism”, Aalborg University.
 von Hippel, Eric (1988) The Sources of Innovation (New York: Oxford University Press).
 Harhoff, Dietmar, Joachim Henkel and Eric von Hippel (2003) “Profiting from voluntary information spillovers: How users benefit from freely revealing their innovations,” Research Policy vol 32, No.10 (December) pp.1753-1769.
 Gault, Fred & Eric von Hippel, 2009, The Prevalence of User Innovation and Free Innovation Transfers: Implications for Statistical Indicators and Innovation Policy, MIT Sloan School of Management Working Chapter no. 4722-09, Cambridge, MA: MIT. pp. 29.