Mining the Minds of Masses : Open Innovation Models

 

There has been an upsurge of attempts by media, corporations and even  public agencies to learn from . the ordinary minds on the streets. Of course, such efforts are not evenly distributed across sectors, regions or nations, and even social segments. Rising interest in open innovation models among researchers among public or private  learning communities, bring to light the limits of our formal R and D systems and their inability to generate new ideas and innovations. What is of greater significance to us is that knowledge, innovations and ideas of common people, which remained on the margin of social thinking and intellectual discourse for so long, despite Honey Bee network’s two decades of persistent efforts, are gradually becoming focus of attention.

Let me explain the how and why of this new, yet welcome change.  When we started learning from grassroots innovators and traditional knowledge holders way back in 1980 and more thoroughly in 1984 that was the post green revolution era when the country was  benefitting from the gains in productivity. Then the  ‘lab to land’, and formal R and D systems were the key drivers of change in formal corporations and public systems. For another decade, this thrust continued unquestioned. But the last decade witnessed a  growing awareness of grassroots or user driven innovations.

It may be because large number of western pharma companies did not have any major drugs in the pipeline. Even patents on the earlier block buster drugs were expiring, hence corporate R and D ceased to be the major driver of innovations in engineering majors too. Even in public systems, the R & D was no more considered equal to innovation. The very basic framework of National Innovation Systems including only academic, corporate (public or private) R and D and any other formal R and D system began to be questioned. The concepts of crowd sourcing, mass sourcing and such other means of learning from common people started being mainstreamed. It did however, generate the basic questions: hy was the world so keen to learn from common people? Why should the impeccable faith of the global leaders in the ability of institutional experts to solve social or market related problems get diluted?

There is another aspect of this transformation of mindsets:Schumpeter’s  thrust on innovations in 1934 was preceded by Asian civilizational search for local solutions for local problems in the first century BC and sixth century AD in China.  Likewise in India, collation, pooling and in some cases codification of popular perceptions, experiences and beliefs was limited to coping with different kinds of stresses in agriculture, animal or human health through ayurvedic texts.

Traditions of open source

But these beliefs were either used as open source knowledge, often not subjected to rigourous trials; or as codified classical knowledge accessible to the conventionally qualified traditional experts. The fact that many of these practices still hold true and valid, testifies to  their repeated validation in the ‘Laboratories of Life’ as Dr Mashelkar puts it. However, with the advent of more formal systems of scientific mode of systematization of knowledge after renaissance in Europe five hundred years ago, a particular lexicon became more and more institutionalized. The lexicon of science aimed at creating a universal language thus enabling accumulation of global knowledge. There were no two standards of science- eastern and western in this philosophy. If alternate boiling and cooling of milk by common people led to its longer storage life due to the killing of bacteria, then it was a valid scientific concept all over the world. Just because the explanation of its causality was often missing, or at least not articulated in a language which was universally understood and agreed upon, it does not lose its validity. The technology evolved in east and its scientific label in the form of pasteurization  evolved in the west. Grandmothers knew what were the ways of enhancing the shelf life of  milk even longer than few days without refrigerators through periodic boiling (or in the case of pulses and grains, periodic sunning). They may not have standardized questions like which grain, how much duration, what interval of sunning and for what duration, and leading to how much shelf life etc., but the  knowledge existed.

Technology preceding  science

There are numerous such instances of technologies preceding the evolution of science. We knew how to build houses, before science of architecture evolved. Likewise, we knew how to make pickles, or  store food or seed for longer duration before the microbiological basis of contamination and its control through solarization or other means evolved. One can add numerous examples of this kind recounted by scholars all over the world. But then there was one specific feature of such pursuits which prevented knowledge of this kind triggering market based entrepreneurial growth. This was the open source nature of such knowledge systems. People generally did not keep such techniques as secret. They let others build upon their insights.

Categorization of  knowledge

It must be however, added that evolution and diffusion, or at least acknowledgement of such knowledge across social or cultural boundaries was problematic not just in eastern societies, but also in western societies. Knowledge produced by certain disadvantaged social segments such as low caste leather workers, or women, or tribals was not recognized and subjected to scientific respect for a long time ( and in the case of much of ethnobiology, it is still appropriated without acknowledgement and reciprocity). It was taken advantage of, but without due respect, recognition or reward. Autumn Stanley in her much neglected book viz., “Mothers and Daughters of  Invention” showed after studying history of patents for  two hundred years in USA, the share of women reached  just two percent in the eighties, rising to about eight percent in late eighties. In India, similar disenfranchisement of certain kind of knowledge for women and lower social castes was attempted/advised in certain popular religious or cultural texts. Women got voting rights in Switzerland only in sixties, much after India gave such rights to them.

Openness of the open  systems

Open knowledge systems did not mean complete openness of institutions, or culture, or even skills, or technologies. Women were culturally prohibited in India from ploughing land, or using blacksmithy or carpentry tools (exception apart). Thus, even if they had ideas about solving their problems, they could not implement them adequately (an issue we will revert to in later issues of Honey Bee Network in greater detail). But the fact remains that a lot of knowledge about child care and food processing, home gardening, knitting and weaving etc., was produced, reproduced among women often as open source exchange system. The tragic part is that somewhere along the way, the taboos came to be exercised against certain healthy and wise practices. The open source knowledge system is not a panacea against such taboos and socially and scientifically regressive practices (such as not feeding mother’s milk to new born child within two hours and first day in many economically developed parts of the country).

Accessing mass produced knowledge

Having said this, we can see that while culture of keeping knowledge as open source gave tremendous impetus to production and validation of robust knowledge for human survival, there were exceptions too. Despite these limitations, the vibrancy of distributed grassroots production and reproduction of knowledge has led to a large number of initiatives that have been known as crowd sourcing, mass sourcing, open source or free and open source etc. A few months ago, Dy. Editor of Forbes, the magazine of the rich and powerful, wrote to us and discussed the idea of using Honey Bee Network approach of learning from common people for crowd sourcing the content of their January, 2011 issue. Using Shri Saidullah’s innovation of amphibious cycle as an illustration of how it could help solve problems worldwide (such as providing relief in floods in Pakistan at that time), she and other colleagues created a new journalistic tradition and invited  readers to suggest the people to be profiled on  the cover page and in the magazine. Thousand of ideas, tweets and contributions followed. Chief of several large corporations have gone on record that in future, majority of the new product leads would come from people outside the organization. An Indian manufacturer puts the photo of the family which provides new recipes to use their snacks (obviously to expand their market) on the wrapper of their snacks.

Of course, the pity is that there are not too many examples of this kind in the country.  But the lesson is clear. What Honey Bee Network started years ago, is getting mainstreamed. We tried to influence the formal science and technology institutions as well as public policy platforms at national and international level. A small difference may have indeed been made. But a lot more remains to be done. These models of open source innovation have come to stay. The uncertainty and complexity in knowledge space is increasing and the possibility of any one discipline, expertise and organization visualizing solution to myriad problems is very little.  Knowledge networks have to emerge. The difference we are trying to make is that knowledge of common people should not be accessed without adequate acknowledgement and reciprocity. But linguistic, institutional and technological barriers in the way of  people to people knowledge exchange still remain to be overcome in substantive terms. What is open source for net savvy consumers is not yet open access for tribals, farm workers and others not having mobile phones or internet. We have to reach them in an affordable, accountable, and accessible manner. I invite your suggestions to meet this  challenge.

Anil K Gupta