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DIGITAL TECHNOLOGY
of delivery, and the availability of multiple communication channels such as CRCs and producer groups as mentioned above. Australian industry’s generally low level of engagement with universities for research and innovation xii is evi- dent as universities struggle to en- gage in the new communication channels, and also with the new “breeds” of firm – big and small – selling DA to farms and the food industry more generally. A pressing issue, and one that is directly within the control of farm- ers, is that of education. It has long been known that educated people (not only in the farming commun- ity) are more likely to explore and adopt innovations; this applies regardless of the source of that education (i.e. higher education, further education or local educa- tion). The profile of people new to agriculture has never been more diverse and the imperative is for this diversity to grow. We predict an expanded disciplinary base for knowledge growth and a “holy trinity” of skills: • Biological scientists – to understand the complex biological processes in- volved in creating value from a farm business; • Data scientists – to create methods of capturing and reporting meaningful data that adds value to the farm business; and • Behavioural scientists – to
reason why this concept cannot be translated into digital trans- formation in agriculture whereby farmers, as consumers of digital in- novation, provide developers with their user requirements. Until that occurs, digital adoption is likely to be slow, farmer-alien and discon- nected with many of the opportun- ities that await digital agriculture. WHAT’S NEXT FOR DIGITAL AGRI- CULTURE AND FARMER LEARN- ING? Lack of digital connectivity is a genuine barrier to the adoption of digital innovations in regional, rural and remote communities. Yet the situation is steadily improving, in Australia at least. However, this is a barrier that can be questioned with governments. Our traditional mechanisms for extension of scientific discovery to farmers have shifted over time, to reflect the iterative nature of in- novation, the changed economics
and their needs are what should be driving innovation. When one thinks of a pyramid whereby there are few corporate decision makers at the top and numerous consum- ers at the bottom; the flow of ideas and decision making about innova- tion development had traditionally filtered from the top of the pyra- mid to the bottom, whereas the bottom-up approach now seems to be gaining traction. Simanis and Duke (2014) give multiple ex- amples of where the top-down approach has failed (e.g. the poor response of sub-Saharan Africans to insecticide-treated bed nets) as it risks alienating those who use the consumer innovations, while the bottom-up approach has made high-impact on society (e.g. an e-verification solution for tracking genuine agricultural in- puts, whereby African farmers can verify the authenticity of seeds or pesticides via their mobile phones at agro-dealer shops). There is no
understand that knowledge creation and therefore value creation from new ways of innovation requires change
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