Securitising uncertainty: Ontological security and cultural scripts in smart farming technology implementation

Abstract

Smart farming technologies are primarily associated with the transformation of agricultural productivity. Despite this, empirical research focusing on farm-level application of smart farming reveals a more complex and nuanced picture characterised by considerable uncertainty over its implementation and use. In this paper we seek to extend farm-level research by investigating two questions: how do perceived uncertainties destabilise meso-scale actors' routines and practices that are critical for ‘supporting farmer learning about the nature of digital data and its interpretation’ (Eastwood et al., 2019: 8); and, in what ways do meso-scale actors seek to re-establish a sense of stability and, in doing so, manage the uncertainty associated with smart farming implementation, and technological change more broadly? To address these questions we investigate the findings from a qualitative study of 20 meso-scale actors involved in the planning and implementation of smart farming technology in the Australian rice industry through an ontological security lens. We refer to meso-scale actors as farm advisors and agronomists whom we argue play a critical role in the uptake of smart farming technology. In applying this lens we argue that the perceived uncertainties related to smart farming de-stabilise or de-securitise actors' day-to-day roles and routines, impacting on who they are and what they do. We then demonstrate that actors draw upon two specific cultural scripts as a way to re-securitise their uncertainty. The first script seeks to securitise resource uncertainty by drawing upon known discourses surrounding farmer adoption of technology, while the second reproduces the importance of technologies that are easy to adopt while downplaying the importance of smart farming technology. While at face value these scripts can appear to create barriers to smart farming adoption, we argue that they can be a catalyst for developing solutions to uncertainty in terms of making smart farming more workable at the farm-level.