Reputational Risk Associated with Big Data Research and Development: An Interdisciplinary Perspective

Abstract

Many private and public actors are incentivized by the promises of big data technologies: digital tools underpinned by capabilities like artificial intelligence and machine learning. While many shared value propositions exist regarding what these technologies afford, public-facing concerns related to individual privacy, algorithm fairness, and the access to insights requires attention if the widespread use and subsequent value of these technologies are to be fully realized. Drawing from perspectives of data science, social science and technology acceptance, we present an interdisciplinary analysis that links these concerns with traditional research and development (R&D) activities. We suggest a reframing of the public R&D ‘brand’ that responds to legitimate concerns related to data collection, development, and the implementation of big data technologies. We offer as a case study Australian agriculture, which is currently undergoing such digitalization, and where concerns have been raised by landholders and the research community. With seemingly limitless possibilities, an updated account of responsible R&D in an increasingly digitalized world may accelerate the ways in which we might realize the benefits of big data and mitigate harmful social and environmental costs.