Managing reputational risk associated with big data research and development: an interdisciplinary perspective

Many private and public actors are incentivized by big data technologies: digital tools underpinned by capabilities such as artificial intelligence and machine learning. While many shared value propositions exist about what these technologies afford, public facing concerns related to individual privacy, algorithm fairness, and access to insights require 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 reveals the connections between these concerns and traditional research and development (R&D) activities of data collection, technology development and implementation. Given the behaviors associated with digital transformation opportunities, we suggest a reframing of the public-facing R&D ‘brand’ that responds to legitimate concerns related to individual privacy, fairness, and social equity. We offer as a case study Australian agriculture, which is currently undergoing such digitalisation 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 increasing digitalized world may accelerate how we might realize benefits of big data and mitigate harmful social and environmental costs.