Convivial AI? Developing a societal impact analysis grid for assessing artificial intelligence in Earth observation

Abstract

The deployment of artificial intelligence (AI) applications with an ecological focus for data collection, analysis, monitoring, and decision automation has been widely described as a promising way of achieving sustainability. Such use has been the subject of research for some time, and recently, the ecological footprint of AI systems themselves has also been considered. While the societal implications of common AI applications are widely researched in terms of fairness, accountability, and transparency, the societal impact of specialized, ecologically-oriented AI applications remains understudied. To address this gap, we designed an analysis framework–the societal technology impact assessment grid (STIAG)–by extending the matrix of convivial technology (MCT), thus making it suitable for analyzing AI applications. We then apply this framework to satellite data-driven Earth observation (EO). This article seeks to communicate insights on two fronts: (1) the STIAG extends existing sustainability-oriented technology impact assessment frameworks, such as the MCT, by incorporating critical social and data-protection theory and (2) we contribute to the EO research domain by applying the analysis grid to EO’s AI-based methods, thereby uncovering their societal–and indeed neo-colonial–implications. We furthermore aim to advance the growing body of critical scholarship on sustainable AI and the field of EO itself by providing a constructive foundation for sustainable EO practices that can also inform research design and policymaking.