Google famously used computing power to improve its energy efficiency.2 However, while incremental progress will be made through endeavours such as this, the quality of the data will likely hamper its success: as the saying goes, “rubbish in, rubbish out".
In this article, we look at the potential for all forms of data – big, micro and alternative – to be translated into meaningful information and then collected and presented in a way that encourages tangible, action-driven outcomes. Challenges arise over privacy, ownership and responsibility. While individuals have a clear role to play in shifting consumer behaviour to a more sustainable footing, we expend the bulk of our attention on governments and companies.1 David Rolnick et al., ‘Tackling climate change with machine learning’, November 2019
Date of publication: February 2020