Digital Conservation Practices and Perspectives in the Anthropocene

The Anthropocene’s breaking down of nature/society binaries means that conservationists must grapple with what are increasingly recognized as value-laden choices about what to protect and restore as well as greater public awareness of the extent of anthropogenic environmental change. This represents an ambiguity in what the Anthropocene thesis implies we should do about it – should we embrace our planet-shaping powers or are people the problem? 

Digital technologies including big data and associated data collection tools such as sensors; machine learning and artificial intelligence (AI); and dashboards and platforms for data sharing collectively constitute “digital conservation” and they might lend themselves to either answer - towards more people-oriented conservation or more fortress-style conservation. So, what do conservationists actually think about and do with digital tools? 

We conducted a content analysis of keywords on conservation technology-related websites and the websites of 69 conservation organizations. We also surveyed 45 organizations across Canada and the US on their use of conservation technologies, their goals in using them, and the outcomes they’ve seen, and we ran a Q-method survey with 10 individuals in the sector to characterize clusters of thought on digital conservation. Finally, we explored a case study, interviewing 5 key informants and coding primary materials.

We find that the conversation on digital conservation revolves around certain technologies (e.g. camera traps), domains (e.g. forests), practical and ethical concerns (e.g. cost, privacy), and conservation approaches (e.g. partnerships). For instance, machine learning and AI are increasingly discussed across the conservation community. However, these remain relatively rare on conservation organizations’ own websites and few report actually using them. A primary goal in using such tools is minimizing labour costs, though this wasn’t as often reported an outcome by the organizations using them. Inversely, big data is discussed less and less, even though it represents one of the most common new technologies organizations report using. While disseminating information through platforms and portals was an important objective for conservation organizations, gathering information from the public wasn’t, and other forms of big data (e.g. from sensors) were utilized more than volunteered forms (e.g. from apps). This was reinforced in our case study of a program that uses eBird data to conserve migratory bird habitat on working lands, in which conservationists described challenges to building new supporting data infrastructures. 

We summarize three ways conservationists think about data technologies. Everyone agrees that AI hasn’t revolutionized conservation. However, one perspective questions tools’ promises to bring about efficiency and empowerment and instead highlights the ethical issues with technologies like drones and AI. The other two perspectives represent more optimistic stances - one emphasizes tools’ efficiency, responsiveness, and labour-saving promises while the other focuses on their societal and organizational outcomes, including how they might democratize conservation, shape public perceptions of nature, and, in general, transform the practice of conservation.

While we can’t definitively determine whether digital conservation reinforces trends towards people-oriented or fortress-like conservation in the Anthropocene, we can conclude that technology doesn’t solve existing conservation challenges. It addresses them unevenly and introduces new ones.