The Datafied Animal: Biologging, Machine Learning and Wildlife Conservation

Over the past several decades, scientists have developed an ever-expanding internet of animals. This network is a collection of tools that includes miniaturized tags, GPS-telemetry, recording devices, cyberinfrastructure, machine learning, and AI directed at wildlife. These new technologies are being used to turn previously inaccessible aspects of animal life into data, fundamentally transforming knowledge about wildlife, as well as reshaping ecology as a discipline.

There have been many critical studies of datafication as related to human lives. However, these studies leave unexamined what happens when these technologies are used for the study of non-human animals. The data about wildlife being generated have the potential to be transformative for conservation and animal management practices.

Implicit in these initiatives is the idea of a better Anthropocene for nonhumans, one in which the human impact on the world is used to improve ecological systems. This remaking of the environment will be informed by the data emerging from the internet of animals; it is thus imperative to understand the values, beliefs, and practices affecting its production.

This project follows the data, its creation in the field, to the development of algorithms and machine learning tools to analyze it. Primary fieldwork for this project will consist of interviews and participant observation research with scientists and laypeople who are developing and using technology to study and manage wildlife. Through an empirical analysis of the technology that produces big data about wildlife and the choices that go into its design and deployment, this project will reckon with how ecosurveillance is produced and what is included and excluded from the scientific gaze.

In doing so, this project will also address broader questions about how representations of the environment and animal life are produced and how this technology has changed ecological science, labor, notions of expertise, and conservation practices.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.