Loss and Damage benefits from the inclusion of Artificial Intelligence systems to support prevention and assessment. As AI research and development is highly dominated by western and private-led powers, the effectiveness of its use is limited for vulnerable countries. We call for an accessible, inclusive and locally-grounded AI to serve the needs of the most vulnerable, support Article 8 of the Paris Agreement and democratise innovation.

Over the past half century, the global environment has become subject to an accelerated pace of mediation and datafication. This ongoing transition has become so comprehensive that the knowledge, management and governance of the Earth system is dependent on enormous flows of data from a “vast machine” of measuring tools. These processes combined have formed what we call a “mediated planet,” subject to interpretation and shared human decision-making – that should ideally be democratic, inclusive and accountable. As environmental datafication continues to accelerate, private corporations are gaining increasing influence on and power over the associated collections of data. This is a cause for concern, as the global environmental commons are a public interest of concern to all people. This article argues for the need to critically research the challenges and risks associated with the rapid datafication of the environment, specifically in relation to the UN Sustainable Development Goals (SDGs) for climate change (13), the ocean (14), biodiversity (15) and inclusive and accountable institutions (16). More knowledge is needed of how the SDGs and their supporting networks influence data-generation on a mediated planet, and how issues of access to and use of environmental data, as well as data ownership and AI implementation, can best be navigated. We contend that such knowledge can help enhance the democratic potential of the SDGs to build public trust and secure broad participation in global environmental governance in ways that also support peaceful and inclusive societies, as promised by SDG 16.

This essay engages with recent scholarship on the epistemology of AI, data and automation, to assert how these practices are becoming increasingly central both to the projects of monitoring and of managing a global environment. We also review Jürgen Renn’s recent contribution The Evolution of Knowledge (2020) in relation to the history of environmental data. Using Renn as point of departure, we stake out a way for understanding the Anthropocene through the interaction between data and environment, taking into account the deeper political implications of datafication. We conclude with discussions about how historians of technology and environment could play an important role in assessing the opportunities and risks of AI for global environmental justice before their full-scale implementation is a fait accompli. In face of the Anthropocene, there is a general need today for integrative efforts of bridging knowledge from natural, technical, social and humanistic domains, and therefore a strong imperative for humanistic studies to transposetools, methodologies, and insights into the realms of policymaking, and legislation. Thus, assessments of AI and environment must account for these historical processes in the present as well as offer critical analysis of the full ontological spectrum from object to epistemology via data and mediation.