Search

• Environmental and climate crises are grist for tech solutions. • AI technologies require computational resources that are environmentally embedded. • Disasters become "shocks" that the AI industry capitalizes on. • Climate AI shapes material investment flows and landscapes. • Data-driven approaches to climate reproduce injustices faced by marginalized communities. Emerging narratives around artificial intelligence (AI) and machine learning place great faith in these technologies' ability to ameliorate threats posed by climate change. They promise the capacity to analyze vast amounts of more precise and real-time data, improving how decision-makers predict, respond, and adapt. Yet scholars in political ecology have long observed that technocentric approaches typically reduce complex human-environment relationships in ways that fail to account for social relations and power dynamics. This paper charts the emerging political economy of "climate AI" – the philanthropies, NGOs, private consultancies, and tech giants investing in data-driven climate initiatives. Mapping out two case studies, we show that environmental and climate crises are grist for tech solutions and find that many climate AI actors are interested in it for surveillance, greenwashing, and commodifying algorithms. We pay special attention to how neocolonial and racialized power structures manifest in climate AI and outline three ways for political ecologists and digital geographers to research its socio-materiality: how computational resources are environmentally embedded, how disasters become "shocks" that the AI industry capitalizes on, and how climate AI shapes material investment flows and landscapes. Highlighting how data-driven approaches to climate crises reproduce injustices already faced by marginalized communities, our analysis contributes to research on environmental data justice. [ABSTRACT FROM AUTHOR]

Conservationists, governments, and corporations see promise in digital technologies to provide holistic, rapid, and objective information to inform policy, shape investments, and monitor ecosystems. But it is increasingly clear that environmental data does more than simply offer a better view of the planet. This special issue makes a single overarching argument: that we cannot fully understand the current conjuncture in global environmental governance without understanding the platforms, devices, and institutions that comprise environmental data infrastructures. The papers draw together scholarship from political ecology and science and technology studies to demonstrate how data has become a significant site in which contemporary environmental politics are waged and socionatures are materialized. We address: (1) the contested practices of utilizing and maintaining data infrastructures; (2) the ways they are governed and the territorial statecraft they enable; (3) the socionatural materiality they arise within but also produce. The papers in this special issue show that, against its dominant representation, data is material, governed, practiced, and requires praxis. Political ecologists could adopt such an approach to make sense of the emerging ways in which data technologies shape environments and their politics. [ABSTRACT FROM AUTHOR]

Drawing on a novel dataset of hazardous waste shipments among Canada, Mexico, and the United States, we seek to enhance dominant modes of understanding transnational trading and regulation at the scale of the nation-state. We argue that these, while valuable, are limited by methodological nationalism. This epistemological position identifies the nation-state as the most relevant unit of analysis in examining “transnational” phenomena. In the case of transboundary waste trading, tracking waste between nation-states has come at the expense of identification and analysis of specific sites within nations that receive hazardous materials or send them abroad, obscuring the ongoing proliferation of waste havens at a subnational level and related environmental justice concerns. Working against methodological nationalism entails an epistemological shift that we pursue in this article through a series of empirical, analytical, and representational practices. We propose three visualization tactics that undermine nation-centered imaginaries: (1) documenting waste havens within the understudied United States through identifying subnational sites importing hazardous waste for processing; (2) establishing connections through flow maps connecting importing and exporting localities transnationally trading specific hazardous wastes; and (3) analyzing the corporate networks dominating the transnational waste trade. We argue these tactics build toward an alternative conception of methodological cosmopolitanism that highlights alternative routes toward environmental justice. [ABSTRACT FROM AUTHOR]

HazMatMapper is an online and interactive geographic visualization tool designed to facilitate exploration of transnational flows of hazardous waste in North America (http://geography.wisc.edu/hazardouswaste/map/). While conventional narratives suggest that wealthier countries such as Canada and the United States (US) export waste to poorer countries like Mexico, little is known about how waste trading may affect specific sites within any of the three countries. To move beyond anecdotal discussions and national aggregates, we assembled a novel geographic dataset describing transnational hazardous waste shipments from 2007 to 2012 through two Freedom of Information Act requests for documents held by the US Environmental Protection Agency. While not yet detailing all of the transnational hazardous waste trade in North America, HazMatMapper supports multiscale and site-specific visual exploration of US imports of hazardous waste from Canada and Mexico. It thus enables academic researchers, waste regulators, and the general public to generate hypotheses on regional clustering, transnational corporate structuring, and environmental justice concerns, as well as to understand the limitations of existing regulatory data collection itself. Here, we discuss the dataset and design process behind HazMatMapper and demonstrate its utility for understanding the transnational hazardous waste trade. [ABSTRACT FROM AUTHOR]