Common but different futures: AI inequity and climate crisis
The piece is authored by Trisha Ray
Some researchers and policymakers suggest that Artificial Intelligence or AI will provide the most game-changing solutions to the climate crisis. The potential lies in applications for optimizing energy demand and supply, accelerating the discovery and development of new materials, and aiding in the forecast and mitigation of the adverse effects of the climate crisis. Both AI development and climate change, however, are deeply embedded in geopolitical, social, and historical contexts that make the path to finding solutions far from straightforward. Given the current trajectory and geographic concentration of AI development and deployment, as well as institutional capacity, the benefits of AI technologies will accrue to a privileged few countries.
Indeed, the top 10 in Oxford Insights’ Government AI Readiness Index (2020) lists only two countries outside of North America and Europe. The report notes, “The lowest-scoring regions on average are Sub-Saharan Africa, Latin America and the Caribbean, and South and Central Asia. This reflects a persistent inequality in government AI readiness.” This inequality will be imprinted on climate change policy, which is itself marked by inequities in responsibility, capacity, and capability to monitor and respond to climate change.
Historically, as analysts have pointed out, developed countries are responsible for the bulk of emissions. Yet, the burden of compliance is placed disproportionately on developing countries. These observers call for a distinction between “survival emissions” of vulnerable communities, especially in developing countries, and “luxury emissions” of the developed ones. The mainstreaming of AI and allied emerging technologies will be an emissions-intensive process. At the same time, AI capacity in terms of R&D, investment, data, and infrastructure is currently skewed, focused within a handful of countries, primarily in the developed West. This report examines the interplay of global inequities in AI and climate change, and concludes with recommendations.
(The piece is authored by Trisha Ray)
