Journal article
Daedalus, 2026
APA
Click to copy
Michalak, A., & Platt, J. C. (2026). The Algorithmic Planet. Daedalus.
Chicago/Turabian
Click to copy
Michalak, A., and J.C. Platt. “The Algorithmic Planet.” Daedalus (2026).
MLA
Click to copy
Michalak, A., and J. C. Platt. “The Algorithmic Planet.” Daedalus, 2026.
BibTeX Click to copy
@article{a2026a,
title = {The Algorithmic Planet},
year = {2026},
journal = {Daedalus},
author = {Michalak, A. and Platt, J.C.}
}
To ensure a sustainable future, we need to understand how Earth's climate has changed over time, how different factors have contributed to those changes, and how human action will impact the climate in the future. Developing this understanding involves a continual process of model refinement, calibration, validation, and evaluation against available observations. These tasks present the core opportunity and challenge of applying artificial intelligence to climate: AI is enabling a revolution in the ability to represent the functioning of complex systems, but while the sheer volume of data available to help us understand the earth system is growing at an unprecedented pace, this observational record is often ill-suited to provide robust benchmarks for AI-driven models. In this essay, we present examples that illustrate this tension, focusing on the AI tractability of different applications, with tractability linked to the availability of metrics and benchmarks to guide model development. We also describe a future when developments in AI will accelerate improvement in models used to support climate action and resilience, enabling us to tackle the currently “intractable” frontier.