Ocean Amplification

Ocean Amplification simulates images of waves to visualize the effects of climate change—and the energy demands of computation.
Picture of Ocean Amplification

The shape of the world’s oceans is changing. According to a 2019 report in the journal Science, wind speed increases in the Earth’s southernmost oceans induced by ocean warming have led over the last thirty or so years to an .25% surge in the wave height of the largest 10 percent of waves. As such, the wave emerges as a key symbol of ocean transformation: of the material effects of climate change, alongside intensified storms, sea-level rise, and increasing temperatures. The present project explores visualizations and simulations of rising waves, read as avatars of a hybrid human-inhuman political ecology.

The installation is built on a GAN, a machine-learning algorithm that generates digital images of waves. These waves become increasingly realistic as the program is trained on archival images of waves. As the imagined AI network “learns,” it consumes ever more electricity. Employing the magnitude of its energy usage — the carbon footprint of the required calculations — as an input to grow the height of its virtual waves, the work is structured around a feedforward loop linking the electro-anthropogenic generation of climate-changed wave power to the added computational loads created by the need for scientific assessments of climate change itself. (Francisco Alarcon with Stefan Helmreich)

*[Curatorial A(i)gents](https://mlml.io/p/curatorial-aigents)* presents a series of machine-learning-based experiments with museum collections and data developed by members and affiliates of metaLAB (at) Harvard, a creative research group working in the networked arts and humanities.