Josh Fairfield Publishes Article in Oxford Intersections: AI in Society The article examines how the resource intensive use of AI can exacerbate environmental damage due to the way AI models learn and evolve.
Professor Josh FairfieldWashington and Lee law professor Josh Fairfield has published an article in Oxford Intersections: AI in Society. The article, “Clean Data: Recursion as Pollution in Environmental AI,” examines how the resource intensive use of AI can exacerbate environmental damage due to the way AI models learn and evolve.
“If ‘data is the new oil,’ then corruption in the data used to train artificial intelligence (AI) constitutes a new form of pollution. Environmental AI has traditionally been discussed in terms of its indirect effects on the environment—the irony of burning power, processor cycles, and heat to produce solutions to stop and heal environmental damage. But there is a deeper problem. When environmental AI suggests interventions, its outputs are written onto the landscape. If that landscape is then read as data to retrain AI, there is a risk of model collapse and catastrophic forgetting, as the snake devours its own tail. This article discusses the difficulty in fit between current legal regimes governing AI and the use of AI in the environmental space and then further details the problems of model collapse in the context of environmental AI,” writes Fairfield.
The article is available online at the W&L Law Scholarly Commons.
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