How Data Hoarding Is the New Threat to Privacy and Climate Change

As machine learning and other data-intensive algorithms proliferate, more organizations are hoarding data in hopes of alchemizing it into something valuable. From spy agencies to network infrastructure providers, data collection is part and parcel of the digital economy. The best data can be combined with clever algorithms to do incredible things — but digital hoarding and computationally-intensive workloads have externalities too.

Data hoarding and computationally-intensive
workloads have climate crisis implications.

The electrical costs — and therefore the environmental impacts — of computation are both extraordinary and growing. Modern machine learning (ML) models are a prime example. They require an enormous amount of energy in order to process mountains of data. The computational costs of training ML models have been growing exponentially since 2012, with a doubling period of 18 months, according to OpenAI. In recent months, similar studies have shown that the electrical costs of cryptocurrency and video streaming are also significant and growing.

Producing this electricity creates literal exhaust in most cases — there are precious few server farms running on 100% renewable energy — and with climate change looming large, it’s time we acknowledge the environmental impact of computation. Just like wrapping every little thing in a plastic bag is, some of our CPU usage is frivolous and wasteful.

Read the story from One Zero by Tyler Elliot Bettilyon - “How Data Hoarding Is the New Threat to Privacy and Climate Change.”