AI & the Environment

I write a lot about AI’s effects on the environment. I’m mostly pushing back against a lot of popular misconceptions and arguing that using AI is not bad for the environment. I’m also using this to share ideas and arguments from environmentalist ethics I think are important. I’ve split these up into sections and ordered each by which posts I’d read first. You can find these posts organized as a normal Substack page here.

Start here

• Using ChatGPT is not bad for the environment - a cheat sheet. I’ve collected every main point I’d make into a big cheat sheet, organized by every popular argument I’m responding to.

• For the climate, little things don’t add up

• Mapping the AI & environment debate

• Computing is efficient

• What a data center is

• Requests for journalists covering AI and the environment

Individual prompts

• Using ChatGPT is not bad for the environment. My original post on this. Most of this is also summarized in the cheat sheet.

• What’s the full “hidden” climate cost of a ChatGPT prompt? Trying to tally up every possible way ChatGPT could be adding to your carbon emissions.

• An example of what I consider a misleading article about AI and the environment. On the water cost of individual prompts being ridiculously small, despite many news stories implying they’re not.

• Reactions to MIT Technology Review's report on AI and the environment

• Why goofy AI art almost never seems wasteful to me

Data Centers

The big buildings where AI processes are run. They’re basically building-sized computers.

General

• What a data center is

• Do data centers only seem bad for the environment because we can see them?

Electricity

• Data centers & electricity - Part 1: They’re not raising national prices

Water

• The AI water issue is fake

• Data centers don’t harm water access at all anywhere in America

• More Perfect Union videos are wildly deceptive on data center water use

• Contra the UK government, please don’t delete your old photos and emails to save water

Environmental ethics

• For the climate, little things don't add up

• When making cuts for the climate, always consider the value you're getting per unit energy, not just the total energy used

• Jevons’ Paradox is good sometimes

• My can of soup example of bad climate communication

Meta

• A few meta points on my posts on AI and the environment

• Requests for journalists covering AI and the environment

• Replies to criticisms of my posts on AI & the environment

• Things I got wrong in my ChatGPT/environment posts

Misc

• Resource recs for energy literacy

Everything I’m saying is actually just a few points repeated over and over

There are actually just a few simple points I’m trying to drive home in all these posts, expressed over and over in different situations:

• For your personal footprint, compare AI to your total carbon and water footprint and see if it has any effect at all. Don’t compare it to incredibly efficient tiny things like Google searches.

• For local and global impact, compare AI to other industries and applications, not to your personal lifestyle. Manufacturing iPhones uses huge amounts of power in total. It would be ridiculous to compare manufacturing all iPhones to the number of flights an individual person takes. Creating a new product for a billion people is a more relevant comparison to training an AI model. Many data centers use the same amounts of water as other industries etc. Always contextualize large numbers.

• The collective environmental footprint of society is made up of the footprints of individuals. We should behave in the ways we’d want the group to behave. We should prioritize the things that actually help climate the most, because some things have many orders of magnitude more effect than others.

• All environmental and climate impacts of all industries are “new” in the sense that every day, all industries add new carbon emissions and air pollution to the environment. Treating AI data centers as special just because the buildings themselves are new normalizes much larger sources of emissions and harm that coincidentally were already happening.

• AI and the environment is confusing to think about because of the environmental paradox of data centers: they both put uniquely large concentrated demand on local grids, but are also tiny efficient parts of the global energy grid. They can look big and evil on the ground, but are actually remarkably efficient.

• In general, computing is one of the most resource-efficient parts of society.

• Most of AI’s effects on the environment will probably be caused by how it’s used, not by the physical operation of the data centers where it’s run.

All of these points seem really simple individually, but I wasn’t finding any popular commentary on AI and the environment online that checked all these boxes in the way I wanted, which was a big motivation to post about it more. There are a lot of great industry reports written for more technical audiences, but a lot of the popular coverage I was reading went against basically all of these points.