From Baillie Gifford

Kate Crawford: exposing artificial intelligence’s true costs

October 2023 / 4 minutes

Key points

  • Prof Kate Crawford works in academia and at Microsoft Research, studying the implications of AI
  • Her book Atlas of AI highlights the environmental and social costs involved, as well as the opaque nature of the technology’s supply chain
  • Crawford urges users of ChatGPT and other ‘generative’ AI tools to consider their supply chains

Prof Kate Crawford studies the social implications of artificial intelligence. Photography by Cath Muscat.

Kate Crawford knows of a secret that makes it impossible to see the latest chatbots and other artificial intelligence advances the same way.

The Australia-born professor recently surprised an Edinburgh Book Festival audience with news of a study “indicating that every time you have an exchange with ChatGPT, it's the equivalent of pouring out half a litre of fresh water onto the ground” because that’s what it takes to “cool the giant AI supercomputers” involved.

When we meet shortly afterwards, she highlights a further issue with the ‘large language models’ (LLMs) that let ChatGPT and other ‘generative’ AI tools create text, images and other human-like output.

“The energy difference from just doing a traditional search query to using a LLM is enormous,” she says. “Some research indicates it can be up to 1,000 times more energy intensive.”

And this brings us to the heart of the matter. While such claims are arresting, they are hard to verify or get more details about from the companies responsible.

“The question of the environmental cost of AI is the biggest secret in the industry right now,” Crawford explains.

“It’s incredibly difficult because it’s incredibly hard to find out very accurate numbers on exactly how much water is being used and from where and exactly how much energy and from which sources are coming – from dirty sources of energy or clean sources of energy?

“All along the pipeline – the hardware, the software, the energy, the water to cool the systems – we have enormous environmental costs that are not being fully shared with the public.”


Industry insider

It’s a striking observation from a contributor to the work of Microsoft Research’s lab in New York. Its parent company has invested billions of dollars in ChatGPT’s creator, OpenAI, and is in the process of rolling out generative AI across its Microsoft 365 suite of apps. Crawford works with a group of experts at the firm, drawing on learnings from sociology, anthropology and other fields to suggest ways computer-related technologies can be developed ethically and accountably.

But that’s just one of many plates the multi-talented scholar has spinning.

Crawford is a professor at the University Southern California Annenberg and the École Normale Supérieure in Paris. She has several electronica albums to her name. And she draws on both her artistic and academic temperaments to develop large-scale artworks illustrating AI’s complex dynamics. A notable example is the Anatomy of an AI System, which she created with another professor that visualises the human labour, data and natural resources needed to create an Amazon Echo smart speaker. The Metropolitan Museum of Modern Art in New York now has it on display, and it is also in the permanent collection of the UK’s V&A museums.

In 2021, Crawford published the book Atlas of AI: Power, Politics and the Planetary Costs of Artificial Intelligence. ChatGPT’s subsequent release has only amplified her concerns.

“If you're in this field right now, you probably haven't slept for six months,” she says.

“Anyone who was working in this space thought we had probably another decade, at least, until we got to this place. So the degree of rapid change has caught everybody by surprise, including the people building these models.”


Extractive technology

Speaking to Crawford, her fizzing intellect is apparent, but so too is her courage to speak out in an industry that doesn’t always take criticism kindly. Her description of AI as a “technology of extraction” must make some uncomfortable.

This refers to extracting the natural resources needed to create an AI system, ranging from the rare earths and other minerals mined from the ground to make semiconductors and other hardware to the energy and water consumption described above.

It also involves the extraction of human resources: data and labour.

Some data centres use renewable energy to reduce the environmental impact of carrying out AI and other computing tasks.

The data includes everything we have created and that has been created about us on the internet. That covers the creative labour of writers, artists, musicians and many others whose work has been taken, almost always without their knowledge or consent, to train the generative AI tools.

It also extends to the ‘hidden labour’ involved in the repetitive tasks some AI systems require, such as labelling huge amounts of training data, reviewing harmful content and testing the output. Many of these workers, Crawford writes, are scattered across the world and poorly compensated, often “paid pennies per microtask”.

“Everybody has a stake in this,” she tells me, “because these are systems that are built on something that we have all produced collectively.”


Transparency and accountability

Crawford believes there’s an urgent need for more transparency, but the opposite trend is unfolding.

“The history of the AI field has been one of openness,” she says. “All the conference papers are published in open journals. Anyone can read them. But we are now moving into a much more closed era and, I think, concerning period.”

National governments, the European Union, the G7 and the United Nations are all considering new laws and regulations to ensure companies and others deploy AI safely, ethically and in a trustworthy manner.

Crawford urges those involved to focus on how AI is “already accelerating a climate crisis [and] creating more economic inequality” rather than being distracted by the “boogeyman” of an out-of-control “Terminator risk scenario”.

“We have to start with transparency, and then we need accountability,” she says.

“These are going to be difficult diplomatic processes. But we’ve done it before [with nuclear technology]. We absolutely have to have the courage to do it again.”


Search v chatbot

Crawford also believes the public has a role to play. Although she recognises that there are times when a generative AI tool might be best suited to a task, there are many others when she suggests a more basic search query would be a more responsible choice and might even give a better answer.

“We’re not being trained to ask enough [whether] we are basically bringing a battleship to a knife fight,” she says.

“We're at this point in history where people are not being given a very good sense of what these tools are good for. And I think partly that's because the industry doesn't know either.

“Think about it almost as like building a plane in mid-air. People are figuring this out as we go.”

Most people think of artificial intelligence in abstract, intangible terms. Crawford’s talent is making the invisible visible and demonstrating that AI belongs to the physical world. Her intention is for this to be empowering: by mapping out the technology’s true costs and considering its long-term impacts, those responsible for developing, governing and using AI can make better decisions today.

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