Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?
Generative AI has a large carbon footprint and other drawbacks. But AI can help mitigate its own harms—by plowing through mountains of data on extreme weather and human displacement.
The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.
But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.
Generative AI tools are based on large language models (LLMs), with most well-known being various versions of GPT. LLMs can perform natural language processing, including translating, summarizing and answering questions. They use artificial neural networks, called deep learning or machine learning. Inspired by the human brain, neural networks are made of millions of artificial neurons. “The basic principles of neural networks were known even in the 1950s and 1960s,” Toyama says, “but it’s only now, with the tremendous amount of compute power that we have, as well as huge amounts of data, that it’s become possible to train generative AI models.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries.
In recent months, much attention has gone to the transformative benefits of these technologies. But it’s important to consider that these remarkable advances may come at a price.
AI’s carbon footprint
In their latest annual report, 2023 Landscape: Confronting Tech Power, the AI Now Institute, an independent policy research entity focusing on the concentration of power in the tech industry, says: “The constant push for scale in artificial intelligence has led Big Tech firms to develop hugely energy-intensive computational models that optimize for ‘accuracy’—through increasingly large datasets and computationally intensive model training—over more efficient and sustainable alternatives.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries. In 2019, Emma Strubell, then a graduate researcher at the University of Massachusetts Amherst, estimated that training a single LLM resulted in over 280,000 kg in CO2 emissions—an equivalent of driving almost 1.2 million km in a gas-powered car. A couple of years later, David Patterson, a computer scientist from the University of California Berkeley, and colleagues, estimated GPT-3’s carbon footprint at over 550,000 kg of CO2 In 2022, the tech company Hugging Face, estimated the carbon footprint of its own language model, BLOOM, as 25,000 kg in CO2 emissions. (BLOOM’s footprint is lower because Hugging Face uses renewable energy, but it doubled when other life-cycle processes like hardware manufacturing and use were added.)
Luckily, despite the growing size and numbers of data centers, their increasing energy demands and emissions have not kept pace proportionately—thanks to renewable energy sources and energy-efficient hardware.
But emissions don’t tell the full story.
AI’s hidden human cost
“If historical colonialism annexed territories, their resources, and the bodies that worked on them, data colonialism’s power grab is both simpler and deeper: the capture and control of human life itself through appropriating the data that can be extracted from it for profit.” So write Nick Couldry and Ulises Mejias, authors of the bookThe Costs of Connection.
The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
Technologies we use daily inexorably gather our data. “Human experience, potentially every layer and aspect of it, is becoming the target of profitable extraction,” Couldry and Meijas say. This feeds data capitalism, the economic model built on the extraction and commodification of data. While we are being dispossessed of our data, Big Tech commodifies it for their own benefit. This results in consolidation of power structures that reinforce existing race, gender, class and other inequalities.
“The political economy around tech and tech companies, and the development in advances in AI contribute to massive displacement and pollution, and significantly changes the built environment,” says technologist and activist Yeshi Milner, who founded Data For Black Lives (D4BL) to create measurable change in Black people’s lives using data. The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
AI’s recent explosive growth spiked the demand for manual, behind-the-scenes tasks, creating an industry described by Mary Gray and Siddharth Suri as “ghost work” in their book. This invisible human workforce that lies behind the “magic” of AI, is overworked and underpaid, and very often based in the Global South. For example, workers in Kenya who made less than $2 an hour, were the behind the mechanism that trained ChatGPT to properly talk about violence, hate speech and sexual abuse. And, according to an article in Analytics India Magazine, in some cases these workers may not have been paid at all, a case for wage theft. An exposé by the Washington Post describes “digital sweatshops” in the Philippines, where thousands of workers experience low wages, delays in payment, and wage theft by Remotasks, a platform owned by Scale AI, a $7 billion dollar American startup. Rights groups and labor researchers have flagged Scale AI as one company that flouts basic labor standards for workers abroad.
It is possible to draw a parallel with chattel slavery—the most significant economic event that continues to shape the modern world—to see the business structures that allow for the massive exploitation of people, Milner says. Back then, people got chocolate, sugar, cotton; today, they get generative AI tools. “What’s invisible through distance—because [tech companies] also control what we see—is the massive exploitation,” Milner says.
“At Data for Black Lives, we are less concerned with whether AI will become human…[W]e’re more concerned with the growing power of AI to decide who’s human and who’s not,” Milner says. As a decision-making force, AI becomes a “justifying factor for policies, practices, rules that not just reinforce, but are currently turning the clock back generations years on people’s civil and human rights.”
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement.
Nuria Oliver, a computer scientist, and co-founder and vice-president of the European Laboratory of Learning and Intelligent Systems (ELLIS), says that instead of focusing on the hypothetical existential risks of today’s AI, we should talk about its real, tangible risks.
“Because AI is a transverse discipline that you can apply to any field [from education, journalism, medicine, to transportation and energy], it has a transformative power…and an exponential impact,” she says.
AI's accountability
“At the core of what we were arguing about data capitalism [is] a call to action to abolish Big Data,” says Milner. “Not to abolish data itself, but the power structures that concentrate [its] power in the hands of very few actors.”
A comprehensive AI Act currently negotiated in the European Parliament aims to rein Big Tech in. It plans to introduce a rating of AI tools based on the harms caused to humans, while being as technology-neutral as possible. That sets standards for safe, transparent, traceable, non-discriminatory, and environmentally friendly AI systems, overseen by people, not automation. The regulations also ask for transparency in the content used to train generative AIs, particularly with copyrighted data, and also disclosing that the content is AI-generated. “This European regulation is setting the example for other regions and countries in the world,” Oliver says. But, she adds, such transparencies are hard to achieve.
Google, for example, recently updated its privacy policy to say that anything on the public internet will be used as training data. “Obviously, technology companies have to respond to their economic interests, so their decisions are not necessarily going to be the best for society and for the environment,” Oliver says. “And that’s why we need strong research institutions and civil society institutions to push for actions.” ELLIS also advocates for data centers to be built in locations where the energy can be produced sustainably.
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement. “The only way to make sense of this data is using machine learning methods,” Oliver says.
Milner believes that the best way to expose AI-caused systemic inequalities is through people's stories. “In these last five years, so much of our work [at D4BL] has been creating new datasets, new data tools, bringing the data to life. To show the harms but also to continue to reclaim it as a tool for social change and for political change.” This change, she adds, will depend on whose hands it is in.
A woman receives a mammogram, which can detect the presence of tumors in a patient's breast.
When a patient is diagnosed with early-stage breast cancer, having surgery to remove the tumor is considered the standard of care. But what happens when a patient can’t have surgery?
Whether it’s due to high blood pressure, advanced age, heart issues, or other reasons, some breast cancer patients don’t qualify for a lumpectomy—one of the most common treatment options for early-stage breast cancer. A lumpectomy surgically removes the tumor while keeping the patient’s breast intact, while a mastectomy removes the entire breast and nearby lymph nodes.
Fortunately, a new technique called cryoablation is now available for breast cancer patients who either aren’t candidates for surgery or don’t feel comfortable undergoing a surgical procedure. With cryoablation, doctors use an ultrasound or CT scan to locate any tumors inside the patient’s breast. They then insert small, needle-like probes into the patient's breast which create an “ice ball” that surrounds the tumor and kills the cancer cells.
Cryoablation has been used for decades to treat cancers of the kidneys and liver—but only in the past few years have doctors been able to use the procedure to treat breast cancer patients. And while clinical trials have shown that cryoablation works for tumors smaller than 1.5 centimeters, a recent clinical trial at Memorial Sloan Kettering Cancer Center in New York has shown that it can work for larger tumors, too.
In this study, doctors performed cryoablation on patients whose tumors were, on average, 2.5 centimeters. The cryoablation procedure lasted for about 30 minutes, and patients were able to go home on the same day following treatment. Doctors then followed up with the patients after 16 months. In the follow-up, doctors found the recurrence rate for tumors after using cryoablation was only 10 percent.
For patients who don’t qualify for surgery, radiation and hormonal therapy is typically used to treat tumors. However, said Yolanda Brice, M.D., an interventional radiologist at Memorial Sloan Kettering Cancer Center, “when treated with only radiation and hormonal therapy, the tumors will eventually return.” Cryotherapy, Brice said, could be a more effective way to treat cancer for patients who can’t have surgery.
“The fact that we only saw a 10 percent recurrence rate in our study is incredibly promising,” she said.
Urinary tract infections account for more than 8 million trips to the doctor each year.
Few things are more painful than a urinary tract infection (UTI). Common in men and women, these infections account for more than 8 million trips to the doctor each year and can cause an array of uncomfortable symptoms, from a burning feeling during urination to fever, vomiting, and chills. For an unlucky few, UTIs can be chronic—meaning that, despite treatment, they just keep coming back.
But new research, presented at the European Association of Urology (EAU) Congress in Paris this week, brings some hope to people who suffer from UTIs.
Clinicians from the Royal Berkshire Hospital presented the results of a long-term, nine-year clinical trial where 89 men and women who suffered from recurrent UTIs were given an oral vaccine called MV140, designed to prevent the infections. Every day for three months, the participants were given two sprays of the vaccine (flavored to taste like pineapple) and then followed over the course of nine years. Clinicians analyzed medical records and asked the study participants about symptoms to check whether any experienced UTIs or had any adverse reactions from taking the vaccine.
The results showed that across nine years, 48 of the participants (about 54%) remained completely infection-free. On average, the study participants remained infection free for 54.7 months—four and a half years.
“While we need to be pragmatic, this vaccine is a potential breakthrough in preventing UTIs and could offer a safe and effective alternative to conventional treatments,” said Gernot Bonita, Professor of Urology at the Alta Bro Medical Centre for Urology in Switzerland, who is also the EAU Chairman of Guidelines on Urological Infections.
The news comes as a relief not only for people who suffer chronic UTIs, but also to doctors who have seen an uptick in antibiotic-resistant UTIs in the past several years. Because UTIs usually require antibiotics, patients run the risk of developing a resistance to the antibiotics, making infections more difficult to treat. A preventative vaccine could mean less infections, less antibiotics, and less drug resistance overall.
“Many of our participants told us that having the vaccine restored their quality of life,” said Dr. Bob Yang, Consultant Urologist at the Royal Berkshire NHS Foundation Trust, who helped lead the research. “While we’re yet to look at the effect of this vaccine in different patient groups, this follow-up data suggests it could be a game-changer for UTI prevention if it’s offered widely, reducing the need for antibiotic treatments.”