Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?
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 book The 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.
The Friday Five: The plain solution to holiday stress?
The Friday Five covers five stories in research that you may have missed this week. There are plenty of controversies and troubling ethical issues in science – and we get into many of them in our online magazine – but this news roundup focuses on scientific creativity and progress to give you a therapeutic dose of inspiration headed into the weekend.
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Here are the promising studies covered in this week's Friday Five:
- How to improve your working memory
- A plain old solution to stress
- Progress on a deadly cancer for first time since 1995*
- Rise of the robot surgeon
- Tomato brain power
And in an honorable mention this week, new research on the gut connection to better brain health after strokes.
* The methodology for this study has come under scrutiny here.
Scientists Are Working to Decipher the Puzzle of ‘Broken Heart Syndrome’
Elaine Kamil had just returned home after a few days of business meetings in 2013 when she started having chest pains. At first Kamil, then 66, wasn't worried—she had had some chest pain before and recently went to a cardiologist to do a stress test, which was normal.
"I can't be having a heart attack because I just got checked," she thought, attributing the discomfort to stress and high demands of her job. A pediatric nephrologist at Cedars-Sinai Hospital in Los Angeles, she takes care of critically ill children who are on dialysis or are kidney transplant patients. Supporting families through difficult times and answering calls at odd hours is part of her daily routine, and often leaves her exhausted.
She figured the pain would go away. But instead, it intensified that night. Kamil's husband drove her to the Cedars-Sinai hospital, where she was admitted to the coronary care unit. It turned out she wasn't having a heart attack after all. Instead, she was diagnosed with a much less common but nonetheless dangerous heart condition called takotsubo syndrome, or broken heart syndrome.
A heart attack happens when blood flow to the heart is obstructed—such as when an artery is blocked—causing heart muscle tissue to die. In takotsubo syndrome, the blood flow isn't blocked, but the heart doesn't pump it properly. The heart changes its shape and starts to resemble a Japanese fishing device called tako-tsubo, a clay pot with a wider body and narrower mouth, used to catch octopus.
"The heart muscle is stunned and doesn't function properly anywhere from three days to three weeks," explains Noel Bairey Merz, the cardiologist at Cedar Sinai who Kamil went to see after she was discharged.
"The heart muscle is stunned and doesn't function properly anywhere from three days to three weeks."
But even though the heart isn't permanently damaged, mortality rates due to takotsubo syndrome are comparable to those of a heart attack, Merz notes—about 4-5 percent of patients die from the attack, and 20 percent within the next five years. "It's as bad as a heart attack," Merz says—only it's much less known, even to doctors. The condition affects only about 1 percent of people, and there are around 15,000 new cases annually. It's diagnosed using a cardiac ventriculogram, an imaging test that allows doctors to see how the heart pumps blood.
Scientists don't fully understand what causes Takotsubo syndrome, but it usually occurs after extreme emotional or physical stress. Doctors think it's triggered by a so-called catecholamine storm, a phenomenon in which the body releases too much catecholamines—hormones involved in the fight-or-flight response. Evolutionarily, when early humans lived in savannas or forests and had to either fight off predators or flee from them, these hormones gave our ancestors the needed strength and stamina to take either action. Released by nerve endings and by the adrenal glands that sit on top of the kidneys, these hormones still flood our bodies in moments of stress, but an overabundance of them could sometimes be damaging.
Elaine Kamil
A study by scientists at Harvard Medical School linked increased risk of takotsubo to higher activity in the amygdala, a brain region responsible for emotions that's involved in responses to stress. The scientists believe that chronic stress makes people more susceptible to the syndrome. Notably, one small study suggested that the number of Takotsubo cases increased during the COVID-19 pandemic.
There are no specific drugs to treat takotsubo, so doctors rely on supportive therapies, which include medications typically used for high blood pressure and heart failure. In most cases, the heart returns to its normal shape within a few weeks. "It's a spontaneous recovery—the catecholamine storm is resolved, the injury trigger is removed and the heart heals itself because our bodies have an amazing healing capacity," Merz says. It also helps that tissues remain intact. 'The heart cells don't die, they just aren't functioning properly for some time."
That's the good news. The bad news is that takotsubo is likely to strike again—in 5-20 percent of patients the condition comes back, sometimes more severe than before.
That's exactly what happened to Kamil. After getting her diagnosis in 2013, she realized that she actually had a previous takotsubo episode. In 2010, she experienced similar symptoms after her son died. "The night after he died, I was having severe chest pain at night, but I was too overwhelmed with grief to do anything about it," she recalls. After a while, the pain subsided and didn't return until three years later.
For weeks after her second attack, she felt exhausted, listless and anxious. "You lose confidence in your body," she says. "You have these little twinges on your chest, or if you start having arrhythmia, and you wonder if this is another episode coming up. It's really unnerving because you don't know how to read these cues." And that's very typical, Merz says. Even when the heart muscle appears to recover, patients don't return to normal right away. They have shortens of breath, they can't exercise, and they stay anxious and worried for a while.
Women over the age of 50 are diagnosed with takotsubo more often than other demographics. However, it happens in men too, although it typically strikes after physical stress, such as a triathlon or an exhausting day of cycling. Young people can also get takotsubo. Older patients are hospitalized more often, but younger people tend to have more severe complications. It could be because an older person may go for a jog while younger one may run a marathon, which would take a stronger toll on the body of a person who's predisposed to the condition.
Notably, the emotional stressors don't always have to be negative—the heart muscle can get out of shape from good emotions, too. "There have been case reports of takotsubo at weddings," Merz says. Moreover, one out of three or four takotsubo patients experience no apparent stress, she adds. "So it could be that it's not so much the catecholamine storm itself, but the body's reaction to it—the physiological reaction deeply embedded into out physiology," she explains.
Merz and her team are working to understand what makes people predisposed to takotsubo. They think a person's genetics play a role, but they haven't yet pinpointed genes that seem to be responsible. Genes code for proteins, which affect how the body metabolizes various compounds, which, in turn, affect the body's response to stress. Pinning down the protein involved in takotsubo susceptibility would allow doctors to develop screening tests and identify those prone to severe repeating attacks. It will also help develop medications that can either prevent it or treat it better than just waiting for the body to heal itself.
Researchers at the Imperial College London found that elevated levels of certain types of microRNAs—molecules involved in protein production—increase the chances of developing takotsubo.
In one study, researchers tried treating takotsubo in mice with a drug called suberanilohydroxamic acid, or SAHA, typically used for cancer treatment. The drug improved cardiac health and reversed the broken heart in rodents. It remains to be seen if the drug would have a similar effect on humans. But identifying a drug that shows promise is progress, Merz says. "I'm glad that there's research in this area."
This article was originally published by Leaps.org on July 28, 2021.
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.