New tech aims to make the ocean healthier for marine life
A defunct drydock basin arched by a rusting 19th century steel bridge seems an incongruous place to conduct state-of-the-art climate science. But this placid and protected sliver of water connecting Brooklyn’s Navy Yard to the East River was just right for Garrett Boudinot to float a small dock topped with water carbon-sensing gear. And while his system right now looks like a trio of plastic boxes wired up together, it aims to mediate the growing ocean acidification problem, caused by overabundance of dissolved carbon dioxide.
Boudinot, a biogeochemist and founder of a carbon-management startup called Vycarb, is honing his method for measuring CO2 levels in water, as well as (at least temporarily) correcting their negative effects. It’s a challenge that’s been occupying numerous climate scientists as the ocean heats up, and as states like New York recognize that reducing emissions won’t be enough to reach their climate goals; they’ll have to figure out how to remove carbon, too.
To date, though, methods for measuring CO2 in water at scale have been either intensely expensive, requiring fancy sensors that pump CO2 through membranes; or prohibitively complicated, involving a series of lab-based analyses. And that’s led to a bottleneck in efforts to remove carbon as well.
But recently, Boudinot cracked part of the code for measurement and mitigation, at least on a small scale. While the rest of the industry sorts out larger intricacies like getting ocean carbon markets up and running and driving carbon removal at billion-ton scale in centralized infrastructure, his decentralized method could have important, more immediate implications.
Specifically, for shellfish hatcheries, which grow seafood for human consumption and for coastal restoration projects. Some of these incubators for oysters and clams and scallops are already feeling the negative effects of excess carbon in water, and Vycarb’s tech could improve outcomes for the larval- and juvenile-stage mollusks they’re raising. “We’re learning from these folks about what their needs are, so that we’re developing our system as a solution that’s relevant,” Boudinot says.
Ocean acidification can wreak havoc on developing shellfish, inhibiting their shells from growing and leading to mass die-offs.
Ocean waters naturally absorb CO2 gas from the atmosphere. When CO2 accumulates faster than nature can dissipate it, it reacts with H2O molecules, forming carbonic acid, H2CO3, which makes the water column more acidic. On the West Coast, acidification occurs when deep, carbon dioxide-rich waters upwell onto the coast. This can wreak havoc on developing shellfish, inhibiting their shells from growing and leading to mass die-offs; this happened, disastrously, at Pacific Northwest oyster hatcheries in 2007.
This type of acidification will eventually come for the East Coast, too, says Ryan Wallace, assistant professor and graduate director of environmental studies and sciences at Long Island’s Adelphi University, who studies acidification. But at the moment, East Coast acidification has other sources: agricultural runoff, usually in the form of nitrogen, and human and animal waste entering coastal areas. These excess nutrient loads cause algae to grow, which isn’t a problem in and of itself, Wallace says; but when algae die, they’re consumed by bacteria, whose respiration in turn bumps up CO2 levels in water.
“Unfortunately, this is occurring at the bottom [of the water column], where shellfish organisms live and grow,” Wallace says. Acidification on the East Coast is minutely localized, occurring closest to where nutrients are being released, as well as seasonally; at least one local shellfish farm, on Fishers Island in the Long Island Sound, has contended with its effects.
The second Vycarb pilot, ready to be installed at the East Hampton shellfish hatchery.
Courtesy of Vycarb
Besides CO2, ocean water contains two other forms of dissolved carbon — carbonate (CO3-) and bicarbonate (HCO3) — at all times, at differing levels. At low pH (acidic), CO2 prevails; at medium pH, HCO3 is the dominant form; at higher pH, CO3 dominates. Boudinot’s invention is the first real-time measurement for all three, he says. From the dock at the Navy Yard, his pilot system uses carefully calibrated but low-cost sensors to gauge the water’s pH and its corresponding levels of CO2. When it detects elevated levels of the greenhouse gas, the system mitigates it on the spot. It does this by adding a bicarbonate powder that’s a byproduct of agricultural limestone mining in nearby Pennsylvania. Because the bicarbonate powder is alkaline, it increases the water pH and reduces the acidity. “We drive a chemical reaction to increase the pH to convert greenhouse gas- and acid-causing CO2 into bicarbonate, which is HCO3,” Boudinot says. “And HCO3 is what shellfish and fish and lots of marine life prefers over CO2.”
This de-acidifying “buffering” is something shellfish operations already do to water, usually by adding soda ash (NaHCO3), which is also alkaline. Some hatcheries add soda ash constantly, just in case; some wait till acidification causes significant problems. Generally, for an overly busy shellfish farmer to detect acidification takes time and effort. “We’re out there daily, taking a look at the pH and figuring out how much we need to dose it,” explains John “Barley” Dunne, director of the East Hampton Shellfish Hatchery on Long Island. “If this is an automatic system…that would be much less labor intensive — one less thing to monitor when we have so many other things we need to monitor.”
Across the Sound at the hatchery he runs, Dunne annually produces 30 million hard clams, 6 million oysters, and “if we’re lucky, some years we get a million bay scallops,” he says. These mollusks are destined for restoration projects around the town of East Hampton, where they’ll create habitat, filter water, and protect the coastline from sea level rise and storm surge. So far, Dunne’s hatchery has largely escaped the ill effects of acidification, although his bay scallops are having a finicky year and he’s checking to see if acidification might be part of the problem. But “I think it's important to have these solutions ready-at-hand for when the time comes,” he says. That’s why he’s hosting a second, 70-liter Vycarb pilot starting this summer on a dock adjacent to his East Hampton operation; it will amp up to a 50,000 liter-system in a few months.
If it can buffer water over a large area, absolutely this will benefit natural spawns. -- John “Barley” Dunne.
Boudinot hopes this new pilot will act as a proof of concept for hatcheries up and down the East Coast. The area from Maine to Nova Scotia is experiencing the worst of Atlantic acidification, due in part to increased Arctic meltwater combining with Gulf of St. Lawrence freshwater; that decreases saturation of calcium carbonate, making the water more acidic. Boudinot says his system should work to adjust low pH regardless of the cause or locale. The East Hampton system will eventually test and buffer-as-necessary the water that Dunne pumps from the Sound into 100-gallon land-based tanks where larvae grow for two weeks before being transferred to an in-Sound nursery to plump up.
Dunne says this could have positive effects — not only on his hatchery but on wild shellfish populations, too, reducing at least one stressor their larvae experience (others include increasing water temperatures and decreased oxygen levels). “If it can buffer water over a large area, absolutely this will [benefit] natural spawns,” he says.
No one believes the Vycarb model — even if it proves capable of functioning at much greater scale — is the sole solution to acidification in the ocean. Wallace says new water treatment plants in New York City, which reduce nitrogen released into coastal waters, are an important part of the equation. And “certainly, some green infrastructure would help,” says Boudinot, like restoring coastal and tidal wetlands to help filter nutrient runoff.
In the meantime, Boudinot continues to collect data in advance of amping up his own operations. Still unknown is the effect of releasing huge amounts of alkalinity into the ocean. Boudinot says a pH of 9 or higher can be too harsh for marine life, plus it can also trigger a release of CO2 from the water back into the atmosphere. For a third pilot, on Governor’s Island in New York Harbor, Vycarb will install yet another system from which Boudinot’s team will frequently sample to analyze some of those and other impacts. “Let's really make sure that we know what the results are,” he says. “Let's have data to show, because in this carbon world, things behave very differently out in the real world versus on paper.”
Researchers probe extreme gene therapy for severe alcoholism
Story by Freethink
A single shot — a gene therapy injected into the brain — dramatically reduced alcohol consumption in monkeys that previously drank heavily. If the therapy is safe and effective in people, it might one day be a permanent treatment for alcoholism for people with no other options.
The challenge: Alcohol use disorder (AUD) means a person has trouble controlling their alcohol consumption, even when it is negatively affecting their life, job, or health.
In the U.S., more than 10 percent of people over the age of 12 are estimated to have AUD, and while medications, counseling, or sheer willpower can help some stop drinking, staying sober can be a huge struggle — an estimated 40-60 percent of people relapse at least once.
A team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
According to the CDC, more than 140,000 Americans are dying each year from alcohol-related causes, and the rate of deaths has been rising for years, especially during the pandemic.
The idea: For occasional drinkers, alcohol causes the brain to release more dopamine, a chemical that makes you feel good. Chronic alcohol use, however, causes the brain to produce, and process, less dopamine, and this persistent dopamine deficit has been linked to alcohol relapse.
There is currently no way to reverse the changes in the brain brought about by AUD, but a team of U.S. researchers suspected that an in-development gene therapy for Parkinson’s disease might work as a dopamine-replenishing treatment for alcoholism, too.
To find out, they tested it in heavy-drinking monkeys — and the animals’ alcohol consumption dropped by 90% over the course of a year.
How it works: The treatment centers on the protein GDNF (“glial cell line-derived neurotrophic factor”), which supports the survival of certain neurons, including ones linked to dopamine.
For the new study, a harmless virus was used to deliver the gene that codes for GDNF into the brains of four monkeys that, when they had the option, drank heavily — the amount of ethanol-infused water they consumed would be equivalent to a person having nine drinks per day.
“We targeted the cell bodies that produce dopamine with this gene to increase dopamine synthesis, thereby replenishing or restoring what chronic drinking has taken away,” said co-lead researcher Kathleen Grant.
To serve as controls, another four heavy-drinking monkeys underwent the same procedure, but with a saline solution delivered instead of the gene therapy.
The results: All of the monkeys had their access to alcohol removed for two months following the surgery. When it was then reintroduced for four weeks, the heavy drinkers consumed 50 percent less compared to the control group.
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
The researchers then took the alcohol away for another four weeks, before giving it back for four. They repeated this cycle for a year, and by the end of it, the treated monkeys’ consumption had fallen by more than 90 percent compared to the controls.
“Drinking went down to almost zero,” said Grant. “For months on end, these animals would choose to drink water and just avoid drinking alcohol altogether. They decreased their drinking to the point that it was so low we didn’t record a blood-alcohol level.”
When the researchers examined the monkeys’ brains at the end of the study, they were able to confirm that dopamine levels had been replenished in the treated animals, but remained low in the controls.
Looking ahead: Dopamine is involved in a lot more than addiction, so more research is needed to not only see if the results translate to people but whether the gene therapy leads to any unwanted changes to mood or behavior.
Because the therapy requires invasive brain surgery and is likely irreversible, it’s unlikely to ever become a common treatment for alcoholism — but it could one day be the only thing standing between people with severe AUD and death.
“[The treatment] would be most appropriate for people who have already shown that all our normal therapeutic approaches do not work for them,” said Grant. “They are likely to create severe harm or kill themselves or others due to their drinking.”
This article originally appeared on Freethink, home of the brightest minds and biggest ideas of all time.
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.