After spaceflight record, NASA looks to protect astronauts on even longer trips
At T-minus six seconds, the main engines of the Atlantis Space Shuttle ignited, rattling its capsule “like a skyscraper in an earthquake,” according to astronaut Tom Jones, describing the 1988 launch. As the rocket lifted off and accelerated to three times the force of Earth's gravity, “It felt as if two of my friends were standing on my chest and wouldn’t get off.” But when Atlantis reached orbit, the main engines cut off, and the astronauts were suddenly weightless.
Since 1961, NASA has sent hundreds of astronauts into space while working to making their voyages safer and smoother. Yet, challenges remain. Weightlessness may look amusing when watched from Earth, but it has myriad effects on cognition, movement and other functions. When missions to space stretch to six months or longer, microgravity can impact astronauts’ health and performance, making it more difficult to operate their spacecraft.
Yesterday, NASA astronaut Frank Rubio returned to Earth after over one year, the longest single spaceflight for a U.S. astronaut. But this is just the start; longer and more complex missions into deep space loom ahead, from returning to the moon in 2025 to eventually sending humans to Mars. To ensure that these missions succeed, NASA is increasing efforts to study the biological effects and prevent harm.
The dangers of microgravity are real
A NASA report published in 2016 details a long list of incidents and near-misses caused – at least partly – by space-induced changes in astronauts’ vision and coordination. These issues make it harder to move with precision and to judge distance and velocity.
According to the report, in 1997, a resupply ship collided with the Mir space station, possibly because a crew member bumped into the commander during the final docking maneuver. This mishap caused significant damage to the space station.
Returns to Earth suffered from problems, too. The same report notes that touchdown speeds during the first 100 space shuttle landings were “outside acceptable limits. The fastest landing on record – 224 knots (258 miles) per hour – was linked to the commander’s momentary spatial disorientation.” Earlier, each of the six Apollo crews that landed on the moon had difficulty recognizing moon landmarks and estimating distances. For example, Apollo 15 landed in an unplanned area, ultimately straddling the rim of a five-foot deep crater on the moon, harming one of its engines.
Spaceflight causes unique stresses on astronauts’ brains and central nervous systems. NASA is working to reduce these harmful effects.
NASA
Space messes up your brain
In space, astronauts face the challenges of microgravity, ionizing radiation, social isolation, high workloads, altered circadian rhythms, monotony, confined living quarters and a high-risk environment. Among these issues, microgravity is one of the most consequential in terms of physiological changes. It changes the brain’s structure and its functioning, which can hurt astronauts’ performance.
The brain shifts upwards within the skull, displacing the cerebrospinal fluid, which reduces the brain’s cushioning. Essentially, the brain becomes crowded inside the skull like a pair of too-tight shoes.
That’s partly because of how being in space alters blood flow. On Earth, gravity pulls our blood and other internal fluids toward our feet, but our circulatory valves ensure that the fluids are evenly distributed throughout the body. In space, there’s not enough gravity to pull the fluids down, and they shift up, says Rachael D. Seidler, a physiologist specializing in spaceflight at the University of Florida and principal investigator on many space-related studies. The head swells and legs appear thinner, causing what astronauts call “puffy face chicken legs.”
“The brain changes at the structural and functional level,” says Steven Jillings, equilibrium and aerospace researcher at the University of Antwerp in Belgium. “The brain shifts upwards within the skull,” displacing the cerebrospinal fluid, which reduces the brain’s cushioning. Essentially, the brain becomes crowded inside the skull like a pair of too-tight shoes. Some of the displaced cerebrospinal fluid goes into cavities within the brain, called ventricles, enlarging them. “The remaining fluids pool near the chest and heart,” explains Jillings. After 12 consecutive months in space, one astronaut had a ventricle that was 25 percent larger than before the mission.
Some changes reverse themselves while others persist for a while. An example of a longer-lasting problem is spaceflight-induced neuro-ocular syndrome, which results in near-sightedness and pressure inside the skull. A study of approximately 300 astronauts shows near-sightedness affects about 60 percent of astronauts after long missions on the International Space Station (ISS) and more than 25 percent after spaceflights of only a few weeks.
Another long-term change could be the decreased ability of cerebrospinal fluid to clear waste products from the brain, Seidler says. That’s because compressing the brain also compresses its waste-removing glymphatic pathways, resulting in inflammation, vulnerability to injuries and worsening its overall health.
The effects of long space missions were best demonstrated on astronaut twins Scott and Mark Kelly. This NASA Twins Study showed multiple, perhaps permanent, changes in Scott after his 340-day mission aboard the ISS, compared to Mark, who remained on Earth. The differences included declines in Scott’s speed, accuracy and cognitive abilities that persisted longer than six months after returning to Earth in March 2016.
By the end of 2020, Scott’s cognitive abilities improved, but structural and physiological changes to his eyes still remained, he said in a BBC interview.
“It seems clear that the upward shift of the brain and compression of the surrounding tissues with ventricular expansion might not be a good thing,” Seidler says. “But, at this point, the long-term consequences to brain health and human performance are not really known.”
NASA astronaut Kate Rubins conducts a session for the Neuromapping investigation.
NASA
Staying sharp in space
To investigate how prolonged space travel affects the brain, NASA launched a new initiative called the Complement of Integrated Protocols for Human Exploration Research (CIPHER). “CIPHER investigates how long-duration spaceflight affects both brain structure and function,” says neurobehavioral scientist Mathias Basner at the University of Pennsylvania, a principal investigator for several NASA studies. “Through it, we can find out how the brain adapts to the spaceflight environment and how certain brain regions (behave) differently after – relative to before – the mission.”
To do this, he says, “Astronauts will perform NASA’s cognition test battery before, during and after six- to 12-month missions, and will also perform the same test battery in an MRI scanner before and after the mission. We have to make sure we better understand the functional consequences of spaceflight on the human brain before we can send humans safely to the moon and, especially, to Mars.”
As we go deeper into space, astronauts cognitive and physical functions will be even more important. “A trip to Mars will take about one year…and will introduce long communication delays,” Seidler says. “If you are on that mission and have a problem, it may take eight to 10 minutes for your message to reach mission control, and another eight to 10 minutes for the response to get back to you.” In an emergency situation, that may be too late for the response to matter.
“On a mission to Mars, astronauts will be exposed to stressors for unprecedented amounts of time,” Basner says. To counter them, NASA is considering the continuous use of artificial gravity during the journey, and Seidler is studying whether artificial gravity can reduce the harmful effects of microgravity. Some scientists are looking at precision brain stimulation as a way to improve memory and reduce anxiety due to prolonged exposure to radiation in space.
Other scientists are exploring how to protect neural stem cells (which create brain cells) from radiation damage, developing drugs to repair damaged brain cells and protect cells from radiation.
To boldly go where no astronauts have gone before, they must have optimal reflexes, vision and decision-making. In the era of deep space exploration, the brain—without a doubt—is the final frontier.
Additionally, NASA is scrutinizing each aspect of the mission, including astronaut exercise, nutrition and intellectual engagement. “We need to give astronauts meaningful work. We need to stimulate their sensory, cognitive and other systems appropriately,” Basner says, especially given their extreme confinement and isolation. The scientific experiments performed on the ISS – like studying how microgravity affects the ability of tissue to regenerate is a good example.
“We need to keep them engaged socially, too,” he continues. The ISS crew, for example, regularly broadcasts from space and answers prerecorded questions from students on Earth, and can engage with social media in real time. And, despite tight quarters, NASA is ensuring the crew capsule and living quarters on the moon or Mars include private space, which is critical for good mental health.
Exploring deep space builds on a foundation that began when astronauts first left the planet. With each mission, scientists learn more about spaceflight effects on astronauts’ bodies. NASA will be using these lessons to succeed with its plans to build science stations on the moon and, eventually, Mars.
“Through internally and externally led research, investigations implemented in space and in spaceflight simulations on Earth, we are striving to reduce the likelihood and potential impacts of neurostructural changes in future, extended spaceflight,” summarizes NASA scientist Alexandra Whitmire. To boldly go where no astronauts have gone before, they must have optimal reflexes, vision and decision-making. In the era of deep space exploration, the brain—without a doubt—is the final frontier.
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.