New implants let paraplegics surf the web and play computer games
When I greeted Rodney Gorham, age 63, in an online chat session, he replied within seconds: “My pleasure.”
“Are you moving parts of your body as you type?” I asked.
This time, his response came about five minutes later: “I position the cursor with the eye tracking and select the same with moving my ankles.” Gorham, a former sales representative from Melbourne, Australia, living with amyotrophic lateral sclerosis, or ALS, a rare form of Lou Gehrig’s disease that impairs the brain’s nerve cells and the spinal cord, limiting the ability to move. ALS essentially “locks” a person inside their own body. Gorham is conversing with me by typing with his mind only–no fingers in between his brain and his computer.
The brain-computer interface enabling this feat is called the Stentrode. It's the brainchild of Synchron, a company backed by Amazon’s Jeff Bezos and Microsoft cofounder Bill Gates. After Gorham’s neurologist recommended that he try it, he became one of the first volunteers to have an 8mm stent, laced with small electrodes, implanted into his jugular vein and guided by a surgeon into a blood vessel near the part of his brain that controls movement.
After arriving at their destination, these tiny sensors can detect neural activity. They relay these messages through a small receiver implanted under the skin to a computer, which then translates the information into words. This minimally invasive surgery takes a day and is painless, according to Gorham. Recovery time is typically short, about two days.
When a paralyzed patient thinks about trying to move their arms or legs, the motor cortex will fire patterns that are specific to the patient’s thoughts.
When a paralyzed patient such as Gorham thinks about trying to move their arms or legs, the motor cortex will fire patterns that are specific to the patient’s thoughts. This pattern is detected by the Stentrode and relayed to a computer that learns to associate this pattern with the patient’s physical movements. The computer recognizes thoughts about kicking, making a fist and other movements as signals for clicking a mouse or pushing certain letters on a keyboard. An additional eye-tracking device controls the movement of the computer cursor.
The process works on a letter by letter basis. That’s why longer and more nuanced responses often involve some trial and error. “I have been using this for about two years, and I enjoy the sessions,” Gorham typed during our chat session. Zafar Faraz, field clinical engineer at Synchron, sat next to Gorham, providing help when required. Gorham had suffered without internet access, but now he looks forward to surfing the web and playing video games.
Gorham, age 63, has been enjoying Stentrode sessions for about two years.
Rodeny Dekker
The BCI revolution
In the summer of 2021, Synchron became the first company to receive the FDA’s Investigational Device Exemption, which allows research trials on the Stentrode in human patients. This past summer, the company, together with scientists from Icahn School of Medicine at Mount Sinai and the Neurology and Neurosurgery Department at Utrecht University, published a paper offering a framework for how to develop BCIs for patients with severe paralysis – those who can't use their upper limbs to type or use digital devices.
Three months ago, Synchron announced the enrollment of six patients in a study called COMMAND based in the U.S. The company will seek approval next year from the FDA to make the Stentrode available for sale commercially. Meanwhile, other companies are making progress in the field of BCIs. In August, Neuralink announced a $280 million financing round, the biggest fundraiser yet in the field. Last December, Synchron announced a $75 million financing round. “One thing I can promise you, in five years from now, we’re not going to be where we are today. We're going to be in a very different place,” says Elad I. Levy, professor of neurosurgery and radiology at State University of New York in Buffalo.
The risk of hacking exists, always. Cybercriminals, for example, might steal sensitive personal data for financial reasons, blackmailing, or to spread malware to other connected devices while extremist groups could potentially hack BCIs to manipulate individuals into supporting their causes or carrying out actions on their behalf.
“The prospect of bestowing individuals with paralysis a renewed avenue for communication and motor functionality is a step forward in neurotech,” says Hayley Nelson, a neuroscientist and founder of The Academy of Cognitive and Behavioral Neuroscience. “It is an exciting breakthrough in a world of devastating, scary diseases,” says Neil McArthur, a professor of philosophy and director of the Centre for Professional and Applied Ethics at the University of Manitoba. “To connect with the world when you are trapped inside your body is incredible.”
While the benefits for the paraplegic community are promising, the Stentrode’s long-term effectiveness and overall impact needs more research on safety. “Potential risks like inflammation, damage to neural tissue, or unexpected shifts in synaptic transmission due to the implant warrant thorough exploration,” Nelson says.
There are also concens about data privacy concerns and the policies of companies to safeguard information processed through BCIs. “Often, Big Tech is ahead of the regulators because the latter didn’t envisage such a turn of events...and companies take advantage of the lack of legal framework to push forward,” McArthur says. Hacking is another risk. Cybercriminals could steal sensitive personal data for financial reasons, blackmailing, or to spread malware to other connected devices. Extremist groups could potentially hack BCIs to manipulate individuals into supporting their causes or carrying out actions on their behalf.
“We have to protect patient identity, patient safety and patient integrity,” Levy says. “In the same way that we protect our phones or computers from hackers, we have to stay ahead with anti-hacking software.” Even so, Levy thinks the anticipated benefits for the quadriplegic community outweigh the potential risks. “We are on the precipice of an amazing technology. In the future, we would be able to connect patients to peripheral devices that enhance their quality of life.”
In the near future, the Stentrode could enable patients to use the Stentrode to activate their wheelchairs, iPods or voice modulators. Synchron's focus is on using its BCI to help patients with significant mobility restrictions—not to enhance the lives of healthy people without any illnesses. Levy says we are not prepared for the implications of endowing people with superpowers.
I wondered what Gorham thought about that. “Pardon my question, but do you feel like you have sort of transcended human nature, being the first in a big line of cybernetic people doing marvelous things with their mind only?” was my last question to Gorham.
A slight smile formed on his lips. In less than a minute, he typed: “I do a little.”
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.