Why Are Autism Rates Steadily Rising?
Stefania Sterling was just 21 when she had her son, Charlie. She was young and healthy, with no genetic issues apparent in either her or her husband's family, so she expected Charlie to be typical.
"It is surprising that the prevalence of a significant disorder like autism has risen so consistently over a relatively brief period."
It wasn't until she went to a Mommy and Me music class when he was one, and she saw all the other one-year-olds walking, that she realized how different her son was. He could barely crawl, didn't speak, and made no eye contact. By the time he was three, he was diagnosed as being on the lower functioning end of the autism spectrum.
She isn't sure why it happened – and researchers, too, are still trying to understand the basis of the complex condition. Studies suggest that genes can act together with influences from the environment to affect development in ways that lead to Autism Spectrum Disorder (ASD). But rates of ASD are rising dramatically, making the need to figure out why it's happening all the more urgent.
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Indeed, the CDC's latest autism report, released last week, which uses 2016 data, found that the prevalence of ASD in four-year-old children was one in 64 children, or 15.6 affected children per 1,000. That's more than the 14.1 rate they found in 2014, for the 11 states included in the study. New Jersey, as in years past, was the highest, with 25.3 per 1,000, compared to Missouri, which had just 8.8 per 1,000.
The rate for eight-year-olds had risen as well. Researchers found the ASD prevalence nationwide was 18.5 per 1,000, or one in 54, about 10 percent higher than the 16.8 rate found in 2014. New Jersey, again, was the highest, at one in 32 kids, compared to Colorado, which had the lowest rate, at one in 76 kids. For New Jersey, that's a 175 percent rise from the baseline number taken in 2000, when the state had just one in 101 kids.
"It is surprising that the prevalence of a significant disorder like autism has risen so consistently over a relatively brief period," said Walter Zahorodny, an associate professor of pediatrics at Rutgers New Jersey Medical School, who was involved in collecting the data.
The study echoed the findings of a surprising 2011 study in South Korea that found 1 in every 38 students had ASD. That was the the first comprehensive study of autism prevalence using a total population sample: A team of investigators from the U.S., South Korea, and Canada looked at 55,000 children ages 7 to 12 living in a community in South Korea and found that 2.64 percent of them had some level of autism.
Searching for Answers
Scientists can't put their finger on why rates are rising. Some say it's better diagnosis. That is, it's not that more people have autism. It's that we're better at detecting it. Others attribute it to changes in the diagnostic criteria. Specifically, the May 2013 update of the Diagnostic and Statistical Manual of Mental Disorders-5 -- the standard classification of mental disorders -- removed the communication deficit from the autism definition, which made more children fall under that category. Cynical observers believe physicians and therapists are handing out the diagnosis more freely to allow access to services available only to children with autism, but that are also effective for other children.
Alycia Halladay, chief science officer for the Autism Science Foundation in New York, said she wishes there were just one answer, but there's not. While she believes the rising ASD numbers are due in part to factors like better diagnosis and a change in the definition, she does not believe that accounts for the entire rise in prevalence. As for the high numbers in New Jersey, she said the state has always had a higher prevalence of autism compared to other states. It is also one of the few states that does a good job at recording cases of autism in its educational records, meaning that children in New Jersey are more likely to be counted compared to kids in other states.
"Not every state is as good as New Jersey," she said. "That accounts for some of the difference compared to elsewhere, but we don't know if it's all of the difference in prevalence, or most of it, or what."
"What we do know is that vaccinations do not cause autism."
There is simply no defined proven reason for these increases, said Scott Badesch, outgoing president and CEO of the Autism Society of America.
"There are suggestions that it is based on better diagnosis, but there are also suggestions that the incidence of autism is in fact increasing due to reasons that have yet been determined," he said, adding, "What we do know is that vaccinations do not cause autism."
Zahorodny, the pediatrics professor, believes something is going on beyond better detection or evolving definitions.
"Changes in awareness and shifts in how children are identified or diagnosed are relevant, but they only take you so far in accounting for an increase of this magnitude," he said. "We don't know what is driving the surge in autism recorded by the ADDM Network and others."
He suggested that the increase in prevalence could be due to non-genetic environmental triggers or risk factors we do not yet know about, citing possibilities including parental age, prematurity, low birth rate, multiplicity, breech presentation, or C-section delivery. It may not be one, but rather several factors combined, he said.
"Increases in ASD prevalence have affected the whole population, so the triggers or risks must be very widely dispersed across all strata," he added.
There are studies that find new risk factors for ASD almost on a daily basis, said Idan Menashe, assistant professor in the Department of Health at Ben-Gurion University of the Negev, the fastest growing research university in Israel.
"There are plenty of studies that find new genetic variants (and new genes)," he said. In addition, various prenatal and perinatal risk factors are associated with a risk of ASD. He cited a study his university conducted last year on the relationship between C-section births and ASD, which found that exposure to general anesthesia may explain the association.
Whatever the cause, health practitioners are seeing the consequences in real time.
"People say rates are higher because of the changes in the diagnostic criteria," said Dr. Roseann Capanna-Hodge, a psychologist in Ridgefield, CT. "And they say it's easier for children to get identified. I say that's not the truth and that I've been doing this for 30 years, and that even 10 years ago, I did not see the level of autism that I do see today."
Sure, we're better at detecting autism, she added, but the detection improvements have largely occurred at the low- to mid- level part of the spectrum. The higher rates of autism are occurring at the more severe end, in her experience.
A Polarizing Theory
Among the more controversial risk factors scientists are exploring is the role environmental toxins may play in the development of autism. Some scientists, doctors and mental health experts suspect that toxins like heavy metals, pesticides, chemicals, or pollution may interrupt the way genes are expressed or the way endocrine systems function, manifesting in symptoms of autism. But others firmly resist such claims, at least until more evidence comes forth. To date, studies have been mixed and many have been more associative than causative.
"Today, scientists are still trying to figure out whether there are other environmental changes that can explain this rise, but studies of this question didn't provide any conclusive answer," said Menashe, who also serves as the scientific director of the National Autism Research Center at BGU.
"It's not everything that makes Charlie. He's just like any other kid."
That inconclusiveness has not dissuaded some doctors from taking the perspective that toxins do play a role. "Autism rates are rising because there is a mismatch between our genes and our environment," said Julia Getzelman, a pediatrician in San Francisco. "The majority of our evolution didn't include the kinds of toxic hits we are experiencing. The planet has changed drastically in just the last 75 years –- it has become more and more polluted with tens of thousands of unregulated chemicals being used by industry that are having effects on our most vulnerable."
She cites BPA, an industrial chemical that has been used since the 1960s to make certain plastics and resins. A large body of research, she says, has shown its impact on human health and the endocrine system. BPA binds to our own hormone receptors, so it may negatively impact the thyroid and brain. A study in 2015 was the first to identify a link between BPA and some children with autism, but the relationship was associative, not causative. Meanwhile, the Food and Drug Administration maintains that BPA is safe at the current levels occurring in food, based on its ongoing review of the available scientific evidence.
Michael Mooney, President of St. Louis-based Delta Genesis, a non-profit organization that treats children struggling with neurodevelopmental delays like autism, suspects a strong role for epigenetics, which refers to changes in how genes are expressed as a result of environmental influences, lifestyle behaviors, age, or disease states.
He believes some children are genetically predisposed to the disorder, and some unknown influence or combination of influences pushes them over the edge, triggering epigenetic changes that result in symptoms of autism.
For Stefania Sterling, it doesn't really matter how or why she had an autistic child. That's only one part of Charlie.
"It's not everything that makes Charlie," she said. "He's just like any other kid. He comes with happy moments. He comes with sad moments. Just like my other three kids."
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.