How sharing, hearing, and remembering positive stories can help shape our brains for the better
Across cultures and through millennia, human beings have always told stories. Whether it’s a group of boy scouts around a campfire sharing ghost stories or the paleolithic Cro-Magnons etching pictures of bison on cave walls, researchers believe that storytelling has been universal to human beings since the development of language.
But storytelling was more than just a way for our ancestors to pass the time. Researchers believe that storytelling served an important evolutionary purpose, helping humans learn empathy, share important information (such as where predators were or what berries were safe to eat), as well as strengthen social bonds. Quite literally, storytelling has made it possible for the human race to survive.
Today, neuroscientists are discovering that storytelling is just as important now as it was millions of years ago. Particularly in sharing positive stories, humans can more easily form relational bonds, develop a more flexible perspective, and actually grow new brain circuitry that helps us survive. Here’s how.
How sharing stories positively impacts the brain
When human beings share stories, it increases the levels of certain neurochemicals in the brain, neuroscientists have found. In a 2021 study published in Proceedings of the National Academy of Sciences (PNAS), Swedish researchers found that simply hearing a story could make hospitalized children feel better, compared to other hospitalized children who played a riddle game for the same amount of time. In their research, children in the intensive care unit who heard stories for just 30 minutes had higher levels of oxytocin, a hormone that promotes positive feelings and is linked to relaxation, trust, social connectedness, and overall psychological stability. Furthermore, the same children showed lower levels of cortisol, a hormone associated with stress. Afterward, the group of children who heard stories tended to describe their hospital experiences more positively, and even reported lower levels of pain.
Annie Brewster, MD, knows the positive effect of storytelling from personal experience. An assistant professor at Harvard Medical School and the author of The Healing Power of Storytelling: Using Personal Narrative to Navigate Illness, Trauma, and Loss, Brewster started sharing her personal experience with chronic illness after being diagnosed with multiple sclerosis in 2001. In doing so, Brewster says it has enabled her to accept her diagnosis and integrate it into her identity. Brewster believes so much in the power of hearing and sharing stories that in 2013 she founded Health Story Collaborative, a forum for others to share their mental and physical health challenges.“I wanted to hear stories of people who had found ways to move forward in positive ways, in spite of health challenges,” Brewster said. In doing so, Brewster believes people with chronic conditions can “move closer to self-acceptance and self-love.”
While hearing and sharing positive stories has been shown to increase oxytocin and other “feel good” chemicals, simply remembering a positive story has an effect on our brains as well. Mark Hoelterhoff, PhD, a lecturer in clinical psychology at the University of Edinburgh, recalling and “savoring” a positive story, thought, or feedback “begins to create new brain circuitry—a new neural network that’s geared toward looking for the positive,” he says. Over time, other research shows, savoring positive stories or thoughts can literally change the shape of your brain, hard-wiring someone to see things in a more positive light.How stories can change your behavior
In 2009, Paul Zak, PhD, a neuroscientist and professor at Claremont Graduate University, set out to measure how storytelling can actually change human behavior for the better. In his study, Zak wanted to measure the behavioral effects of oxytocin, and did this by showing test subjects two short video clips designed to elicit an emotional response.
In the first video they showed the study participants, a father spoke to the camera about his two-year-old son, Ben, who had been diagnosed with terminal brain cancer. The father told the audience that he struggled to connect with and enjoy Ben, as Ben had only a few months left to live. In the end, the father finds the strength to stay emotionally connected to his son until he dies.
The second video clip, however, was much less emotional. In that clip, the same father and son are shown spending the day at the zoo. Ben is only suggested to have cancer (he is bald from chemotherapy and referred to as a ‘miracle’, but the cancer isn’t mentioned directly). The second story lacked the dramatic narrative arc of the first video.
Zak’s team took blood before and after the participants watched one of the two videos and found that the first story increased the viewers’ cortisol and oxytocin, suggesting that they felt distress over the boy’s diagnosis and empathy toward the boy and his father. The second narrative, however, didn’t increase oxytocin or cortisol at all.
But Zak took the experiment a step further. After the movie clips, his team gave the study participants a chance to share money with a stranger in the lab. The participants who had an increase in cortisol and oxytocin were more likely to donate money generously. The participants who had increased cortisol and oxytocin were also more likely to donate money to a charity that works with children who are ill. Zak also found that the amount of oxytocin that was released was correlated with how much money people felt comfortable giving—in other words, the more oxytocin that was released, the more generous they felt, and the more money they donated.
How storytelling strengthens our bond with others
Sharing, hearing, and remembering stories can be a powerful tool for social change–not only in the way it changes our brain and our behavior, but also because it can positively affect our relationships with other people
Emotional stimulation from telling stories, writes Zak, is the foundation for empathy, and empathy strengthens our relationships with other people. “By knowing someone’s story—where they come from, what they do, and who you might know in common—relationships with strangers are formed.”
But why are these relationships important for humanity? Because human beings can use storytelling to build empathy and form relationships, it enables them to “engage in the kinds of large-scale cooperation that builds massive bridges and sends humans into space,” says Zak.
Storytelling, Zak found, and the oxytocin release that follows, also makes people more sensitive to social cues. This sensitivity not only motivates us to form relationships, but also to engage with other people and offer help, particularly if the other person seems to need help.
But as Zak found in his experiments, the type of storytelling matters when it comes to affecting relationships. Where Zak found that storytelling with a dramatic arc helps release oxytocin and cortisol, enabling people to feel more empathic and generous, other researchers have found that sharing happy stories allows for greater closeness between individuals and speakers. A group of Chinese researchers found that, compared to emotionally-neutral stories, happy stories were more “emotionally contagious.” Test subjects who heard happy stories had greater activation in certain areas of their brains, experienced more significant, positive changes in their mood, and felt a greater sense of closeness between themselves and the speaker.
“This finding suggests that when individuals are happy, they become less self-focused and then feel more intimate with others,” the authors of the study wrote. “Therefore, sharing happiness could strengthen interpersonal bonding.” The researchers went on to say that this could lead to developing better social networks, receiving more social support, and leading more successful social lives.
Since the start of the COVID pandemic, social isolation, loneliness, and resulting mental health issues have only gotten worse. In light of this, it’s safe to say that hearing, sharing, and remembering stories isn’t just something we can do for entertainment. Storytelling has always been central to the human experience, and now more than ever it’s become something crucial for our survival.
Want to know how you can reap the benefits of hearing happy stories? Keep an eye out for Upworthy’s first book, GOOD PEOPLE: Stories from the Best of Humanity, published by National Geographic/Disney, available on September 3, 2024. GOOD PEOPLE is a much-needed trove of life-affirming stories told straight from the heart. Handpicked from Upworthy’s community, these 101 stories speak to the breadth, depth, and beauty of the human experience, reminding us we have a lot more in common than we realize.
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.