To Make Science Engaging, We Need a Sesame Street for Adults
This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.
In the mid-1960s, a documentary producer in New York City wondered if the addictive jingles, clever visuals, slogans, and repetition of television ads—the ones that were captivating young children of the time—could be harnessed for good. Over the course of three months, she interviewed educators, psychologists, and artists, and the result was a bonanza of ideas.
Perhaps a new TV show could teach children letters and numbers in short animated sequences? Perhaps adults and children could read together with puppets providing comic relief and prompting interaction from the audience? And because it would be broadcast through a device already in almost every home, perhaps this show could reach across socioeconomic divides and close an early education gap?
Soon after Joan Ganz Cooney shared her landmark report, "The Potential Uses of Television in Preschool Education," in 1966, she was prototyping show ideas, attracting funding from The Carnegie Corporation, The Ford Foundation, and The Corporation for Public Broadcasting, and co-founding the Children's Television Workshop with psychologist Lloyd Morrisett. And then, on November 10, 1969, informal learning was transformed forever with the premiere of Sesame Street on public television.
For its first season, Sesame Street won three Emmy Awards and a Peabody Award. Its star, Big Bird, landed on the cover of Time Magazine, which called the show "TV's gift to children." Fifty years later, it's hard to imagine an approach to informal preschool learning that isn't Sesame Street.
And that approach can be boiled down to one word: Entertainment.
Despite decades of evidence from Sesame Street—one of the most studied television shows of all time—and more research from social science, psychology, and media communications, we haven't yet taken Ganz Cooney's concepts to heart in educating adults. Adults have news programs and documentaries and educational YouTube channels, but no Sesame Street. So why don't we? Here's how we can design a new kind of television to make science engaging and accessible for a public that is all too often intimidated by it.
We have to start from the realization that America is a nation of high-school graduates. By the end of high school, students have decided to abandon science because they think it's too difficult, and as a nation, we've made it acceptable for any one of us to say "I'm not good at science" and offload thinking to the ones who might be. So, is it surprising that a large number of Americans are likely to believe in conspiracy theories like the 25% that believe the release of COVID-19 was planned, the one in ten who believe the Moon landing was a hoax, or the 30–40% that think the condensation trails of planes are actually nefarious chemtrails? If we're meeting people where they are, the aim can't be to get the audience from an A to an A+, but from an F to a D, and without judgment of where they are starting from.
There's also a natural compulsion for a well-meaning educator to fill a literacy gap with a barrage of information, but this is what I call "factsplaining," and we know it doesn't work. And worse, it can backfire. In one study from 2014, parents were provided with factual information about vaccine safety, and it was the group that was already the most averse to vaccines that uniquely became even more averse.
Why? Our social identities and cognitive biases are stubborn gatekeepers when it comes to processing new information. We filter ideas through pre-existing beliefs—our values, our religions, our political ideologies. Incongruent ideas are rejected. Congruent ideas, no matter how absurd, are allowed through. We hear what we want to hear, and then our brains justify the input by creating narratives that preserve our identities. Even when we have all the facts, we can use them to support any worldview.
But social science has revealed many mechanisms for hijacking these processes through narrative storytelling, and this can form the foundation of a new kind of educational television.
Could new television series establish the baseline narratives for novel science like gene editing, quantum computing, or artificial intelligence?
As media creators, we can reject factsplaining and instead construct entertaining narratives that disrupt cognitive processes. Two-decade-old research tells us when people are immersed in entertaining fiction narratives, they loosen their defenses, opening a path for new information, editing attitudes, and inspiring new behavior. Where news about hot-button issues like climate change or vaccination might trigger resistance or a backfire effect, fiction can be crafted to be absorbing and, as a result, persuasive.
But the narratives can't be stuffed with information. They must be simplified. If this feels like the opposite of what an educator should be doing, it is possible to reduce the complexity of information, without oversimplification, through "exemplification," a framing device to tell the stories of individuals in specific circumstances that can speak to the greater issue without needing to explain it all. It's a technique you've seen used in biopics. The Discovery Channel true-crime miniseries Manhunt: Unabomber does many things well from a science storytelling perspective, including exemplifying the virtues of the scientific method through a character who argues for a new field of science, forensic linguistics, to catch one of the most notorious domestic terrorists in U.S. history.
We must also appeal to the audience's curiosity. We know curiosity is such a strong driver of human behavior that it can even counteract the biases put up by one's political ideology around subjects like climate change. If we treat science information like a product—and we should—advertising research tells us we can maximize curiosity though a Goldilocks effect. If the information is too complex, your show might as well be a PowerPoint presentation. If it's too simple, it's Sesame Street. There's a sweet spot for creating intrigue about new information when there's a moderate cognitive gap.
The science of "identification" tells us that the more the main character is endearing to a viewer, the more likely the viewer will adopt the character's worldview and journey of change. This insight further provides incentives to craft characters reflective of our audiences. If we accept our biases for what they are, we can understand why the messenger becomes more important than the message, because, without an appropriate messenger, the message becomes faint and ineffective. And research confirms that the stereotype-busting doctor-skeptic Dana Scully of The X-Files, a popular science-fiction series, was an inspiration for a generation of women who pursued science careers.
With these directions, we can start making a new kind of television. But is television itself still the right delivery medium? Americans do spend six hours per day—a quarter of their lives—watching video. And even with the rise of social media and apps, science-themed television shows remain popular, with four out of five adults reporting that they watch shows about science at least sometimes. CBS's The Big Bang Theory was the most-watched show on television in the 2017–2018 season, and Cartoon Network's Rick & Morty is the most popular comedy series among millennials. And medical and forensic dramas continue to be broadcast staples. So yes, it's as true today as it was in the 1980s when George Gerbner, the "cultivation theory" researcher who studied the long-term impacts of television images, wrote, "a single episode on primetime television can reach more people than all science and technology promotional efforts put together."
We know from cultivation theory that media images can shape our views of scientists. Quick, picture a scientist! Was it an old, white man with wild hair in a lab coat? If most Americans don't encounter research science firsthand, it's media that dictates how we perceive science and scientists. Characters like Sheldon Cooper and Rick Sanchez become the model. But we can correct that by representing professionals more accurately on-screen and writing characters more like Dana Scully.
Could new television series establish the baseline narratives for novel science like gene editing, quantum computing, or artificial intelligence? Or could new series counter the misinfodemics surrounding COVID-19 and vaccines through more compelling, corrective narratives? Social science has given us a blueprint suggesting they could. Binge-watching a show like the surreal NBC sitcom The Good Place doesn't replace a Ph.D. in philosophy, but its use of humor plants the seed of continued interest in a new subject. The goal of persuasive entertainment isn't to replace formal education, but it can inspire, shift attitudes, increase confidence in the knowledge of complex issues, and otherwise prime viewers for continued learning.
[Editor's Note: To read other articles in this special magazine issue, visit the beautifully designed e-reader version.]
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.
Here's how one doctor overcame extraordinary odds to help create the birth control pill
Dr. Percy Julian had so many personal and professional obstacles throughout his life, it’s amazing he was able to accomplish anything at all. But this hidden figure not only overcame these incredible obstacles, he also laid the foundation for the creation of the birth control pill.
Julian’s first obstacle was growing up in the Jim Crow-era south in the early part of the twentieth century, where racial segregation kept many African-Americans out of schools, libraries, parks, restaurants, and more. Despite limited opportunities and education, Julian was accepted to DePauw University in Indiana, where he majored in chemistry. But in college, Julian encountered another obstacle: he wasn’t allowed to stay in DePauw’s student housing because of segregation. Julian found lodging in an off-campus boarding house that refused to serve him meals. To pay for his room, board, and food, Julian waited tables and fired furnaces while he studied chemistry full-time. Incredibly, he graduated in 1920 as valedictorian of his class.
After graduation, Julian landed a fellowship at Harvard University to study chemistry—but here, Julian ran into yet another obstacle. Harvard thought that white students would resent being taught by Julian, an African-American man, so they withdrew his teaching assistantship. Julian instead decided to complete his PhD at the University of Vienna in Austria. When he did, he became one of the first African Americans to ever receive a PhD in chemistry.
Julian received offers for professorships, fellowships, and jobs throughout the 1930s, due to his impressive qualifications—but these offers were almost always revoked when schools or potential employers found out Julian was black. In one instance, Julian was offered a job at the Institute of Paper Chemistory in Appleton, Wisconsin—but Appleton, like many cities in the United States at the time, was known as a “sundown town,” which meant that black people weren’t allowed to be there after dark. As a result, Julian lost the job.
During this time, Julian became an expert at synthesis, which is the process of turning one substance into another through a series of planned chemical reactions. Julian synthesized a plant compound called physostigmine, which would later become a treatment for an eye disease called glaucoma.
In 1936, Julian was finally able to land—and keep—a job at Glidden, and there he found a way to extract soybean protein. This was used to produce a fire-retardant foam used in fire extinguishers to smother oil and gasoline fires aboard ships and aircraft carriers, and it ended up saving the lives of thousands of soldiers during World War II.
At Glidden, Julian found a way to synthesize human sex hormones such as progesterone, estrogen, and testosterone, from plants. This was a hugely profitable discovery for his company—but it also meant that clinicians now had huge quantities of these hormones, making hormone therapy cheaper and easier to come by. His work also laid the foundation for the creation of hormonal birth control: Without the ability to synthesize these hormones, hormonal birth control would not exist.
Julian left Glidden in the 1950s and formed his own company, called Julian Laboratories, outside of Chicago, where he manufactured steroids and conducted his own research. The company turned profitable within a year, but even so Julian’s obstacles weren’t over. In 1950 and 1951, Julian’s home was firebombed and attacked with dynamite, with his family inside. Julian often had to sit out on the front porch of his home with a shotgun to protect his family from violence.
But despite years of racism and violence, Julian’s story has a happy ending. Julian’s family was eventually welcomed into the neighborhood and protected from future attacks (Julian’s daughter lives there to this day). Julian then became one of the country’s first black millionaires when he sold his company in the 1960s.
When Julian passed away at the age of 76, he had more than 130 chemical patents to his name and left behind a body of work that benefits people to this day.