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.]
Story by Big Think
For most of history, artificial intelligence (AI) has been relegated almost entirely to the realm of science fiction. Then, in late 2022, it burst into reality — seemingly out of nowhere — with the popular launch of ChatGPT, the generative AI chatbot that solves tricky problems, designs rockets, has deep conversations with users, and even aces the Bar exam.
But the truth is that before ChatGPT nabbed the public’s attention, AI was already here, and it was doing more important things than writing essays for lazy college students. Case in point: It was key to saving the lives of tens of millions of people.
AI-designed mRNA vaccines
As Dave Johnson, chief data and AI officer at Moderna, told MIT Technology Review‘s In Machines We Trust podcast in 2022, AI was integral to creating the company’s highly effective mRNA vaccine against COVID. Moderna and Pfizer/BioNTech’s mRNA vaccines collectively saved between 15 and 20 million lives, according to one estimate from 2022.
Johnson described how AI was hard at work at Moderna, well before COVID arose to infect billions. The pharmaceutical company focuses on finding mRNA therapies to fight off infectious disease, treat cancer, or thwart genetic illness, among other medical applications. Messenger RNA molecules are essentially molecular instructions for cells that tell them how to create specific proteins, which do everything from fighting infection, to catalyzing reactions, to relaying cellular messages.
Johnson and his team put AI and automated robots to work making lots of different mRNAs for scientists to experiment with. Moderna quickly went from making about 30 per month to more than one thousand. They then created AI algorithms to optimize mRNA to maximize protein production in the body — more bang for the biological buck.
For Johnson and his team’s next trick, they used AI to automate science, itself. Once Moderna’s scientists have an mRNA to experiment with, they do pre-clinical tests in the lab. They then pore over reams of data to see which mRNAs could progress to the next stage: animal trials. This process is long, repetitive, and soul-sucking — ill-suited to a creative scientist but great for a mindless AI algorithm. With scientists’ input, models were made to automate this tedious process.
“We don’t think about AI in the context of replacing humans,” says Dave Johnson, chief data and AI officer at Moderna. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
All these AI systems were in put in place over the past decade. Then COVID showed up. So when the genome sequence of the coronavirus was made public in January 2020, Moderna was off to the races pumping out and testing mRNAs that would tell cells how to manufacture the coronavirus’s spike protein so that the body’s immune system would recognize and destroy it. Within 42 days, the company had an mRNA vaccine ready to be tested in humans. It eventually went into hundreds of millions of arms.
Biotech harnesses the power of AI
Moderna is now turning its attention to other ailments that could be solved with mRNA, and the company is continuing to lean on AI. Scientists are still coming to Johnson with automation requests, which he happily obliges.
“We don’t think about AI in the context of replacing humans,” he told the Me, Myself, and AI podcast. “We always think about it in terms of this human-machine collaboration, because they’re good at different things. Humans are really good at creativity and flexibility and insight, whereas machines are really good at precision and giving the exact same result every single time and doing it at scale and speed.”
Moderna, which was founded as a “digital biotech,” is undoubtedly the poster child of AI use in mRNA vaccines. Moderna recently signed a deal with IBM to use the company’s quantum computers as well as its proprietary generative AI, MoLFormer.
Moderna’s success is encouraging other companies to follow its example. In January, BioNTech, which partnered with Pfizer to make the other highly effective mRNA vaccine against COVID, acquired the company InstaDeep for $440 million to implement its machine learning AI across its mRNA medicine platform. And in May, Chinese technology giant Baidu announced an AI tool that designs super-optimized mRNA sequences in minutes. A nearly countless number of mRNA molecules can code for the same protein, but some are more stable and result in the production of more proteins. Baidu’s AI, called “LinearDesign,” finds these mRNAs. The company licensed the tool to French pharmaceutical company Sanofi.
Writing in the journal Accounts of Chemical Research in late 2021, Sebastian M. Castillo-Hair and Georg Seelig, computer engineers who focus on synthetic biology at the University of Washington, forecast that AI machine learning models will further accelerate the biotechnology research process, putting mRNA medicine into overdrive to the benefit of all.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
Opioid prescription policies may hurt those in chronic pain
Tinu Abayomi-Paul works as a writer and activist, plus one unwanted job: Trying to fill her opioid prescription. She says that some pharmacists laugh and tell her that no one needs the amount of pain medication that she is seeking. Another pharmacist near her home in Venus, Tex., refused to fill more than seven days of a 30-day prescription.
To get a new prescription—partially filled opioid prescriptions can’t be dispensed later—Abayomi-Paul needed to return to her doctor’s office. But without her medication, she was having too much pain to travel there, much less return to the pharmacy. She rationed out the pills over several weeks, an agonizing compromise that left her unable to work, interact with her children, sleep restfully, or leave the house. “Don’t I deserve to do more than survive?” she says.
Abayomi-Paul’s pain results from a degenerative spine disorder, chronic lymphocytic leukemia, and more than a dozen other diagnoses and disabilities. She is part of a growing group of people with chronic pain who have been negatively impacted by the fallout from efforts to prevent opioid overdose deaths.
Guidelines for dispensing these pills are complicated because many opioids, like codeine, oxycodone, and morphine, are prescribed legally for pain. Yet, deaths from opioids have increased rapidly since 1999 and become a national emergency. Many of them, such as heroin, are used illegally. The CDC identified three surges in opioid use: an increase in opioid prescriptions in the ‘90s, a surge of heroin around 2010, and an influx of fentanyl and other powerful synthetic opioids in 2013.
As overdose deaths grew, so did public calls to address them, prompting the CDC to change its prescription guidelines in 2016. The new guidelines suggested limiting medication for acute pain to a seven-day supply, capping daily doses of morphine, and other restrictions. Some statistics suggest that these policies have worked; from 2016 to 2019, prescriptions for opiates fell 44 percent. Physicians also started progressively lowering opioid doses for patients, a practice called tapering. A study tracking nearly 100,000 Medicare subscribers on opioids found that about 13 percent of patients were tapering in 2012, and that number increased to about 23 percent by 2017.
But some physicians may be too aggressive with this tapering strategy. About one in four people had doses reduced by more than 10 percent per week, a rate faster than the CDC recommends. The approach left people like Abayomi-Paul without the medication they needed. Every year, Abayomi-Paul says, her prescriptions are harder to fill. David Brushwood, a pharmacy professor who specializes in policy and outcomes at the University of Florida in Gainesville, says opioid dosing isn’t one-size-fits-all. “Patients need to be taken care of individually, not based on what some government agency says they need,” he says.
‘This is not survivable’
Health policy and disability rights attorney Erin Gilmer advocated for people with pain, using her own experience with chronic pain and a host of medical conditions as a guidepost. She launched an advocacy website, Healthcare as a Human Right, and shared her struggles on Twitter: “This pain is more than anything I've endured before and I've already been through too much. Yet because it's not simply identified no one believes it's as bad as it is. This is not survivable.”
When her pain dramatically worsened midway through 2021, Gilmer’s posts grew ominous: “I keep thinking it can't possibly get worse but somehow every day is worse than the last.”
The CDC revised its guidelines in 2022 after criticisms that people with chronic pain were being undertreated, enduring dangerous withdrawal symptoms, and suffering psychological distress. (Long-term opioid use can cause physical dependency, an adaptive reaction that is different than the compulsive misuse associated with a substance use disorder.) It was too late for Gilmer. On July 7, 2021, the 38-year-old died by suicide.
Last August, an Ohio district court ruling set forth a new requirement for Walgreens, Walmart, and CVS pharmacists in two counties. These pharmacists must now document opioid prescriptions that are turned down, even for customers who have no previous purchases at that pharmacy, and they’re required to share this information with other locations in the same chain. None of the three pharmacies responded to an interview request from Leaps.org.
In a practice called red flagging, pharmacists may label a prescription suspicious for a variety of reasons, such as if a pharmacist observes an unusually high dose, a long distance from the patient’s home to the pharmacy, or cash payment. Pharmacists may question patients or prescribers to resolve red flags but, regardless of the explanation, they’re free to refuse to fill a prescription.
As the risk of litigation has grown, so has finger-pointing, says Seth Whitelaw, a compliance consultant at Whitelaw Compliance Group in West Chester, PA, who advises drug, medical device, and biotech companies. Drugmakers accused in National Prescription Opioid Litigation (NPOL), a complex set of thousands of cases on opioid epidemic deaths, which includes the Ohio district case, have argued that they shouldn’t be responsible for the large supply of opiates and overdose deaths. Yet, prosecutors alleged that these pharmaceutical companies hid addiction and overdose risks when labeling opioids, while distributors and pharmacists failed to identify suspicious orders or scripts.
Patients and pharmacists fear red flags
The requirements that pharmacists document prescriptions they refuse to fill so far only apply to two counties in Ohio. But Brushwood fears they will spread because of this precedent, and because there’s no way for pharmacists to predict what new legislation is on the way. “There is no definition of a red flag, there are no lists of red flags. There is no instruction on what to do when a red flag is detected. There’s no guidance on how to document red flags. It is a standardless responsibility,” Brushwood says. This adds trepidation for pharmacists—and more hoops to jump through for patients.
“I went into the doctor one day here and she said, ‘I'm going to stop prescribing opioids to all my patients effective immediately,” Nicolson says.
“We now have about a dozen studies that show that actually ripping somebody off their medication increases their risk of overdose and suicide by three to five times, destabilizes their health and mental health, often requires some hospitalization or emergency care, and can cause heart attacks,” says Kate Nicolson, founder of the National Pain Advocacy Center based in Boulder, Colorado. “It can kill people.” Nicolson was in pain for decades due to a surgical injury to the nerves leading to her spinal cord before surgeries fixed the problem.
Another issue is that primary care offices may view opioid use as a reason to turn down new patients. In a 2021 study, secret shoppers called primary care clinics in nine states, identifying themselves as long-term opioid users. When callers said their opioids were discontinued because their former physician retired, as opposed to an unspecified reason, they were more likely to be offered an appointment. Even so, more than 40 percent were refused an appointment. The study authors say their findings suggest that some physicians may try to avoid treating people who use opioids.
Abayomi-Paul says red flagging has changed how she fills prescriptions. “Once I go to one place, I try to [continue] going to that same place because of the amount of records that I have and making sure my medications don’t conflict,” Abayomi-Paul says.
Nicolson moved to Colorado from Washington D.C. in 2015, before the CDC issued its 2016 guidelines. When the guidelines came out, she found the change to be shockingly abrupt. “I went into the doctor one day here and she said, ‘I'm going to stop prescribing opioids to all my patients effective immediately.’” Since then, she’s spoken with dozens of patients who have been red-flagged or simply haven’t been able to access pain medication.
Despite her expertise, Nicolson isn’t positive she could successfully fill an opioid prescription today even if she needed one. At this point, she’s not sure exactly what various pharmacies would view as a red flag. And she’s not confident that these red flags even work. “You can have very legitimate reasons for being 50 miles away or having to go to multiple pharmacies, given that there are drug shortages now, as well as someone refusing to fill [a prescription.] It doesn't mean that you’re necessarily ‘drug seeking.’”
While there’s no easy solution. Whitelaw says clarifying the role of pharmacists and physicians in patient access to opioids could help people get the medication they need. He is seeking policy changes that focus on the needs of people in pain more than the number of prescriptions filled. He also advocates standardizing the definition of red flags and procedures for resolving them. Still, there will never be a single policy that can be applied to all people, explains Brushwood, the University of Florida professor. “You have to make a decision about each individual prescription.”