Across the country, schools are wrestling with the difficult choice of whether to reopen, and how to do it with reduced risk. In Kalamazoo, Michigan—not far from one the main sites where Pfizer is frantically manufacturing vaccines—they plan to stay virtual through the end of the school year. In Iowa, a state without a mask mandate, kids can now go back to in-person learning full time. Meanwhile, in a school district in San Mateo County, California, that borders Silicon Valley, there’s no clear decision—and low-income and affluent parents are clashing over what to do.
It’s been a difficult journey. Since March 2020, when most schools closed, districts have been asked to adjust over and over—to new science about how the virus behaves, new policy recommendations, and the different needs of families, kids, teachers, and staff.
Now, as President Biden forges ahead with his promise to reopen most schools within his first 100 days, the debates sound as complicated as ever—and offer a glimpse into many of the difficulties of reopening society at large.
The limits of “guidance”
Schools across the country have looked to the Centers for Disease Control and Prevention for guidance on how to operate in the pandemic. In its latest recommendations, the CDC says a lot of the things we’ve heard all year: that everyone in a school building should wear masks, stay at least six feet apart, and wash their hands frequently. But schools have found that even when guidelines seem relatively straightforward on paper, they are often much harder—or downright impossible—to put into practice.
“There’s a difference between public health mitigation policies when we think them through and when we write them down, and then when we try to implement them,” says Theresa Chapple, an epidemiologist in Washington, DC. “We see that there are barriers at play.”
Chapple points to a recent study by the CDC that looked at elementary schools in Georgia. After just 24 days of in-person learning, the researchers found nine clusters of covid-19 cases that could be linked back to the school. In all, about 45 students and teachers tested positive. How did that happen? Classroom layouts and class sizes meant physical distancing wasn’t possible, so students were less than three feet apart, separated only by plastic dividers. And though students and teachers mostly wore masks, students had to eat lunch in their classrooms.
Researchers also note that teachers and students may have infected each other “during small group instruction sessions in which educators worked in close proximity to students.”
Following the CDC’s best practices might be inherently difficult, but it’s also complicated by the fact that they are just guidelines: states and other jurisdictions make the rules, and those often conflict with what the CDC says to do. Since February 15, Iowa schools have been required to offer fully in-person learning options that some school officials say make distancing impossible. Because the state no longer has a mask mandate, students aren’t required to wear masks in school.
Jurisdictions following all these different policies have one thing in common: although case totals have dipped since their peak in January, the vast majority of the US still has substantial or high community spread. A big takeaway from the CDC’s latest guidance is that high community transmission is linked to increased risk in schools.
“If we are opening schools,” Chapple says, “we are saying that there’s an acceptable amount of spread that we will take in order for children to be educated.”
Meeting different needs
Some schools are trying alternative tactics that they hope will reduce the risks associated with in-person learning.
In Sharon, a Massachusetts town just south of Boston where about 60% of public school students are still learning remotely, pods of students and staff are called down to a central location in their school building twice a week for voluntary covid-19 testing. One by one, children as young as five turn up, sanitize their hands, lower their mask, swab their own nostrils, and place their swab in a single test tube designated for their whole cohort. To make room for everyone, sometimes even the principal’s office becomes a testing site: one person in, one person out. The tubes are then sent to a lab for something called “pooled testing.”
Pooled testing allows a small group of samples to be tested for covid all at once. In Sharon, each tube holds anywhere from 5 to 25 samples. If the test for that small group comes back negative, the whole group is cleared. If it’s positive, each group member is tested until the positive individual is found. Meg Dussault, the district’s acting superintendent, says each pool test costs the school between $5 and $50, and over a third of Sharon Public Schools students and staff participate.
“I’ve seen the benefits of this,” she says “And I believe it’s essential.”
Because schools are funded unequally and largely through taxes, access to resources is a common theme in discussions of school reopening. The state paid for Sharon’s pilot period, but not every district or school has the money or staffing to mount large-scale programs—and Dussault says the district will need to foot the bill for any testing once this program ends in April. It will also need to keep relying on the goodwill of the parent volunteers who wrangle students and swabs for testing each week.
In the seven weeks since pooled testing began, Dussault says, only one batch has come back positive. It’s given her peace of mind.
And even with mitigation measures in place, there are stark demographic differences in opinion on reopening. A recent Pew study found that Black, Asian, and Hispanic adults are more likely to support holding off until teachers have access to vaccines. Those groups are also more likely than white adults to say that the risk of covid-19 transmission “should be given a lot of consideration” when weighing reopening.
Chapple worries that these parents’ concerns will be overlooked, or that funds for remote learning will dwindle because some districts decide to move to in-person learning.
She says: “School districts need to keep in mind that if they’re reopening but a small percentage of their minority students are coming back, what does that look like in terms of equity?”
These robots know when to ask for help
A new training model, dubbed “KnowNo,” aims to address this problem by teaching robots to ask for our help when orders are unclear. At the same time, it ensures they seek clarification only when necessary, minimizing needless back-and-forth. The result is a smart assistant that tries to make sure it understands what you want without bothering you too much.
Andy Zeng, a research scientist at Google DeepMind who helped develop the new technique, says that while robots can be powerful in many specific scenarios, they are often bad at generalized tasks that require common sense.
For example, when asked to bring you a Coke, the robot needs to first understand that it needs to go into the kitchen, look for the refrigerator, and open the fridge door. Conventionally, these smaller substeps had to be manually programmed, because otherwise the robot would not know that people usually keep their drinks in the kitchen.
That’s something large language models (LLMs) could help to fix, because they have a lot of common-sense knowledge baked in, says Zeng.
Now when the robot is asked to bring a Coke, an LLM, which has a generalized understanding of the world, can generate a step-by-step guide for the robot to follow.
The problem with LLMs, though, is that there’s no way to guarantee that their instructions are possible for the robot to execute. Maybe the person doesn’t have a refrigerator in the kitchen, or the fridge door handle is broken. In these situations, robots need to ask humans for help.
KnowNo makes that possible by combining large language models with statistical tools that quantify confidence levels.
When given an ambiguous instruction like “Put the bowl in the microwave,” KnowNo first generates multiple possible next actions using the language model. Then it creates a confidence score predicting the likelihood that each potential choice is the best one.
The Download: inside the first CRISPR treatment, and smarter robots
The news: A new robot training model, dubbed “KnowNo,” aims to teach robots to ask for our help when orders are unclear. At the same time, it ensures they seek clarification only when necessary, minimizing needless back-and-forth. The result is a smart assistant that tries to make sure it understands what you want without bothering you too much.
Why it matters: While robots can be powerful in many specific scenarios, they are often bad at generalized tasks that require common sense. That’s something large language models could help to fix, because they have a lot of common-sense knowledge baked in. Read the full story.
Medical microrobots that travel inside the body are (still) on their way
The human body is a labyrinth of vessels and tubing, full of barriers that are difficult to break through. That poses a serious hurdle for doctors. Illness is often caused by problems that are hard to visualize and difficult to access. But imagine if we could deploy armies of tiny robots into the body to do the job for us. They could break up hard-to-reach clots, deliver drugs to even the most inaccessible tumors, and even help guide embryos toward implantation.
We’ve been hearing about the use of tiny robots in medicine for years, maybe even decades. And they’re still not here. But experts are adamant that medical microbots are finally coming, and that they could be a game changer for a number of serious diseases. Read the full story.
5 things we didn’t put on our 2024 list of 10 Breakthrough Technologies
We haven’t always been right (RIP, Baxter), but we’ve often been early to spot important areas of progress (we put natural-language processing on our very first list in 2001; today this technology underpins large language models and generative AI tools like ChatGPT).
Every year, our reporters and editors nominate technologies that they think deserve a spot, and we spend weeks debating which ones should make the cut. Here are some of the technologies we didn’t pick this time—and why we’ve left them off, for now.
New drugs for Alzheimer’s disease
Alzmeiher’s patients have long lacked treatment options. Several new drugs have now been proved to slow cognitive decline, albeit modestly, by clearing out harmful plaques in the brain. In July, the FDA approved Leqembi by Eisai and Biogen, and Eli Lilly’s donanemab could soon be next. But the drugs come with serious side effects, including brain swelling and bleeding, which can be fatal in some cases. Plus, they’re hard to administer—patients receive doses via an IV and must receive regular MRIs to check for brain swelling. These drawbacks gave us pause.
Sustainable aviation fuel
Alternative jet fuels made from cooking oil, leftover animal fats, or agricultural waste could reduce emissions from flying. They have been in development for years, and scientists are making steady progress, with several recent demonstration flights. But production and use will need to ramp up significantly for these fuels to make a meaningful climate impact. While they do look promising, there wasn’t a key moment or “breakthrough” that merited a spot for sustainable aviation fuels on this year’s list.
One way to counteract global warming could be to release particles into the stratosphere that reflect the sun’s energy and cool the planet. That idea is highly controversial within the scientific community, but a few researchers and companies have begun exploring whether it’s possible by launching a series of small-scale high-flying tests. One such launch prompted Mexico to ban solar geoengineering experiments earlier this year. It’s not really clear where geoengineering will go from here or whether these early efforts will stall out. Amid that uncertainty, we decided to hold off for now.