The US has administered more than 118 million doses of covid-19 vaccines so far, and millions more are being injected every day. So far, demand from people who are desperate to get vaccinated has outstripped supply of the drugs, and when vaccine appointments are released, they’re quickly scooped up.
But jurisdictions across the country may soon face the opposite problem.
In some states, the shift from scarcity to abundance is already here. In Idaho, where 20% of people have gotten at least one shot, many appointments have gone unfilled, causing state officials to increase eligibility ahead of schedule. The state plans to open up appointments to those 55 and up beginning March 22.
In a March 16 media briefing, Idaho officials said they’re making appointments available to 200,000 or more people every other week. They remain hopeful that many Idahoans who’ve been hesitant about getting vaccinated will start getting in line now that the rollout is further along.
Meanwhile, some Native American communities are running weeks ahead of any US state when it comes to delivering vaccines. The Chickasaw Nation, for example, has successfully vaccinated so many of its 38,000 residents that it is now offering shots to anyone 16 and older—and even to the general public in Oklahoma.
This all means that America is racing toward the point at which so many people are resistant to the virus that it becomes much harder to spread.
This all means that America is racing toward the point at which so many people are resistant to the virus that it becomes much harder to spread. President Biden has set a goal that all states should be able to make every adult eligible for vaccination by May 1. (As for whatever may be left over, the administration plans to send millions of excess doses of the AstraZeneca vaccine to Canada and Mexico to fill their supply gaps.) Medical experts think we will need a vaccination rate of around 80% to reach the point where infections are dramatically reduced in the US, and projections show that 70% of Americans will be vaccinated by late June.
But those projections assume that everyone who is eligible will take a vaccine. A recent Pew study estimates, however, that only 69% of Americans want a shot. That means reaching the threshold will require efforts to understand why the “maybes” are hesitant and how their minds might be changed.
Understanding the hesitant
Data collected by the Delphi Group at Carnegie Mellon University could offer a road map for the coming months. In a survey of more than 1.9 million Americans, researchers found that although a rising share of people have gotten vaccinated or are willing to, around a quarter of unvaccinated adults are still hesitant. Alex Reinhart, assistant teaching professor of statistics and data science at Carnegie Mellon, hopes that research on who’s hesitant—and why—could help officials focus their efforts.
For example, the Delphi team found that trust in vaccines varied geographically. In southern states like Alabama, Mississippi, Georgia, and Louisiana, along with North Dakota and Wyoming, respondents were more likely to say they probably or definitely wouldn’t accept a vaccine if it were offered.
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 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.
—June Kim
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.
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.
Solar geoengineering
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.
