Whenever Eric Karl Oermann has to tell a patient about a terrible prognosis, their first question is always: "how long do I have?" Oermann would like to offer a precise answer, to provide some certainty and help guide treatment. But although he's one of the country's foremost experts in medical artificial intelligence, Oermann is still dependent on a computer algorithm that's often wrong.
Doctors are notoriously terrible at guessing how long their patients will live.
Artificial intelligence, now often called deep learning or neural networks, has radically transformed language and image processing. It's allowed computers to play chess better than the world's grand masters and outwit the best Jeopardy players. But it still can't precisely tell a doctor how long a patient has left – or how to help that person live longer.
Someday, researchers predict, computers will be able to watch a video of a patient to determine their health status. Doctors will no longer have to spend hours inputting data into medical records. And computers will do a better job than specialists at identifying tiny tumors, impending crises, and, yes, figuring out how long the patient has to live. Oermann, a neurosurgeon at Mount Sinai, says all that technology will allow doctors to spend more time doing what they do best: talking with their patients. "I want to see more deep learning and computers in a clinical setting," he says, "so there can be more human interaction." But those days are still at least three to five years off, Oermann and other researchers say.
Doctors are notoriously terrible at guessing how long their patients will live, says Nigam Shah, an associate professor at Stanford University and assistant director of the school's Center for Biomedical Informatics Research. Doctors don't want to believe that their patient – whom they've come to like – will die. "Doctors over-estimate survival many-fold," Shah says. "How do you go into work, in say, oncology, and not be delusionally optimistic? You have to be."
But patients near the end of life will get better treatment – and even live longer – if they are overseen by hospice or palliative care, research shows. So, instead of relying on human bias to select those whose lives are nearing their end, Shah and his colleagues showed that they could use a deep learning algorithm based on medical records to flag incoming patients with a life expectancy of three months to a year. They use that data to indicate who might need palliative care. Then, the palliative care team can reach out to treating physicians proactively, instead of relying on their referrals or taking the time to read extensive medical charts.
But, although the system works well, Shah isn't yet sure if such indicators actually get the appropriate patients into palliative care. He's recently partnered with a palliative care doctor to run a gold-standard clinical trial to test whether patients who are flagged by this algorithm are indeed a better match for palliative care.
"What is effective from a health system perspective might not be effective from a treating physician's perspective and might not be effective from the patient's perspective," Shah notes. "I don't have a good way to guess everybody's reaction without actually studying it." Whether palliative care is appropriate, for instance, depends on more than just the patient's health status. "If the patient's not ready, the family's not ready and the doctor's not ready, then you're just banging your head against the wall," Shah says. "Given limited capacity, it's a waste of resources" to put that person in palliative care.
The algorithm isn't perfect, but "on balance, it leads to better decisions more often."
Alexander Smith and Sei Lee, both palliative care doctors, work together at the University of California, San Francisco, to develop predictions for patients who come to the hospital with a complicated prognosis or a history of decline. Their algorithm, they say, helps decide if this patient's problems – which might include diabetes, heart disease, a slow-growing cancer, and memory issues – make them eligible for hospice. The algorithm isn't perfect, they both agree, but "on balance, it leads to better decisions more often," Smith says.
Bethany Percha, an assistant professor at Mount Sinai, says that an algorithm may tell doctors that their patient is trending downward, but it doesn't do anything to change that trajectory. "Even if you can predict something, what can you do about it?" Algorithms may be able to offer treatment suggestions – but not what specific actions will alter a patient's future, says Percha, also the chief technology officer of Precise Health Enterprise, a product development group within Mount Sinai. And the algorithms remain challenging to develop. Electronic medical records may be great at her hospital, but if the patient dies at a different one, her system won't know. If she wants to be certain a patient has died, she has to merge social security records of death with her system's medical records – a time-consuming and cumbersome process.
An algorithm that learns from biased data will be biased, Shah says. Patients who are poor or African American historically have had worse health outcomes. If researchers train an algorithm on data that includes those biases, they get baked into the algorithms, which can then lead to a self-fulfilling prophesy. Smith and Lee say they've taken race out of their algorithms to avoid this bias.
Age is even trickier. There's no question that someone's risk of illness and death goes up with age. But an 85-year-old who breaks a hip running a marathon should probably be treated very differently than an 85-year-old who breaks a hip trying to get out of a chair in a dementia care unit. That's why the doctor can never be taken out of the equation, Shah says. Human judgment will always be required in medical care and an algorithm should never be followed blindly, he says.
Experts say that the flaws in artificial intelligence algorithms shouldn't prevent people from using them – carefully.
Researchers are also concerned that their algorithms will be used to ration care, or that insurance companies will use their data to justify a rate increase. If an algorithm predicts a patient is going to end up back in the hospital soon, "who's benefitting from knowing a patient is going to be readmitted? Probably the insurance company," Percha says.
Still, Percha and others say, the flaws in artificial intelligence algorithms shouldn't prevent people from using them – carefully. "These are new and exciting tools that have a lot of potential uses. We need to be conscious about how to use them going forward, but it doesn't mean we shouldn't go down this road," she says. "I think the potential benefits outweigh the risks, especially because we've barely scratched the surface of what big data can do right now."
In the 1990s, a mysterious virus spread throughout the Massachusetts Institute of Technology Artificial Intelligence Lab—or that’s what the scientists who worked there thought. More of them rubbed their aching forearms and massaged their cricked necks as new computers were introduced to the AI Lab on a floor-by-floor basis. They realized their musculoskeletal issues coincided with the arrival of these new computers—some of which were mounted high up on lab benches in awkward positions—and the hours spent typing on them.
Today, these injuries have become more common in a society awash with smart devices, sleek computers, and other gadgets. And we don’t just get hurt from typing on desktop computers; we’re massaging our sore wrists from hours of texting and Facetiming on phones, especially as they get bigger in size.
In 2007, the first iPhone measured 3.5-inches diagonally, a measurement known as the display size. That’s been nearly doubled by the newest iPhone 13 Pro, which has a 6.7-inch display. Other phones, too, like the Google Pixel 6 and the Samsung Galaxy S22, have bigger screens than their predecessors. Physical therapists and orthopedic surgeons have had to come up with names for a variety of new conditions: selfie elbow, tech neck, texting thumb. Orthopedic surgeon Sonya Sloan says she sees selfie elbow in younger kids and in women more often than men. She hears complaints related to technology once or twice a day.
The addictive quality of smartphones and social media means that people spend more time on their devices, which exacerbates injuries. According to Statista, 68 percent of those surveyed spent over three hours a day on their phone, and almost half spent five to six hours a day. Another report showed that people dedicate a third of their day to checking their phones, while the Media Effects Research Laboratory at Pennsylvania State University has found that bigger screens, ideal for entertainment purposes, immerse their users more than smaller screens. Oversized screens also provide easier navigation and more space for those with bigger hands or trouble seeing.
But others with conditions like arthritis can benefit from smaller phones. In March of 2016, Apple released the iPhone SE with a display size of 4.7 inches—an inch smaller than the iPhone 7, released that September. Apple has since come out with two more versions of the diminutive iPhone SE, one in 2020 and another in 2022.
These devices are now an inextricable part of our lives. So where does the burden of responsibility lie? Is it with consumers to adjust body positioning, get ergonomic workstations, and change habits to abate tech-related pain? Or should tech companies be held accountable?
Kavin Senapathy, a freelance science journalist, has the Google Pixel 6. She was drawn to the phone because Google marketed the Pixel 6’s camera as better at capturing different skin tones. But this phone boasts one of the largest display sizes on the market: 6.4 inches.
Senapathy was diagnosed with carpal and cubital tunnel syndromes in 2017 and fibromyalgia in 2019. She has had to create a curated ergonomic workplace setup, otherwise her wrists and hands get weak and tingly, and she’s had to adjust how she holds her phone to prevent pain flares.
Recently, Senapathy underwent an electromyography, or an EMG, in which doctors insert electrodes into muscles to measure their electrical activity. The electrical response of the muscles tells doctors whether the nerve cells and muscles are successfully communicating. Depending on her results, steroid shots and even surgery might be required. Senapathy wants to stick with her Pixel 6, but the pain she’s experiencing may push her to buy a smaller phone. Unfortunately, options for these modestly sized phones are more limited.
These devices are now an inextricable part of our lives. So where does the burden of responsibility lie? Is it with consumers like Senapathy to adjust body positioning, get ergonomic workstations, and change habits to abate tech-related pain? Or should tech companies be held accountable for creating addictive devices that lead to musculoskeletal injury?
Kavin Senapathy, a freelance journalist, bought the Google Pixel 6 because of its high-quality camera, but she’s had to adjust how she holds the oversized phone to prevent pain flares.
A one-size-fits-all mentality for smartphones will continue to lead to injuries because every user has different wants and needs. S. Shyam Sundar, the founder of Penn State’s lab on media effects and a communications professor, says the needs for mobility and portability conflict with the desire for greater visibility. “The best thing a company can do is offer different sizes,” he says.
Joanna Bryson, an AI ethics expert and professor at The Hertie School of Governance in Berlin, Germany, echoed these sentiments. “A lot of the lack of choice we see comes from the fact that the markets have consolidated so much,” she says. “We want to make sure there’s sufficient diversity [of products].”
Consumers can still maintain some control despite the ubiquity of tech. Sloan, the orthopedic surgeon, has to pester her son to change his body positioning when using his tablet. Our heads get heavier as they bend forward: at rest, they weigh 12 pounds, but bent 60 degrees, they weigh 60. “I have to tell him, ‘Raise your head, son!’” she says. It’s important, Sloan explains, to consider that growth and development will affect ligaments and bones in the neck, potentially making kids even more vulnerable to injuries from misusing gadgets. She recommends that parents limit their kids’ tech time to alleviate strain. She also suggested that tech companies implement a timer to remind us to change our body positioning.
In 2017, Nan-Wei Gong, a former contractor for Google, founded Figur8, which uses wearable trackers to measure muscle function and joint movement. It’s like physical therapy with biofeedback. “Each unique injury has a different biomarker,” says Gong. “With Figur8, you are comparing yourself to yourself.” This allows an individual to self-monitor for wear and tear and strengthen an injury in a way that’s efficient and designed for their body. Gong noticed that the work-from-home model during the COVID-19 pandemic created a new set of ergonomic problems that resulted in injuries. Figur8 provides real-time data for these injuries because “behavioral change requires feedback.”
Gong worked on a project called Jacquard while at Google. Textile experts weave conductive thread into their fabric, and the result is a patch of the fabric—like the cuff of a Levi’s jacket—that responds to commands on your smartphone. One swipe can call your partner or check the weather. It was designed with cyclists in mind who can’t easily check their phones, and it’s part of a growing movement in the tech industry to deliver creative, hands-free design. Gong thinks that engineers at large corporations like Google have accessibility in mind; it’s part of what drives their decisions for new products.
Display sizes of iPhones have become larger over time.
Sourced from Screenrant https://screenrant.com/iphone-apple-release-chronological-order-smartphone/ and Apple Tech Specs: https://www.apple.com/iphone-se/specs/
Back in Germany, Joanna Bryson reminds us that products like smartphones should adhere to best practices. These rules may be especially important for phones and other products with AI that are addictive. Disclosure, accountability, and regulation are important for AI, she says. “The correct balance will keep changing. But we have responsibilities and obligations to each other.” She was on an AI Ethics Council at Google, but the committee was disbanded after only one week due to issues with one of their members.
Bryson was upset about the Council’s dissolution but has faith that other regulatory bodies will prevail. OECD.AI, and international nonprofit, has drafted policies to regulate AI, which countries can sign and implement. “As of July 2021, 46 governments have adhered to the AI principles,” their website reads.
Sundar, the media effects professor, also directs Penn State’s Center for Socially Responsible AI. He says that inclusivity is a crucial aspect of social responsibility and how devices using AI are designed. “We have to go beyond first designing technologies and then making them accessible,” he says. “Instead, we should be considering the issues potentially faced by all different kinds of users before even designing them.”
Jessica Ware is obsessed with bugs.
My guest today is a leading researcher on insects, the president of the Entomological Society of America and a curator at the American Museum of Natural History. Learn more about her here.
You may not think that insects and human health go hand-in-hand, but as Jessica makes clear, they’re closely related. A lot of people care about their health, and the health of other creatures on the planet, and the health of the planet itself, but researchers like Jessica are studying another thing we should be focusing on even more: how these seemingly separate areas are deeply entwined. (This is the theme of an upcoming event hosted by Leaps.org and the Aspen Institute.)
Listen to the Episode
Entomologist Jessica Ware
D. Finnin / AMNH
Maybe it feels like a core human instinct to demonize bugs as gross. We seem to try to eradicate them in every way possible, whether that’s with poison, or getting out our blood thirst by stomping them whenever they creep and crawl into sight.
But where did our fear of bugs really come from? Jessica makes a compelling case that a lot of it is cultural, rather than in-born, and we should be following the lead of other cultures that have learned to live with and appreciate bugs.
The truth is that a healthy planet depends on insects. You may feel stung by that news if you hate bugs. Reality bites.
Jessica and I talk about whether learning to live with insects should include eating them and gene editing them so they don’t transmit viruses. She also tells me about her important research into using genomic tools to track bugs in the wild to figure out why and how we’ve lost 50 percent of the insect population since 1970 according to some estimates – bad news because the ecosystems that make up the planet heavily depend on insects. Jessica is leading the way to better understand what’s causing these declines in order to start reversing these trends to save the insects and to save ourselves.