Donna Shirley pictured at her home in Tulsa, with a model of the Sojourner rover she was in charge of that explored Mars.
"Periodically, I'll hear somebody say they got into the space program because of me, and that makes me feel really good," Shirley told Leaps.org. "I look at the mission control area, and there are a lot of women in there. I'm quite pleased I was able to break the glass ceiling."
Her $25-million, 25-pound microrover – powered by solar energy and designed to get rock samples and test soil chemistry for evidence of life – was named after Sojourner Truth, a 19th-century Black abolitionist and women's rights activist. Unlike Mars Pathfinder, Shirley didn't have to travel more than 131 million miles to reach her goal, but her path to scientific fame as a woman sometimes resembled an asteroid field.
The Sojourner Rover in 1997 on Mars.NASA/JPLAs a high-IQ tomboy growing up in Wynnewood, Oklahoma (pop. 2,300), Shirley yearned to escape. She decided to become an engineer at age 10 and took flying lessons at 15. Her extraterrestrial aspirations were fueled by Ray Bradbury's The Martian Chronicles and Arthur C. Clarke's The Sands of Mars. Yet when she entered the University of Oklahoma (OU) in 1958, her freshman academic advisor initially told her: "Girls can't be engineers." She ignored him.
Years later, Shirley would combat such archaic thinking, succeeding at JPL with her creative, collaborative management style. "If you look at the literature, you'll find that teams that are either led by or heavily involved with women do better than strictly male teams," she noted.
However, her career trajectory stalled at OU. Burned out by her course load and distracted by a broken engagement to marry a fellow student, she switched her major to professional writing. After graduation, she applied her aeronautical background as a McDonnell Aircraft technical writer, but her boss, she says, harassed her and she faced gender-based hostility from male co-workers.
Returning to OU, Shirley finished off her engineering degree and became a JPL aerodynamist in 1966 after answering an ad in the St. Louis Post-Dispatch. At first, she was the only female engineer among the research center's 2,000-odd engineers. She wore many hats, from designing planetary atmospheric entry vehicles to picking the launch date of November 4, 1973 for Mariner 10's mission to Venus and Mercury.
By the mid-1980's, she was managing teams that focused on robotics and Mars, delivering creative solutions when NASA budget cuts loomed. In 1989, the same year the Sojourner microrover concept was born, President George H.W. Bush announced his Space Exploration Initiative, including plans for a human mission to Mars by 2019.
That target, of course, wasn't attained, despite huge advances in technology and our understanding of the Martian environment. Today, Shirley believes humans could land on Mars by 2030. She became the founding director of the Science Fiction Museum and Hall of Fame in Seattle in 2004 after leaving NASA, and to this day, she enjoys checking out pop culture portrayals of Mars landings – even if they're not always accurate.
After the novel The Martian was published in 2011, which later was adapted into the hit film starring Matt Damon, Shirley phoned author Andy Weir: "You've got a major mistake in here. It says there's a storm that tries to blow the rocket over. But actually, the Mars atmosphere is so thin, it would never blow a rocket over!"
Fearlessly speaking her mind and seeking the stars helped Donna Shirley make history. However, a 2019 Washington Post story noted: "Women make up only about a third of NASA's workforce. They comprise just 28 percent of senior executive leadership positions and are only 16 percent of senior scientific employees." Whether it's traveling to Mars or trending toward gender equality, we've still got a long way to go.
A recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens 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.