His phone rang. “I’ll be there,” Beyer told a colleague who wondered when he would return to parliament to vote.
It seemed as if college would have to wait.
That was the story of the year for Beyer (D-Va.), who was a part-time student at George Mason University pursuing a master’s degree in machine learning while balancing his duties as a congressman. Beyer — a science wok, economist, and former auto salesman — has been taking one class per semester in a slow but steady march to graduation, hoping to one day apply his knowledge of artificial intelligence to his legislative work as technology advances .
“It was a lot of fun”, the Beyer, 72, said – though: “I tried to think about the consequences last night. Number one is that I’ve only read two-thirds as many books this year. If I hit 53, I’ll be lucky just because I’m struggling during the time I’ve been reading books.”
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He usually does his homework sometime between 9 and 11 a.m. after he gets home from the Hill and before he turns on the light. He attended a Zoom class every Thursday night with lots of 18-year-olds who kept their cameras off and who, in small work sessions, seemed unaware (or cared?) that their classmate is a US congressman. The warden, who was conducting an exam in his estimating class this spring, leaned forward and whispered, “What are you doing here?” as Beyer handed in his test.
“That’s what everyone has to think, right?” Beyer’s deputy chief of staff Aaron Fritschner asked as Beyer related the story.
In short, what is Beyer doing here?
Long fascinated by the ability of machines to extract meaning from huge data sets, a few years ago Beyer visited an AI company in Arlington that had just done well with a facial recognition project in an international competition. He was fascinated. Then, a year ago, he visited George Mason’s new innovation initiative in Arlington, once again fascinated by the potential of AI.
“It was so impressive. I said, ‘Can I take classes here?’ recalled Beyer, who chairs the House Subcommittee on Science, Space and Technology under NASA oversight and co-founded a caucus to study fusion energy.
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So they sent him the catalog, made an exception for Beyer, who missed a deadline to register for classes, and voila, he was back in college. In order to qualify for the master’s degree, Beyer had to complete seven undergraduate courses in mathematics and computer science; With three canceled courses this year and four pending, he expects to start actual thesis work by 2024.
Rep. Jay Obernolte (R-Calif.), who will next term co-chair the AI caucus that Beyer is a member of, hailed the Virginia Democrat for working overtime to get the deal. He himself earned an AI master’s degree and a PhD in public administration while serving in the California Legislature. He said: “I can tell you from personal experience that it’s very difficult to do both at the same time.”
But as the power of artificial intelligence and its uses grows, Obernolte said it will be worth having another member at the table with all this fresh knowledge — especially as the AI faction seeks to steer Congress into responsible ways to regulate the economy Technology and Use of Personal Information.
“Some people unfamiliar with AI think that the biggest downside of AI is evil robots with red laser eyes. You know what I mean?” Obernolte said. “You get closer and realize, no, there are actually downsides that are more serious, but they’re also more subtle in a thoughtful manner that provides the necessary protections for consumers and privacy, but also doesn’t stifle the innovation and entrepreneurial spirit that has characterized America’s tech industry for the last 50 years.”
Beyer said that when considering how to use his AI background, he focused on an area that has long been a priority of his: suicide prevention.
The use of AI technology as a tool in the mental health field is still relatively nascent. Although applications vary, one AI role is to find common factors or patterns in cases of people who may have attempted or died by suicide or expressed suicidal thoughts. AI then uses that data to create risk profiles that could help doctors identify which patients may be at higher risk and may need more services, explained Adam Horwitz, an assistant professor at the University of Michigan Medical School specializing in suicide prevention specialized. AI tools are intended to complement, not replace, the work of clinicians seeing patients, Horwitz said, and indeed, he noted, the US Department of Veterans Affairs is already using the technology.
“I think the role of AI is more to help build the structure and framework for treating higher-risk cases,” Horwitz said, “and to be able to better allocate the resources and follow up on them.” and to support people who might need it.”
In Beyer’s office, suicide prevention is personal after a young employee dies by suicide. His death surprised so many, Beyer said – his family, friends and colleagues wished there had been a sign.
The technology, Beyer said, could provide the warning signs that clinicians might not see right away.
“There must be another thousand markers, many of which can be subtle,” Beyer said of factors that could be part of a risk profile. “But if you put them all together, you can use machine learning to say, ‘What are these 47,000 people doing?’ or over the course of 10 years: ‘What do these 500,000 people have in common?’ break this path” for someone else?
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Horwitz said that while the research is still in its infancy, other ethical and privacy concerns have yet to be evaluated, considering the sensitivity of mental health records or decisions about how the data is used once it’s in the hands of a mental health professional third parties; Doctors are already bound by data protection regulations. This could be an area where Congress might need to be familiar with the technology, he said. “I think these are things that are going to be important for people in this space, so they’re familiar, know how it’s used, why it’s used, the applications and make sure safety precautions are in place,” he said.
Figuring out where Congress fits in, Beyer notes, is “absolutely the most practical net effect of just doing maths late at night.” He hasn’t figured it all out yet, he said, although he thinks long-term he hasn’t ruled out pursuing a PhD in machine learning.
“I won’t live forever, but I thought, you know, look With our 80-year-old president, I thought it wouldn’t be a bad thing to have a PhD in machine learning and artificial intelligence at age 80. Maybe 20 years left,” he said.
Right now he’s concentrating on his next course in the spring: Discrete Mathematics. Goodbye, New York Times Sunday crossword, he laments.
If you or someone you know needs help, call Suicide & Crisis Lifeline on 988. You can also reach a crisis counselor by sending a message crisis text line at 741741.