The Next Great Tech Revolution

AI research at Rice is fueling significant breakthroughs, plus debate about the public good

The Next Great Tech Revolution

Spring 2024
By Hilary C. Ritz
Illustrations by Antoine Doré

Angela Wilkins, until recently the executive director of Rice’s Ken Kennedy Institute, is definitely pro-artificial intelligence. Even over our Zoom call, her enthusiasm about it is uplifting, and it’s entirely with that kind of positive energy — not distrust or anxiety — that she says AI has “seeped into everything.”

“It’s in every field now. Everybody’s doing it,” she adds. “They’re either making AI that works for them, using AI that works for them, or they have a collaborator that’s doing it for them.”

When I ask her why AI is so important, she says, as if it were perfectly obvious, “It’s important because science is important. AI allows us to do better science.”

For Wilkins, who is newly appointed to the Texas AI Advisory Council, AI is simply the next great technological revolution, following the printing press, the personal computer and the internet. “Now we can see something that might help make the world a better place,” she says. “Hopefully fix climate change and hopefully make the world more equitable. I’ve never seen anything quite like what’s going on now in the context of, just, people see what the possibilities are.”

But Wilkins’ enthusiasm isn’t blind faith, nor blind optimism. “We need explainability, we need responsibility. We need to make sure that it’s fair, it’s equitable. For technology to influence the way we do things, it has to be done right,” she says. “This is something we really, really care about.”

All this is really prelude to the conversation I set out to have with Wilkins, which was to understand the full breadth and depth of AI research on campus at Rice. As it turns out, this is a challenging task. “We have people who do everything,” Wilkins says. “As a whole, we’re covering the entire field.”

I decide to focus on several key projects from disparate areas in order to showcase the full range of research at Rice. When I ask Wilkins to suggest projects, she exclaims, “It’s so hard to choose! I love everybody!” But she admits that she’s particularly excited about the collaboration between Rice and Houston Methodist, where robots will be used to train nurses, and soon I’m off to the brand-new Ralph S. O’Connor Building for Engineering and Science to learn more.

Embodied AI for better health care

At the O’Connor Building, computer scientists Lydia Kavraki and Vaibhav Unhelkar and grad students Pam Qian, Qingxi Meng and Carlos Quintero Peña meet me in their fourth-floor lab. There, Kavraki tells me, “The health care field lost one-third of its workforce since COVID-19, so this means that there is a shortage, and they don’t have the instructors to train the nurses.” According to their partners at Houston Methodist — Shannan Hamlin, Nicole Fontenot and Hsin-Mei Chen — it’s a real problem.

Enter a robot that looks less like what I imagined when I thought “robot” and more like a Roomba with a tall camera stand on top of it. But I soon understand that the minimalism is by design, making the robots unobtrusive, maneuverable and cost effective. Their first application will be to help nurse trainees learn how to maintain a sterile field while applying dressings to wounds. Qian and Meng demonstrate how the system tracks hand and body movements and flashes a warning when trainees break rules, such as reaching across the sterile field.

Many of the techniques that have been developed in AI really get their final tests in the embodied AI systems.

Many milestones are yet to come, like programming the robot to continuously position itself to get the best view of the trainee’s movements while staying safely out of the way. “There are a lot of systems that have to come into play,” Unhelkar says, listing areas of research such as “imitation learning” and “perception-aware motion planning.”

Kavraki adds, “Many of the techniques that have been developed in AI really get their final tests in the embodied AI systems, because there you cannot afford to make mistakes. You cannot afford to have this robot collide, even if it is 1% of the time.”

As far as the team knows, this is a unique application of embodied AI. And sterile field training is critically important, considering that, according to the CDC, one in 31 U.S. patients acquires an infection in association with their health care every day. But this is just the beginning of what these robots will be able to do.


View the full article by Rice Magazine's Hilary C. Ritz at: https://magazine.rice.edu/spring-2024/the-next-great-tech-revolution

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