Employers are scrambling to find people with AI, machine learning and data science skills and higher education is responding. Leaders from a group of top universities gathered at GTC DC Wednesday to discuss how universities can meet this demand.
Martial Hebert, dean of the School of Computer Science at Carnegie Mellon University, was joined by Cammy Abernathy, dean and professor of materials science and engineering at the University of Florida; Kenneth Ball, dean of the Volgenau School of Engineering at George Mason University; and Joe Paris, director for research computing at Northwestern University.
GTC DC has become the premier AI conference in the nation’s capital, this year attended by more than 3,600 developers, researchers, educators and CIOs focusing on the intersection of AI, policy and industry.
Wednesday’s panel, moderated by NVIDIA’s Jonathan Bentz, a solutions architect for higher education and research, life science, and high performance computing, discussed the importance of democratizing AI and data science tools and concepts for students.
The panelists explored three ways to better democratize AI: new degree programs, new coursework and building skills.
“We are distributing important digital skills throughout every course and major — from humanities to fine arts to healthcare to genomics — and developing brand new degrees to meet the needs of the changing workforce,” Ball said.
A major challenge to building skills, however, remains access to computing resources. Hebert described computing as “one of the biggest obstacles” faced by institutions limiting the number of students who can be involved with cutting-edge work.
In addition to access to the most capable machines, students need to be equipped with the knowledge and tools to address bias in AI.
“As we head down this path, it’s not lost on us the examples where our biases as programmers are finding their way into codes that are being applied to important tasks,” Paris said.
Abernathy said she’s “amazed” to see how quickly AI and machine learning have embedded themselves in almost every discipline. As the technology spreads, she stressed the importance of reaching out to and preparing underrepresented groups.
“It’s pretty clear if you want to be employable and a leader in your profession, you need to have skills in these domains,” Abernathy said. “It’s important that we provide access to a wider range of people.”
At GTC DC, the NVIDIA Deep Learning Institute offered a bevy of sold-out courses, workshops and hands-on training in AI, accelerated computing and data science and it announced a dozen new courses on Monday.
Resources:
- Watch the panel discussion
- Get started with your own AI training today with the DLI.
- Check out NVIDIA’s technology for higher education and research, as well as discounts for all accredited institutions, professors and students.