Lynne Parker, Assistant Director for Artificial Intelligence at The White House Office of Science and Technology Policy, has been at the forefront of artificial intelligence (AI) for more than two decades.
Hers was the first PhD dissertation ever on the topic of multi-robot systems, she is a pioneering researcher in that field, and formed the Distributed Intelligence Laboratory at the University of Tennessee, Knoxville. There, she has conducted research in multi-robot systems, sensor networks, machine learning and human-robot interaction.
As AI continues to proliferate through all aspects of life, so too has Lynne’s impact on the field. In August, she put her academic work on hold to take on a groundbreaking assignment with The White House Office of Science and Technology Policy.
Recently, Lynne took a few minutes to discuss her new role, share her insights on the state of AI in the US (and beyond), and opine on the future impact of high-performance computing (HPC) on the evolution of AI.
I encourage you to read on, as the growing convergence of AI and HPC will be one of the hot topics at SC19 this November!
Michela: Tell me about your new role with The White House Office of Science and Technology Policy.
Lynne: I’m focusing on the development of strategic policies that can help accelerate AI innovation and positive impact. We’re engaging with numerous stakeholders – not only the federal government, but industry, academia and others – to look at how we can accelerate advances in AI for economic growth, improved quality of life and national economic security.
It’s an exciting time, with the executive order signed by President Trump on February 11 that established the American AI Initiative. And, on March 19, we launched AI.gov as an “all of government” portal into federal AI activities. Now, our office is focused on making sure we deliver on all of the actions outlined in the executive order — across the federal government, and through engagement with industry and academia.
Michela: You have been quoted as saying The White House initiative is intended to help us, as a nation, “harness the ability of AI.” Can you elaborate on that point?
Lynne: Because AI already touches on so many aspects of life, people are figuring out ways it can help address numerous challenges. They are also learning how it can help people be more productive in their jobs.
To move AI along in its development, we’re looking at all the touch points where we, as the federal government, need to take action. The executive order lays out a holistic approach – across R&D; providing data models and competing resources, like cloud computing; AI governance and technical standards; workforce development; and international engagement. All to support an environment that also opens up markets for AI industries.
Michela: Can you provide a brief overview, in layman’s terms, of your own research interests in AI and other areas?
Lynne: My career has focused on innovative uses of AI for creating distributed teams of intelligent robots that can work together. More recently, we’ve been looking at teams in which humans and robots are working together; focusing in particular on how that interaction can happen in a very natural and intuitive way for humans. My work has frequently used machine learning techniques and solutions.
Michela: What role does HPC play in your research?
Lynne: My research has been more aligned with edge computing. When you think about physical robots in the real world, with limited bandwidth and noisy communications, it hasn’t primarily been a domain that lends itself to HPC.
But it’s changing. Now there is more data available for deep learning that is useful for robots, and also communications capabilities have improved. This is beginning to lead to a paradigm shift in robotics; now, we can begin to leverage those capabilities in terms of perception and reasoning to help robots look at alternative solutions using HPC computation and simulation.
The executive order calls on federal agencies with resources in HPC and cloud computing to make those resources more available for AI research and development. Part of our task is to help make computational research more accessible, beyond just the big companies.
Michela: What’s next? How do you imagine supercomputing will impact the evolution of AI in the next five years?
Lynne: One of the things that really excites me is the potential for the combination of AI and supercomputing — bringing together the model-based, analytical approach to reasoning and problem solving that HPC has historically delivered, with the data-driven approach that has been central to AI’s bigger successes.
I’m excited to see where that leads. It could theoretically provide us a greater understanding of how to use data for solving tough problems.
Michela Taufer, PhD, General Chair, SC19
Michela Taufer is the Dongarra Professor in the Min H. Kao Department of Electrical Engineering & Computer Science, Tickle College of Engineering, University of Tennessee, Knoxville.