Sethuraman Panchanathanits 15th director National Science Foundation spoke at Northeastern's official opening EXP Research Center on October 16.
A computer scientist and engineer, Panchanathan is known for championing innovation and inclusiveness, as well as leading innovations in artificial intelligence.
He sat down with Northeastern Global News for a wide-ranging discussion about what NSF is doing to support effective research solutions to pressing global and societal challenges—from infectious disease outbreaks to climate change and national security.
His answers have been edited for brevity and clarity.
Earlier this month, the 2023 Nobel Prizes in physiology/medicine, physics, chemistry and economics were announced. Tell us what NFS has done to support future and current awardees.
To date, NSF has funded 262 early-career Nobel laureates — the most of any agency in the United States or anywhere in the world.
NSF unleashes talent across our country. It was founded in 1950, after World War II, to answer the questions: How can we ensure human health, well-being, prosperity, national security, and economic security for our nation?
It is currently a $10 billion organization that unleashes ideas and advances curiosity-driven research and discovery at scale.
NSF has a footprint in all 50 states and territories and addresses all aspects of science, technology, engineering and innovation.
How does NSF work with academia and industry to advance innovation?
Let me give you something very native to Boston as an example – Ginkgo Bioworks. NSF helped fund the company through grants, including Small Business Innovation Research, or SBIR, grants.
Today it is a $6 billion company. What I'm trying to communicate here is that NSF makes basic research, fundamental research, translational research, and impactful results possible, including startup companies and people doing research.
If you went to any tech company in Boston and asked them, “What do you think about NSF?” chances are you'll run into people who say, “I was supported by an NSF undergraduate research fellowship,” or “My mentor had an NSF fellowship and I was supported by that.”
They would have been touched by the NSF one way or another.
Experiential learning drives everything we do at Northeastern, including our research enterprise. What are your thoughts on integrating real-world experience with what happens in the labs?
Northeastern is the third largest NSF-invested institution in Massachusetts — Woods Hole, MIT and Northeastern.
Whether it's pandemic prediction, climate change, climate mitigation, adaptation and resilience, or any grand challenge we have, you'll find that NSF has made possible fundamental discoveries and translational discoveries that come to address the problem and provide solutions.
The real work happens at great places like Northeastern University.
When you have an experiential kind of program, students can see not only what the big academic security researchers are doing and things like that, but they're also inspired by people in the industry who are doing amazing work.
This is what makes great innovations possible and great innovations possible. It's like a feed of ideas.
I would argue that without that mentor-mentee relationship, these ideas don't flow with speed and scale. I was inspired by my mentor. And this has enabled me to come up with some great ideas as part of my academic experience as a student.
You are a champion of using technological innovation to empower people with disabilities. Tell us why it's a priority.
My own work started, as you said, with people with disabilities. I worked with people who are blind or visually impaired, people with mobility disabilities, cognitive disabilities or children with autism.
But I soon realized that they were people with great ideas, great abilities. I have come to use the term, “people with a range of abilities”. These aren't people who don't have abilities — they have abilities of a different type.
What you need to do is see how technology, working with people, can co-create amazing futures and amazing, great innovations.
What happens is when you start thinking, “I'm going to help visually impaired people be able to have more gainful employment or a purposeful life,” innovations become useful to the entire population.
Assistive note taking and remote communication are some examples. I'm not sure if you know that the typewriter was invented for the blind. Where is the typewriter right now? It's here, on your mobile.
How beneficial is it for researchers to have access to a global network? How does it encourage innovation?
I keep repeating it: Science is global!
Global expertise, global partnerships, global context are extremely important if you really want to solve global grand challenges, plain and simple.
But in doing so, you want to work with like-minded global partners because at the end of the day, scientists are about core values. So one must embrace these core values of openness, transparency, reciprocity, research, integrity and respect for intellectual property.
Then we can hyper-collaborate so that we can solve these big challenge problems much more comprehensively and faster.
What are some of the most important ingredients of creativity and innovation?
Freedom is the first fundamental step. If you're a free spirit, you'll go out and innovate, right? You have no fear.
Fear is the worst form of constraint to innovation. Or some kind of limitation, some kind of feeling that, “I know I can't do this,” because that blocks your inevitable possibility to express yourself in its fullest form.
Fear is not a good motivator.
What is NSF's role in supporting research that does not fall into a scientific silo?
Social, behavioral, economic sciences, humanities and art are extremely important in the development and planning of science and technology.
Climate change is not just a science problem or an engineering problem. We all know it's a social problem. It's a behavior problem.
So, unless we bring all the inspirations even to the ideation of the technology and the design of the development of the solutions, then we try to do patch work after the fact.
A credible AI program we worked with Amazon, for example, includes not only computational information and sciences, but also social behavioral economics.
That's the kind of mindset we use to get people to co-create programs. So the community out there can then start responding by creating even bigger ideas.
You are optimistic about the promise of artificial intelligence and machine learning. Why should researchers embrace these technologies?
We have challenges in AI. Absolutely. But the promise of innovation, the potential of innovation, is far beyond what the challenges can do to slow innovation.
Challenges should motivate us, inspire us, see what kind of guardrails, what kind of new technologies, what kind of innovations can be developed to deal with them.
We don't shy away from challenges. We don't shy away from challenges. We understand them, we shape them.
This is when I would say speed up rather than slow down.
Cynthia McCormick Hibbert is a reporter for Northeastern Global News. Email her at c.hibbert@northeastern.edu or connect with her on Twitter @HibbertCynthia.
