As a YouTube influencer known for her social media videos, Jordan Harrod translates developments in artificial intelligence and public health to mass audiences.
Harrod, a Ph. D. candidate for Medical Engineering and Medical Physics at the Harvard-MIT Health Sciences and Technology program, is known for her viral videos like: “Can AI Recognize You From Your Walk?,” “Edge Computing, Explained,” and “How AI Learns to Cheat.” When she’s not exploring how humans interact with AI and other technologies, “for better or for worse,” she’s working on her Olympic lifts at the gym or reading fantasy novels.
YR Media chatted Harrod up over Zoom about what motivates her, the future of AI, and the benefits and betrayals of recent AI technology.
Cureha Mitchell, YR Media Contributor: What project have you worked on that you are most excited about? How does it work, what was involved in creating it, what makes it special?
Jordan Harrod: My first foray into machine learning was in machine learning and medical imaging. And it was a very interesting learning experience for me in terms of getting into the field.
We’re interested in designing machine learning systems that could identify Magnetic Resonance Images (MRI) that had been acquired incorrectly. Because sometimes the errors that either the MRI or the software make can look like tumors, or something that might be diagnosed as an issue in a patient, when it’s not really there. That project was exciting, because it was one of the first projects that I worked on that felt like it could have a short term impact.
CM: Can you tell us about a person or experience you credit for putting you on the path you’re on?
JH: My dad essentially told me to ask for what I want from a pretty young age, because the worst answer you can get is “no”. And that’s somewhat become the motto of most of the decisions and opportunities that I’ve been able to make over the entire educational journey I’ve been on.
CM: Is there a void in your field and how do you see your contributions as filling that need?
JH: At the intersection of my scientific work and my academic work, there’s definitely a void of researchers, who also are interested in communicating their work in more ways than giving talks. And I hope that the content work that I do helps to fill that gap of people who are reaching out to audiences that likely wouldn’t come across traditional forms of public science engagement.
CM: Can you think of a time when you ever considered giving up on your dream? Walk us through what you did to get past that.
JH: I thought that I was going to go into pharma right after undergrad. I did an internship in pharma. I realized that I was not actually interested in going into pharma after all, and I don’t think that was me giving up on a dream, but it was just a change in the trajectory of the path that I was on.
CM: What advice would you give to young people looking to break onto your world?
JH: The environment that you work in is just as important, if not more important than the work that you do, but often isn’t something that you necessarily consider when deciding to pursue new work, new opportunities, or when reflecting on past opportunities.
CM: We know you can’t see into the future, but if you were to predict: What will be happening in your field that’s different from now?
JH: I hope that we’ll have a better understanding of the human brain than we do now. I think on the machine learning side, I hope that we start to see more and more interdisciplinary work, more incorporation of the ethical side of things into kind of the educational pipeline so that people will have an understanding and our respect for that side of things.
CM: Do you have any opinions regarding AI use in synthetic speech such as Uberduck? Do you see any pros and cons of this technology?
JH: Synthetic speech has some pros, often in the form of dubbing, so being able to take content that was originally created in one language and dub it in a realistic way into another language. That also ties into video deep fakes where you could make it so that the lip sync ends up working better.
At the same time, there’s obviously plenty of ways to misuse this kind of stuff. It’s something that’s very easily exploited, especially since it’s readily available across the internet and you don’t actually need any real expertise in order to find systems that will let you do it.
CM: How do you want your legacy to be remembered?
JH: I hope the research that I do will contribute something to either understanding of the world that we live in or advancing human health. But I don’t think that I need to be someone who people read about in textbooks; I just hope that the work that I do ends up having a net positive impact.