This summer I was one of 40 girls selected to attend the AI4ALL program at Stanford University. During the three-week program, we visited Silicon Valley companies, learned how artificial intelligence is transforming various fields, and applied our programming skills to group projects. (My team’s project focused on using natural language processing to analyze social media and improve relief efforts following natural disasters). One of our guest speakers was Marina Sirota of UCSF, who is using AI to improve medical diagnosis and treatment. I was inspired by her talk and thrilled when she agreed to this interview.
What are the biggest misconceptions people have about AI? What is the one fear or misconception you wish you could change?
I think the biggest misconception about AI is that it can solve all of our problems – I think of AI as a way to help us to better do our job instead. For instance, in the context of biomedical applications of AI, we are not aiming to replace physicians, but to have algorithms that help doctors make better decisions or carry out their work more effectively.
What did you become interested in first, Biology/Medicine or Computer Science? How, when, and why did you make the decision to focus on applying AI to life sciences?
In school, I was always interested in math and thought I would a pursue a career in computer science, however as a junior in high school I took a biotech class where I got to learn more about genetics and try out several exciting lab techniques such as PCR and gene transfer which I was very excited about. That led me to explore the application of computational methods to biology and study bioinformatics in college and graduate school.
How can we encourage or incentivize people to use AI to solve problems that are important and not just those that might help them make the most money?
It’s all about asking the right questions and finding interesting and impactful problems – I think finding what a person is truly passionate about and pursuing that can often trump the desire to make the most money. On another hand, if someone is working on something they are really excited about, they are more likely to succeed and innovate which will lead to monetary success as well.
AI as a field needs people with strong Math and Computer Science backgrounds to advance the research. And in your particular area, understanding Biology and Medicine is important, too. What are some of the other skills and areas of expertise the AI field will need to fulfill its potential?
I think communication is one of the most important skills that one can develop during their training. Being able to present your work effectively whether when giving a talk or in writing is crucial to one’s success as a scientist. Being able to communicate our work clearly to a broad audience allows us to have a larger impact and share the work with the scientific community and beyond. Especially in transdisciplinary fields such as bioinformatics, being able to speak to a statistician, a computer scientist, a biologist and a clinician in a way that those individuals can understand is extremely important and will allow one to focus on the important questions and problems in the field as well as find the right approach to tackle those problems.
How can we diversify the AI field and encourage kids from underrepresented groups to pursue STEM given not all public schools have strong offerings? (I attended San Francisco public schools until eighth grade and was surprised at how weak my background in Science was compared to same-age peers who attended private schools or public schools in better-funded districts).
I can’t agree more that we need to encourage kids from underrepresented groups to pursue STEM at an early age and this is something that I’m very passionate about. In order to achieve this goal, this year I launched a new program at UCSF called AI4ALL, a high school education and research program that focuses on introducing high school girls from diverse populations to applications of artificial intelligence in biomedicine at UCSF (http://ai4all.uscf.edu).
What excites you the most about your current research?
Being able to potentially impact clinical care and the life of patients by applying innovative computational techniques to biomedical data is what excites me most about my research. We currently have several projects leveraging different types of molecular (genetics, gene expression, microbiome) and clinical data to study preterm birth in the context of diagnostics and therapeutics. The fact that we can often use data that is publicly available to ask new scientific questions and impact the lives of patients is incredible in my opinion!
Think back to when you were 15 years old (my age). What did you want to be when you grew up?
I was always interested in the math and the sciences and enjoyed problem solving, so I knew I wanted to pursue a career in STEM, but I didn’t know what it was like to do research or be on the edge of what is known. I didn’t know what it is like to work on a problem that no one knows the answer to, which is very much part of my job today. I often still ask myself what I want to be when I grow up and it matters less whether I’m a scientist in the industry or researcher in academia; what matters most to me is that I’m working on exciting problems and am surrounded by smart and talented people.
If you could travel back in time and speak to your 15-year old self, what advice would you give her?
One piece of advice that I would give myself is don’t rush. I was always in a hurry – finish high school, graduate from college and graduate school, find a job, etc. Instead, take time to find what you are truly passionate about, set goals and go for them - don’t be scared of failing and learn from those mistakes!
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