Women in AI | Chelsea Finn: ‘I Certainly Feel Like a Minority’
As part of the Women in AI special project, Synced spoke with Chelsea Finn, an assistant professor in Computer Science and Electrical Engineering at Stanford University. Most of her work focuses on the capability of robots and other agents to develop broadly intelligent behaviour through learning and interaction.
In 1996, participants in the C.V. Ramamoorthy Workshop on Advances in Computer Science and Engineering made donations to help launch the C.V. Ramamoorthy Distinguished Research Award. Although the award can be given to any Berkeley student working in the area of Computer Science (CS) who has made outstanding contributions to a new research area, in 20 years since it was set up, there had never been a female recipient — until Chelsea Finn pocketed it in 2017.
And she remains to be the only female winner of that award to date.
Women continue to be severely underrepresented in computer science and AI. Previous analyses as part of our Women in AI series found that only 18 percent of the authors at the 21 leading AI conferences are women, and as of 2015 women made up just 18 percent of computer science majors in the US.
“I’m not at all surprised,” Finn told Synced, “in many ways that number actually seems somewhat high — at least I think it’s different in different areas.”
Finn currently spends most of her time at Stanford where she is teaching two quarters of the year, doing research projects with her PhD students, and running her lab to study intelligence through robotic interaction at scale. One day a week, she also does research work with the Google Brain Team.
“At artificial intelligence and machine learning conferences for example, I certainly feel like a minority, and I know that there have been many situations when I was the only female for example speaking at a workshop or speaking at some events. And there’s always been a number of awards that I’ve been fortunate enough to receive where I was either the first woman to receive their award or the first woman to receive it in many years,” she said.
Finn graduated with her Bachelor’s in electrical engineering and computer science from MIT and completed her PhD in computer science at UC Berkeley. Her dissertation Learning to Learn with Gradients won the 2018 ACM Doctoral Dissertation Award — she was again the first female winner of that award in about 15 years, though a few women were awarded honourable mention.
Finn is actively concerned about the broad impacts of underrepresentation. “I worry about people feeling like they don’t fit in, that there aren’t people that look like them in a place,” she said.
At a young age, Finn really enjoyed solving puzzles and problems, and with both parents being engineers she knew that engineering was one way to do that. Finn chose to major in Computer Science and Electrical Engineering because she believed that would leave many doors open for her to try different things later down the line. As Finn became more and more drawn to robotics, machine learning, and AI, she realized the need to go to grad school and do research if she hoped to make new advances and develop new algorithms.
Finn says when she started her PhD she wasn’t planning to stay in academia because actually making products in the industry was more appealing. But things didn’t go as planned when she later realized the greater long-term impact she could have through research and teaching.
When Finn was a student at MIT she appreciated the efforts faculties made to increase the representation of women on both their core staff and with guest speakers. It was hoped this would provide more role models for young students. Now, she hopes she can inspire more young students to believe there could also be a career in academia for them.
Some of the things Finn is actively working on include organizing a mentorship program for underrepresented college students. Each of the undergraduates is paired with a grad student in AI to provide them firsthand information about what it’s like to be in grad school, what’s exciting about doing research, and what sort of steps they should take early on in their undergrad years if they’re interested in a career in research and AI. The program has been launched at Stanford, CMU, Berkeley, and MIT, with 50 to 100 undergraduates participating at each school every year, Finn told Synced.
Since her PhD years, Finn has also been helping with other outreach programs for high school students through AI4ALL, a nonprofit dedicated to increasing diversity and inclusion in AI education, research, development, and policy. The nonprofit was co-founded in 2015 by Stanford professor and renowned AI researcher Fei-Fei Li, Olga Russakovsky — Li’s PhD student at the time, and Rick Sommer, executive director of Stanford Pre-Collegiate Studies. The first program that the team launched was SAILORS — a summer outreach program for high school girls to learn about human-centered AI.
“There’s still a lot that we can improve on, but I see progress,” Finn said. “I do think that the environment at Stanford has been improving and I have actually been really excited to see the numbers start to go up in terms of both the student population, the graduate student population, and the faculties.” She says she loves that there are a number of other female computer science faculty at Stanford, so they can have a community.
Finn is also well aware that it takes time for any trends to really lead to concrete, measurable improvement, especially since the number of women studying or pursuing a career in computer science has remained low over the past decade.
It’s still a work in progress, and fixing the pipeline isn’t the entire problem, she added. “I think there’s still more that can be improved — in terms of creating a welcoming and inclusive environment.”
Journalist: Yuan Yuan | Editor: Michael Sarazen
To highlight the contributions of women in the AI industry, Synced introduces the Women in AI special project this month and invites female researchers from the field to share their recent research works and the stories behind the idea. Join our conversation by clicking here.
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