Source | FastCompany : By CALE GUTHRIE WEISSMAN
The idea was born in a hotel room.
In 2005, Hanna Wallach, a machine-learning researcher, found herself bunking with colleagues to attend the Neural Information Systems Processing (NIPS) conference. Wallach had been working in the field since 2001 and had attended numerous conferences, but this was the first time she had roomed with other women who specialized in machine learning, a branch of artificial intelligence that researches how computer programs can learn and grow. As a discipline, it is overwhelmingly male: Wallach estimates that only 13.5% of the entire machine learning field is female.
At the conference, Wallach and her roommates, Jennifer Wortman Vaughan, Lisa Wainer, and Angela Yu, began discussing their experiences and commiserating about the lack of female allies. “We couldn’t believe that there were four of us [at the conference],” Wallach says. She, Vaughan, and Wainer made a list of 10 others in the field and fantasized about a meetup.
The next year, in October 2006, Wallach, Vaughn, and Wainer organized the first Women in Machine Learning Conference. Attendance reached almost 100. “It was incredible to see so many machine-learning women all there in the same space,” Wallach says. “None of us had experienced something like that before.” (Yu attended the conference but did not cofound it.)
Over the past decade, the program has grown substantially, with attendance ballooning to more than 300. (Men are welcome at WiML, though they cannot present.) This year, the organizers had to close registration because they’d reached capacity for the venue. What began as a pie-in-the-sky dream at the NIPS conference has become an important, respected organization and support system for women in AI.