Professor Amy Greenwald of Brown University's Department of Computer Science delivered opening remarks and made multiple other contributions to a workshop she helped found that's celebrating a proud anniversary: Women In Machine Learning (WiML) turned ten this year. Amy made a significant founding contribution to the workshop by writing the initial National Science Foundation proposal that brought students to the first WiML.
The remarks began with a retrospective: formed in response to the lack of female researchers in machine learning, the original WiML was co-located with Grace Hopper Celebration and had sixty participants. Since then, the workshop has grown dramatically. Held on Monday in Montreal in collaboration with the Conference on Neural Information Processing Systems, this year's event was sold out, with more than 260 registrants, more than half of whom were students presenting posters. The workshop is part of what Amy describes as the "Pretty-Good" present state: at the upcoming IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016), for example, 21 out of 26 organizers are women.
Unfortunately, the "Not-So-Good" aspects of the present day make a strong counterpoint. At another major conference (Artificial Intelligence and Statistics), none of 27 contributed talks were given by women, and the Computational Learning Theory Conference steering committee has only 10% female participation. One of the paths out of this imbalance that WiML sees is mentoring: Greenwald led a mentoring session on work-life balance. She also presented a poster ("Learning and Representing Social Norms: A Key to Human-Machine Collaboration") in support of the conference's commitment to sharing the most recent and compelling research in the field.