A CRA-W Discipline Specific Workshop
Participation in AI by groups traditionally under-represented in computer science is is a fraction of what is needed to have a workforce that reflects the diversity in the society. The decrease in the number of women and members of other under-represented groups in AI is specially worrisome, because AI over the years had enjoyed a larger representation of women compared to other areas of computer science.
In the last few months, there has been a flurry of activities and discussion on the problem of diversity in AI:
- Writing on Reddit Jeff Dean warned: “I am personally not worried about
an AI apocalypse, as I consider that a completely made-up fear. I am
concerned about the lack of diversity in the AI research community and
in computer science more generally.”
- Computer Vision Stanford faculty Fei-Fei Li talked at the White House Frontiers Conference about Why AI Needs Diversity.
- Olga Russakovsky, postdoctoral research fellow at CMU, says"Today there’s a lot of fascinating work going on in AI,
but we’re also kind of in a rut. We’ve tended to breed the same style
of researchers over and over again—people who come from similar
backgrounds, have similar interests, read the same books as kids, learn
from the same thought leaders, and ultimately do the same kinds of
research. Given that AI is such an all-encompassing field, and a giant
part of our future, we can’t afford to do that anymore."
- There is evidence of bias, even among well intentioned people. Read the last sentence in the abstract of this study on Single versus Double Blind Reviewing at WSDM 2017.
The goal of the workshop is to discuss the importance of having a diverse set of approaches to solve AI problems and address issues facing members of under-represented groups in AI. Invited speakers will present research directions in various areas within AI to highlight the diversity of topics and methods. Some cases studies and best practices to change the situation at all levels, from K-12 to college level and in the work force, will be presented.
Topics of interest for contributed papers:
- studies on the causes of under-representation and how to address them;
- case studies and best practices to increase diversity of students;
- case studies and best practices to increase diversity in the work force (academia, industry, government, research labs).
We have an exciting program for the day. Look at the Program to see the amazing list of invited speakers and panelists.
Anyone interested in addressing diversity in AI is invited to attend.
Scholarships (funded by CRA-W) are available for students and postdocs from under-represented groups who are US citizens/permanent residents. For details and to apply look at Travel awards.
https://sites.google.com/a/umn.edu/aaai-2017-diversity/
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https://sites.google.com/a/umn.edu/aaai-2017-diversity/