Workshop at AAAI 2017

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."
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).
The workshop will include:
  • confirmed invited speakers to highlight hot topics in AI:
    • Judy Goldsmith, University of Kentucky, AI and ethics
    • Ece Kamar, Microsoft Research Redmond, "Directions in Hybrid Intelligence: Complementing AI Systems with Human Intelligence"
    • Sheila McIlraith, University of Toronto;
    • Jennifer Neville, Purdue University
    • Luis Ortiz, University of Michigan Dearborn, Game theory.
  • Marie desJardins, University of Maryland, Baltimore County, "Finding Balance and Joy in an Academic/Research Career in AI"
  • a panel on careers in AI, both in academia and in industry;
  • some presentations from peer-reviewed submissions;
  • small group discussions on how to navigate a conference and networking opportunities.
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/