Big data and machine learning are among the transformative technologies of our time, and have rewritten how we work as a society. We now face the monumental task of making our data driven world just, inclusive, equitable, safe, and accessible.
The topic of our June 30 workshop will be the unique challenges of cross-disciplinarity in data science: such as power differentials between those with traditional and non-traditional backgrounds, programming and computation skills, compensation, the use of outside expertise, etc.
OPA approaches workshops in an intentional, collaborative and cross-disciplinary manner, so that people with PhDs can discover the real world problems that their expertise can help solve. We invite people from any discipline to join the discussion, listen to the problems and share what they know.
This year, we are developing a new approach to collaborative conversations that build targeted bridges across expert communities: Open Problem Workshops. With our pilot, our goal is to create a collaborative environment for discussing the problems faced by the data science community, and the insights of PhDs from outside data science.
- If you have a PhD in any field, join us to share your methods and expertise, and explore the surprising ways you can help the data science community.
- If you come from data science, share the problems you encounter that would benefit from the fresh perspectives of experts that don’t often work in data science.
- If you have a background in both academia and data science, you’re doubly invited!
We envision a world where data scientists have access to the full range of expertise PhD’s bring to complex social problems, and where people with a PhD offer their expertise with attention to the needs of the data science community.
Our inaugural event will be: June 30, 2021 at noon PT/3:00pm ET. (Tickets are available here.)
This project is jointly coordinated by Beth M. Duckles, Ph.D, Borhane Blili-Hamelin, Ph.D, and Marie-Ève Monette, Ph.D.
This event was funded by a grant from Code for Science & Society, made possible by grant number GBMF8449 from the Gordon and Betty Moore Foundation.