Is data objective? We like to think so, but dig just one layer underneath the numbers and you will find that who is counted, what is gathered, and how data is interpreted are all subjective decisions made by people – and sometimes, the data itself is indecipherable without additional perspective.
This presents a special challenge in the realm of data science for social good, given that many of the organizations with the greatest need for data science lack understanding of how to engage with data and those who know how to use it.
In this interactive talk, we'll examine the key conditions needed for successful cross-sector collaboration: common purpose, common language, sufficient resources, and trust. We will do a live exercise followed by a closer look at successful multi-stakeholder data projects.
For students in the University of Washington's Data Science for Social Good program only.