Is it possible to use data to make predictions without enforcing existing biases?
Rhonda Evans looks at lessons from Monitor Institute’s Re-imagining Measurement initiative.
Stanford's Michael Bernstein discusses how computational systems can create collectives of experts to solve problems.
Steve Schwartz of Upaya Social Ventures, Meg Garlinghouse of LinkedIn for Good, and Corey Marshall and Splunk4Good look at real-life examples of Silicon Valley companies that are helping social sector organizations use data more effectively.
Stanford's Rob Reich and George Triantis, and Eli Sugarman of the William and Flora Hewlett Foundation's Cyber Initiative, discuss the urgent need for better understanding of cyber-social systems.
Valerie Threlfall of the Fund For Shared Insight, Krystle Onibokun of the Boys and Girls Club of the Peninsula, and Brad Dudding of the Center for Employment Opportunities talk about their experience with a new program that aims to build high quality feedback loops.
How can we work together to make our vast stores of data more useful to people working in different fields and sectors?
SSIR academic editor Johanna Mair talks with Roy Steiner of Omidyar Network, Renee Kaplan of the Skoll Foundation, Jim Bildner of the Draper Richards Kaplan Foundation, and Christian Seelos, coauthor with Mair of the new book Innovation and Scaling for Impact.
What can social sector organizations learn from large companies about using data to maximize impact?
Hal Varian, chief economist at Google, discusses methods of big data analysis that can indicate not just correlation but also causality.