Data Science for Social Impact: Case Studies, Challenges, and Opportunities

author: Rayid Ghani, Center for Data Science and Public Policy, University of Chicago
published: Oct. 6, 2016,   recorded: September 2016,   views: 24
Categories

Slides

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

Can Data Science help reduce police violence and misconduct? Can it help prevent children from getting lead poisoning? Can it help cities better target limited resources to improve lives of citizens? We’re all aware of the data science hype right now but turning this hype into any social impact takes effort. In this talk, I’ll discuss lessons learned while working on dozens of projects over the past few years with non-profits and governments on high-impact social challenges. These lessons span from challenges these organizations face when trying to use data science, to understanding how to effectively train and build cross-disciplinary teams to do practical data science, as well as what machine learning and social science research challenges need to be tackled, and what tools and techniques need to be developed in order to have a social and policy impact with machine learning.

See Also:

Download slides icon Download slides: eswc2016_ghani_data_science_01.pdf (3.4 MB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: