Article by Joshua Snoke, and Claire McKay Bowen: “Suppose you had a data set that contained records of individuals, including demographics such as their age, sex, and race. Suppose also that these data contained additional in-depth personal information, such as financial records, health status, or political opinions. Finally, suppose that you wanted to glean relevant insights from these data using machine learning, causal inference, or survey sampling adjustments. What methods would you use? What best practices would you ensure you followed? Where would you seek information to help guide you in this process?…(More)”
How to contribute:
Did you come across – or create – a compelling project/report/book/app at the leading edge of innovation in governance?
Share it with us at info@thelivinglib.org so that we can add it to the Collection!
About the Curator
Get the latest news right in you inbox
Subscribe to curated findings and actionable knowledge from The Living Library, delivered to your inbox every Friday
Related articles
DATA, privacy
Why the most valuable workforce data is voluntary – and how to get it
Posted in July 21, 2025 by Stefaan Verhulst
privacy
Designing Consent: Choice Architecture and Consumer Welfare in Data Sharing
Posted in July 16, 2025 by Stefaan Verhulst
privacy
The IRS Is Building a Vast System to Share Millions of Taxpayers’ Data With ICE
Posted in July 16, 2025 by Stefaan Verhulst