Three Paradoxes of Big Data - DSA ADS Course 2023
DSA ADS Course 2023
This DSA ADS course is part of a series of courses that demonstrate how to use applied data science with high performance compute and high quality data to optimize decision making in real world scenarios.
Discuss the three (3) paradoxes of big data using examples in real world scenarios.
Privacy-Aware Compression for Federated Data Analysis
Audience Selection for On-line Brand Advertising - Privacy-friendly Social Network Targeting
Automation, Big Data, and Politics: A Research Review
Learning to Protect Communications with Adversarial Neural Cryptography
Public vs. Nonpublic Data
De-identification is a process used to prevent a person’s identity from being connected with information. Organizations de-identify data for a range of reasons. Companies may have promised “anonymity” to individuals before collecting their personal information, data protection laws may restrict the sharing of personal data, and, perhaps most importantly, companies de-identify data to mitigate privacy threats from improper internal access or from an external data breach. This Essay attempts to frame the conversation around de-identification.
Consumer Subject Review Boards - Data Privacy and Legal Issues
There are only a handful of reasons to study someone very closely. If you spot a tennis rival filming your practice, you can be reasonably sure that she is studying up on your style of play. Miss too many backhands and guess what you will encounter come match time. But not all careful scrutiny is about taking advantage. Doctors study patients to treat them. Good teachers follow students to see if they are learning. Social scientists study behavior in order to understand and improve the quality of human life.
Privacy Substitutes - Privacy and Legal Issues
Big Data in Small Hands - Privacy and Legal Issues
“Big data” can be defined as a problem-solving philosophy that leverages massive datasets and algorithmic analysis to extract “hidden information and surprising correlations.” Not only does big data pose a threat to traditional notions of privacy, but it also compromises socially shared information. This point remains underappreciated because our so-called public disclosures are not nearly as public as courts and policymakers have argued—at least, not yet. That is subject to change once big data becomes user friendly.