Transparent Data Mining for Big and Small Data

Book Overview

Part I: Transparent Mining.- Chapter 1: The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good.- Chapter 2: Enabling Accountability of Algorithmic Media: Transparency as a Constructive and Critical Lens.- Chapter 3: The Princeton Web Transparency and Accountability Project.- Part II: Algorithmic solutions.- Chapter 4: Algorithmic Transparency via Quantitative Input Influence.- Chapter 5.- Learning Interpretable Classification Rules with Boolean Compressed Sensing.- Chapter 6: Visualizations of Deep Neural Networks in Computer Vision: A Survey.- Part III: Regulatory solutions.- Chapter 7: Beyond the EULA: Improving Consent for Data Mining.- Chapter 8: Regulating Algorithms Regulation? First Ethico-legal Principles, Problems and Opportunities of Algorithms.- Chapter 9: Algorithm Watch: What Role Can a Watchdog Organization Play in Ensuring Algorithmic Accountability?

• Format: Paperback
• Language: English
• ISBN: 331985299X
• ISBN13: 9783319852997
• Release Date: July 2018
• Publisher: Springer
• Length: 215 Pages
• Weight: 0.74 lbs.
• Dimensions: 0.5" x 6.1" x 9.2"