Transparent Data Mining for Big and Small Data

Part I. Transparent Mining

1. The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good
Bruno Lepri, Jacopo Staiano, David Sangokoya, Emmanuel Letouzé, Nuria Oliver

2. Enabling Accountability of Algorithmic Media: Transparency as a Constructive and Critical Lens
Nicholas Diakopoulos

3. The Princeton Web Transparency and Accountability Project
Arvind Narayanan, Dillon Reisman

Part II. Algorithmic Solutions

4. Algorithmic Transparency via Quantitative Input Influence
Anupam Datta, Shayak Sen, Yair Zick

5. Learning Interpretable Classification Rules with Boolean Compressed Sensing
Dmitry M. Malioutov, Kush R. Varshney, Amin Emad, Sanjeeb Dash

6. Visualizations of Deep Neural Networks in Computer Vision: A Survey
Christin Seifert, Aisha Aamir, Aparna Balagopalan, Dhruv Jain, Abhinav Sharma, Sebastian Grottel, Stefan Gumhold

Part III. Regulatory Solutions

7. Beyond the EULA: Improving Consent for Data Mining
Luke Hutton, Tristan Henderson

8. Regulating Algorithms’ Regulation? First Ethico-Legal Principles, Problems, and Opportunities of Algorithms
Giovanni Comandè

9. AlgorithmWatch: What Role Can a Watchdog Organization Play in Ensuring Algorithmic Accountability?
Matthias Spielkamp

Keywords: Computer Science, Data Mining and Knowledge Discovery, International IT and Media Law, Intellectual Property Law, Algorithm Analysis and Problem Complexity, Complexity, Simulation and Modeling, Big Data/Analytics