Transparent Data Mining for Big and Small Data

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 AlgorithmicAccountability?

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• Bases de Dados
• Algoritmos e estruturas de dados
• Os sistemas especialistas / sistemas baseados em conhecimento
• Entretenimento e lei dos media
• Cibernética e teoria dos sistemas
• Modelagem computacional e simulação
• Mineração de Dados
• Matemática para engenheiros

Transparent Predictive Models;Glass-box Algorithms;Black-box Algorithms;Transparent vs Opaque Algorithms;Automated Decision Making;Big Data Paradigm Shift;algorithm analysis and problem complexity;complexity