Networks of Control | Cracked Labs

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Wolfie Christl and Sarah Spiekermann; Networks of Control; Facultas, Vienna; 2016; 185 pages; landing.
Teaser: A Report on Corporate Surveillance, Digital Tracking, Big Data & Privacy

Table of Contents

  1. Preface
  2. Introduction
  3. Analyzing Personal Data
    1. Big Data and predicting behavior with statistics and data mining
    2. Predictive analytics based on personal data: selected examples
      1. The “Target” example: predicting pregnancy from purchase behavior
      2. Predicting sensitive personal attributes from Facebook Likes
      3. Judging personality from phone logs and Facebook data
      4. Analyzing anonymous website visitors and their web searches
      5. Recognizing emotions from keyboard typing patterns
      6. Forecasting future movements based on phone data
      7. Predicting romantic relations and job success from Facebook data
    3. De-anonymization and re-identification
  4. Analyzing Personal Data in Marketing, Finance, Insurance and Work
    1. Practical examples of predicting personality from digital records
    2. Credit scoring and personal finance
    3. Employee monitoring, hiring and workforce analytics
    4. Insurance and healthcare
    5. Fraud prevention and risk management
    6. Personalized price discrimination in e-commerce
  5. Recording Personal Data – Devices and Platforms
    1. Smartphones, mobile devices and apps – spies in your pocket?
    2. Car telematics, tracking-based insurance and the Connected Car
      1. Data abuse by apps
    3. Wearables, fitness trackers and health apps – measuring the self
      1. A step aside – gamification, surveillance and influence on behavior
      2. Example: Fitbit’s devices and apps
      3. Transmitting data to third parties
      4. Health data for insurances and corporate wellness
    4. Ubiquitous surveillance in an Internet of Things?
      1. Examples – from body and home to work and public space
  6. Data Brokers and the Business of Personal Data
    1. The marketing data economy and the value of personal data
    2. Thoughts on a ‘Customers’ Lifetime Risk’ – an excursus
    3. From marketing data to credit scoring and fraud detection
    4. Observing, inferring, modeling and scoring people
    5. Data brokers and online data management platforms
    6. Cross-device tracking and linking user profiles with hidden identifiers
    7. Case studies and example companies
      1. Acxiom – the world’s largest commercial database on consumers
      2. Oracle and their consumer data brokers Bluekai and Datalogix
      3. Experian – expanding from credit scoring to consumer data
      4. arvato Bertelsmann – credit scoring and consumer data in Germany
      5. LexisNexis and ID Analytics – scoring, identity, fraud and credit risks
      6. Palantir – data analytics for national security, banks and insurers
      7. Alliant Data and Analytics IQ – payment data and consumer scores
      8. Lotame – an online data management platform (DMP)
      9. Drawbridge – tracking and recognizing people across devices
      10. Flurry, InMobi and Sense Networks – mobile and location data
      11. Adyen, PAY.ON and others – payment and fraud detection
      12. MasterCard – fraud scoring and marketing data
  7. Summary of Findings and Discussion of its Societal Implications
    1. Ubiquitous data collection
    2. A loss of contextual integrity
    3. The transparency issue
    4. Power imbalances
    5. Power imbalances abused: systematic discrimination and sorting
    6. Companies hurt consumers and themselves
    7. Long term effects: the end of dignity?
    8. Final reflection: From voluntary to mandatory surveillance?
  8. Ethical Reflections on Personal Data Markets (by Sarah Spiekermann)
    1. A short Utilitarian reflection on personal data markets
    2. A short deontological reflection on personal data markets
    3. A short virtue ethical reflection on personal data markets
    4. Conclusion on ethical reflections
  9. Recommended Action
    1. Short- and medium term aspects of regulation
    2. Enforcing transparency from outside the “black boxes”
    3. Knowledge, awareness and education on a broad scale
    4. A technical and legal model for a privacy-friendly digital economy
  10. List of tables
  11. List of figures
  12. References

Mentions

yes

Quoted

  • Anna Fielder, Chair of Privacy International
  • Courtney gabrielson, International Association of Privacy Professionals (IAPP)

References

There are 677 footnoes, which are distinct from the references.
There are 211 references.

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