Data Ethics Philosophy and ethics of big data  
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What Distinguishes Surveillance, Monitoring, and Tracking?

  Center Outline  

Data gathering, processing, and application – along with subsequent philosophical and ethical debates – occur on three levels:

  • Social
  • Emotional
  • Economic

Data Ethics concentrates on the economic, with its corresponding tracking and targeting.



  • Field of application: Social
  • Observation type: Surveillance
  • Executed by: Society (through governmental institutions)
  • Aimed at: Society (civilian population)
  • Purpose: Public security and welfare
  • Examples:
    • Screening email to detect signs of impending terrorism
    • Scanning car license-plates to study traffic patterns


  • Field of application: Emotional
  • Observation type: Monitoring
  • Executed by: Discrete individuals
  • Aimed at: Discrete individuals
  • Purpose: Modulate personal emotions
  • Examples:
    • The collegian lingering at the bar to see if the girl he likes gets affectionate with the Lacrosse player.
    • The mother placing a baby monitor near the crib to be alerted when the newborn cries.
  • Note: Emotional monitoring is currently entering the space of big data ethics as software overlays combined with facial recognition algorithms and wearable hardware transform interpersonal encounters into big data scenes.


  • Field of application: Economic
  • Observation type: Tracking
  • Executed by: Private enterprises
  • Aimed at: Consumers.
  • Purposes: Target consumers' convenience, desires, money
  • Examples
    • Rudimentary: a retailer using loyalty cards to track purchases to learn what patrons’ have found desirable.
    • Contemporary: a retailer processes reams of purchasing histories to predict products that a specific patron will find desirable.
  • Critical historical moments:
    • Data escapes commercial silos.
      • Information gathered by a retailer (maternity clothes purchased) is used to promote a distinct service (natural birthing centers begin sending mailers).
    • Data becomes an independent sources of economic activity.
      • Organizations engaging in no direct consumer interactions acquire information from retailers, social media platforms, government agencies and similar, to synthesize and then resell to the original gatherers as fuller profiles.
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