Big Data and algorithmic systems

What you should know: 

Big Data and algorithmic systems

Important content that should be taught in this learning unit: 

  • The principle of performance against data (see chapter 2.2.2 Nothing is for free).
  • Basic understanding of what information social media platforms have collected from us (see chapter 2.2.7 Examples Google & Facebook - What they know about us)
  • Understanding of how data from social media can be used for specific purposes (see chapter 2.2.9 Example "Cambridge Analytica": Creation of personality images).
  • Data can also unknowingly reveal information (see chapter 2.2.10 Example "Strava"; risks with public data)
  • Raising awareness of the possible use of large amounts of data in connection with algorithmic systems.
    • Example of predictive policing 
    • Example social credit system (see chapter 2.2.6 Social credit systems)

You should sensitise participants to the topic of Big Data and support them in developing an eye for the value of their data and the (sometimes unmanageable) effects of large amounts of data and its processing.  

Exercises on the topic in the CUMILA WIKI: 

  • CUMILA Wiki Exercise c2L06 - Tell-tale receipt.
  • CUMILA Wiki exercise c2L07 - Personalised advertising
  • CUMILA Wiki exercise c2L08 - Big Data

Read the relevant chapters in the module and, if necessary, work on the exercises mentioned yourself or prepare them for your lessons.