Instalment 5: Data Driven Societies (Big Data and Social Physics)

MOOC Summaries - Big Data and Social Physics - Data Driven SocietiesInstalment 5: Data Driven Societies

“Trust Frameworks… Computational Legal Science… Mobile Territorial Lab…openPDS: Privacy through Personal Data Stores…” 
(Source)

Summaries

  • Intro Video
  • Trust Frameworks
  • Computational Legal Science
  • Mobile Territorial Lab
  • openPDS: Privacy through Personal Data Stores

Intro Video

  • Data driven societies: build on last four instalments, and take the lessons to the entire society.
  • Take the same data e.g. from cell phones, communication, movement, neighborhoods etc; we can see where the crime is, where the poverty etc
  • Gives us a way to think about designing society and craft better policies.
  • This type of data sharing is the new oil of the internet; but we need new ways for safer sharing.
  • Need to protects the consumer, while still allowing societies to map poverty, map crime, and build a better society.
  • Key is putting individuals in control of data that is about them e.g. notification when someone’s collecting data about you, required informed consent, auditing, and retraction.
  • City of Toronto now has a community that lives under different rules for safe data sharing, changing the risk-reward ratio for sharing; ideas include a bank for personal data (like a bank for money where they can invest data to get services, and/or take data back.
  • The goal ultimately of data driven societies is using big data for a better life.
Chop Chop MOOCs’ summary of Big Data and Social Physics

Trust Frameworks

  • We need trust frameworks in data driven societies because we are moving into new kind of data ecology.
  • Trust frameworks includes new rules about who controls the data, identity, and ways to adding permitted sharing etc
  • Ideas: NSTIC– national trusted identities in cyberspace; federating data; trusted compute cell with trust wrapper; trusted compute framework;
  • It’s very explicit what the rules are for how to share that data.
  • This new way of sharing data among people will also allow new kinds of applications and services to develop.
Chop Chop MOOCs’ summary of Big Data and Social Physics

Mobile Territorial Lab

  • The idea was building a living lab around Trento (North of Italy) giving some smart phones to people, observing their behavior, make interventions, giving back the data, in order that people can use it and exchange and have the services starting from their personal data.
  • Examples of different studies:
    • The first was to try to understand the social well-being and the stress level of the people e.g. people — with a higher number of strong ties with someone really important for them — usually have a better mood.
    • Second was spending behavior e.g. if a person is a high spender or a low spender etc how these things are connected with the mood of a person.
  • Another study was giving data back to the people, and not only feedback about their own behavior, but also comparisons with the community’s behavior.
  • Also trying to understand the monetary value that people give to their personal data – running a set of different actions, where people give their data for some money, and monetary value of these differing kinds of data are determined.
  • Now giving air monitors/sensors so people can bring them around, and help collect information about air quality, and make decisions about where to go or avoid.
  • A new way to redesign society (into data driven societies?), where you give more power to the people and people have the real control of their data, and perhaps redesign their lives?
Chop Chop MOOCs’ summary of Big Data and Social Physics

openPDS: Privacy through Personal Data Stores

  • OpenPDS – a personal data store that gives control over personal data e.g. when I go for a run, my Nike application records my training information into OpenPDS, and I can then give Pandora access to create the perfect running playlist for me.
  • Built-in safe answer mechanism means services can access rich user data without violating privacy, and users can monitor how their data is being used.
  • Why would services buy in?
    • would no longer have to collect the data themselves;
    • regulation and market pressure;
    • companies may no longer want the liabilities/hassle of hosting personal data.
  • A privacy-preserving, user controlled data repository is the way to finally unleash the potential of big data in data driven societies.
Chop Chop MOOCs’ summary of Big Data and Social Physics

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