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BIG DATA AND THEIR PROBLEM


Luciano Floridi
www.philosophyofinformation.net

Research Chair in Philosophy of Information
UNESCO Chair in Information and Computer Ethics
University of Hertfordshire

Faculty of Philosophy &
Department of Computer Science
University of Oxford
OUTLINE

    Three Ideas
     Time: Hyperhistory
     Space: Infosphere
     Agents: the Fourth Revolution
    Big Data
     Their Rise
     Their Challenges
     The Problem and its Solution
    Conclusion
FIRST IDEA – TIME: HYPERHISTORY




     No ICTs

          Individual and social well-being
           independent of ICT

                           Individual and social well-being
                            dependent on ICT
FIRST IDEA – TIME: HYPERHISTORY


 First Big Data Society: Ur, city state in Sumer (Iraq).
 End of the third millennium: the most developed and
 centralized bureaucratic state in the world.
 Library of more than 500,000 clay tablets.
 Business and Administration documents.
SECOND IDEA – SPACE: INFOSPHERE

 Today the world adapts to smart technologies
 limited capacities increasingly well.




  Enveloping the world without fully realising it.
SECOND IDEA – SPACE: INFOSPHERE




       Dishwasher vs. Humanoid Robot
SECOND IDEA – SPACE: INFOSPHERE
 20

17.5

 15

12.5

 10
  Ca. 18% of EU population used a laptop to access
  the internet, via wireless away from home or work.
 7.5

  5

 2.5

  0

       2004   2005   2006   2007   2008   2009   2010
SECOND IDEA – SPACE: INFOSPHERE




 BIG GREEN DATA?
SECOND IDEA – SPACE: INFOSPHERE




   Inside the computer




                         Outside the computer
THIRD IDEA – AGENTS: THE FOURTH REVOLUTION

  Knowledge, Science, Technology change our
  understanding in two fundamental ways.

                                 Introvert or about ourselves.




 Extrovert or about the world.
THIRD IDEA – AGENTS: THE FOURTH REVOLUTION

 We are not immobile, at the centre of the universe
 (Copernicus).

 We are not unnaturally detached and diverse from the
 rest of the animal world (Darwin).

 We are not Cartesian subjects entirely transparent to
 ourselves (Freud).



 We are not disconnected agents, but
 informational organisms (inforgs),
 sharing with biological and engineered
 agents the infosphere (Turing).
THE RISE OF BIG DATA




                       POWER
                       Moor’s Law
                       1m fold in 40 years
THE RISE OF BIG DATA

                          $ 100 trillions
                          Qatar (57/190) GDP 98 trillions




COST
iPad: 1600m IPS, 1/100m in 40 yrs, 1/1000b in 60 yrs
THE RISE OF BIG DATA




   1 exabyte = 50,000 yrs of DVD
       5 exabytes = all the words ever spoken
THE RISE OF BIG DATA

                             improve



                  innovate              taylor



what BD can do for you
                             Big
                             Data
                   decide               predict



                             simulate
THE CHALLENGES OF BIG DATA

                         Acquisition/Storage

                             Quality/Usability

                              Security/Safety

                                Accessibility

                                 Analytics

                                   Law/Ethics

                                    Costs

 Not enough space
THE PROBLEM WITH BIG DATA




 Small patterns
THE PROBLEM WITH BIG DATA




 Small patterns may be insignificant: half of your
 data is junk, you just do not know which half.
THE PROBLEM WITH BIG DATA

                25 products allow Target to assign
                each shopper a “pregnancy
                prediction” score, estimate her due
                date and send coupons timed to
                specific stages of her pregnancy.

 Small patterns may be significant if aggregated:
 loyalty cards and shopping suggestions.
THE PROBLEM WITH BIG DATA




 Small patterns may be significant if compared:
 same credit card used in two places/same time.
THE PROBLEM WITH BIG DATA




 Small patterns may be significant if absent:
 the silence of the dog.
THE PROBLEM WITH BIG DATA



    Q               A              I

what we need   what we have   what we want
CONCLUSION




 a knower is “the man who knows how to ask and
 answer questions” (Plato, Cratylus, 390c)
BIG DATA AND THEIR PROBLEM
                             Luciano Floridi
                     www.philosophyofinformation.net


                                            THANK YOU!


ACKNOWLEDGEMENTS
Many thanks to Sander Duivestein, Menno van Doorn, SOGETI,
and all the staff who made the meeting possible.
COPYRIGHT DISCLAIMER
Texts, marks, logos, names, graphics, images, photographs, illustrations, artwork, audio clips, video clips, and
software copyrighted by their respective owners are used on these slides for non-commercial, educational and
personal purposes only. Use of any copyrighted material is not authorized without the written consent of the
copyright holder. Every effort has been made to respect the copyrights of other parties. If you believe that your
copyright has been misused, please direct your correspondence to: l.floridi@herts.ac.uk stating your position and I
shall endeavour to correct any misuse as early as possible.

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VINT Symposium 2012: Recorded Future | Luciano Floridi

  • 1. BIG DATA AND THEIR PROBLEM Luciano Floridi www.philosophyofinformation.net Research Chair in Philosophy of Information UNESCO Chair in Information and Computer Ethics University of Hertfordshire Faculty of Philosophy & Department of Computer Science University of Oxford
  • 2. OUTLINE  Three Ideas  Time: Hyperhistory  Space: Infosphere  Agents: the Fourth Revolution  Big Data  Their Rise  Their Challenges  The Problem and its Solution  Conclusion
  • 3. FIRST IDEA – TIME: HYPERHISTORY  No ICTs  Individual and social well-being independent of ICT  Individual and social well-being dependent on ICT
  • 4. FIRST IDEA – TIME: HYPERHISTORY First Big Data Society: Ur, city state in Sumer (Iraq). End of the third millennium: the most developed and centralized bureaucratic state in the world. Library of more than 500,000 clay tablets. Business and Administration documents.
  • 5. SECOND IDEA – SPACE: INFOSPHERE Today the world adapts to smart technologies limited capacities increasingly well. Enveloping the world without fully realising it.
  • 6. SECOND IDEA – SPACE: INFOSPHERE Dishwasher vs. Humanoid Robot
  • 7. SECOND IDEA – SPACE: INFOSPHERE 20 17.5 15 12.5 10 Ca. 18% of EU population used a laptop to access the internet, via wireless away from home or work. 7.5 5 2.5 0 2004 2005 2006 2007 2008 2009 2010
  • 8. SECOND IDEA – SPACE: INFOSPHERE BIG GREEN DATA?
  • 9. SECOND IDEA – SPACE: INFOSPHERE Inside the computer Outside the computer
  • 10. THIRD IDEA – AGENTS: THE FOURTH REVOLUTION Knowledge, Science, Technology change our understanding in two fundamental ways. Introvert or about ourselves. Extrovert or about the world.
  • 11. THIRD IDEA – AGENTS: THE FOURTH REVOLUTION We are not immobile, at the centre of the universe (Copernicus). We are not unnaturally detached and diverse from the rest of the animal world (Darwin). We are not Cartesian subjects entirely transparent to ourselves (Freud). We are not disconnected agents, but informational organisms (inforgs), sharing with biological and engineered agents the infosphere (Turing).
  • 12. THE RISE OF BIG DATA POWER Moor’s Law 1m fold in 40 years
  • 13. THE RISE OF BIG DATA $ 100 trillions Qatar (57/190) GDP 98 trillions COST iPad: 1600m IPS, 1/100m in 40 yrs, 1/1000b in 60 yrs
  • 14. THE RISE OF BIG DATA 1 exabyte = 50,000 yrs of DVD 5 exabytes = all the words ever spoken
  • 15. THE RISE OF BIG DATA improve innovate taylor what BD can do for you Big Data decide predict simulate
  • 16. THE CHALLENGES OF BIG DATA Acquisition/Storage Quality/Usability Security/Safety Accessibility Analytics Law/Ethics Costs Not enough space
  • 17. THE PROBLEM WITH BIG DATA Small patterns
  • 18. THE PROBLEM WITH BIG DATA Small patterns may be insignificant: half of your data is junk, you just do not know which half.
  • 19. THE PROBLEM WITH BIG DATA 25 products allow Target to assign each shopper a “pregnancy prediction” score, estimate her due date and send coupons timed to specific stages of her pregnancy. Small patterns may be significant if aggregated: loyalty cards and shopping suggestions.
  • 20. THE PROBLEM WITH BIG DATA Small patterns may be significant if compared: same credit card used in two places/same time.
  • 21. THE PROBLEM WITH BIG DATA Small patterns may be significant if absent: the silence of the dog.
  • 22. THE PROBLEM WITH BIG DATA Q A I what we need what we have what we want
  • 23. CONCLUSION a knower is “the man who knows how to ask and answer questions” (Plato, Cratylus, 390c)
  • 24. BIG DATA AND THEIR PROBLEM Luciano Floridi www.philosophyofinformation.net THANK YOU! ACKNOWLEDGEMENTS Many thanks to Sander Duivestein, Menno van Doorn, SOGETI, and all the staff who made the meeting possible. COPYRIGHT DISCLAIMER Texts, marks, logos, names, graphics, images, photographs, illustrations, artwork, audio clips, video clips, and software copyrighted by their respective owners are used on these slides for non-commercial, educational and personal purposes only. Use of any copyrighted material is not authorized without the written consent of the copyright holder. Every effort has been made to respect the copyrights of other parties. If you believe that your copyright has been misused, please direct your correspondence to: l.floridi@herts.ac.uk stating your position and I shall endeavour to correct any misuse as early as possible.