Filter Bubble or Serendipity Machine


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A presentation about personalization and the opportunities and dangers of filters.

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  • Personalization technologies on the Internet have been around for a while now, but in my perspective they really took a leap forward in to a whole new state when Facebook opened op for what was then called Facebook connect (and is now the social graph). What you are going to see here is one of the first creative uses of FB connect and it was an implementation that really blew me back.
  • Filter Bubble or Serendipity Machine

    1. 1. Filter Bubble or Serendipity Machine On_Tracks 28 November, 2011
    2. 3. The digital world of ME
    3. 9. We are living in a world where information comes to us
    4. 10. If we don’t see the information it probably isn’t important.
    5. 11. What does this mean for libraries?
    6. 12. The way it used to be
    7. 14. <ul><li>Filing cards </li></ul><ul><li>Physical book shelves </li></ul><ul><li>Active search </li></ul><ul><li>Manual build-up of relevance </li></ul><ul><li>Interaction with librarians </li></ul><ul><li>Serendipitous discoveries on the shelves </li></ul><ul><li>Topical connections through physical proximity </li></ul>
    8. 15. Today search is just… … search
    9. 16. Digitization creates fantastic opportunities
    10. 17. But with great power, comes great responsibility
    11. 18. Opportunity New ways to serve your customers
    12. 19. Responsibility Do not make your customers lazy Do not create filter bubbles
    13. 20. What is personalization?
    14. 21. Interactive elements
    15. 22. Customization
    16. 23. Rule based personalization
    17. 24. Mathematical filtering
    18. 25. Social filtering
    19. 26. Personalization and libraries
    20. 27. Interactive elements <ul><li>Not that relevant </li></ul>
    21. 28. Customization <ul><li>Subscribe to subjects </li></ul><ul><li>Subscribe to authors </li></ul><ul><li>Personal dashboard </li></ul>
    22. 29. Rule based personalization <ul><li>People who searched for phenomenology should see more of this next time they search </li></ul><ul><li>People who search for more than 5 minutes should get personal chat help </li></ul>
    23. 30. Mathematical filtering <ul><li>People who searched for ”Discipline and Punish” should also see ”The history of Sexuality”. </li></ul><ul><li>Tell us your course name and we will recommend literature </li></ul>
    24. 31. Social filtering <ul><li>What are the people at my course/research group searching for? </li></ul><ul><li>Create personal profiles, where people share their searches and reading </li></ul><ul><li>Create subject groups, where people can share search within specific areas </li></ul><ul><li>Who are my academic subject neighbors? What are they searching for/reading? </li></ul>
    25. 32. The dangers of filtering
    26. 33. We always lived in filter bubbles
    27. 34. But the digital bubble is different <ul><li>We are alone in our bubbles </li></ul><ul><li>The filter bubble is invisible </li></ul><ul><li>You don’t choose the filter bubble yourself </li></ul>
    28. 35. Why is it dangerous? <ul><li>It destroys the common agenda </li></ul><ul><li>People get stuck in one perspective </li></ul><ul><li>The death of academic creativity </li></ul>
    29. 36. What we should do as filter builders? <ul><li>Make filters transparent </li></ul><ul><li>Make it possible to opt out of filters </li></ul><ul><li>Combine machine filters with human filters </li></ul><ul><li>Build in more randomness </li></ul>
    30. 37. We need filters! But we need to build responsible filters
    31. 38. [email_address] Find this presentation on: