Including the Human inHumanitarian Big Data    Sara-Jayne Farmer      @bodaceacat
The UN’s Development Reversal Problem                                        2
Where we’d like to be                        3
How bad is it? 2008 – 2011 information lags                                              4
2008: Not knowing what, who, where                                     5
2011: New Data Sources                         6
But new data only gets us so far…Humans don’t have all the info, machines don’t have all the smarts                       ...
Hunchworks: hypothesis management» System = people + processes + tech» Break down the siloes: Engage and connect the globa...
Hunch Mechanism» Detect an interesting “weak signal”» Hypothesize (make a hunch) about the nature of the signal» Share the...
Issues: Community, Complementary skills                                          10
Issues: Encouraging use, encouraging Trust                                             11
Issues: Encouraging Action“is a hunch true enough to take action?”                                           12
Issues: Security, localisation, bandwidth                                            13
Issues: fun problems we’re working on» Hunch set management  • Clustering: hunches are related  • Merging: hunches are the...
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Including the Human in Humanitarian Big Data (extended talk)

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Talk given by Sara-Jayne Farmer in November 2011.

Published in: Technology, Education
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Including the Human in Humanitarian Big Data (extended talk)

  1. 1. Including the Human inHumanitarian Big Data Sara-Jayne Farmer @bodaceacat
  2. 2. The UN’s Development Reversal Problem 2
  3. 3. Where we’d like to be 3
  4. 4. How bad is it? 2008 – 2011 information lags 4
  5. 5. 2008: Not knowing what, who, where 5
  6. 6. 2011: New Data Sources 6
  7. 7. But new data only gets us so far…Humans don’t have all the info, machines don’t have all the smarts 7
  8. 8. Hunchworks: hypothesis management» System = people + processes + tech» Break down the siloes: Engage and connect the global network of UN and international development field staff with analysts and decision makers» Use the machines better: use agents to detect weak signals» Use the people better: Encourage „hunches‟ (hypotheses) about anomalous or interesting data and observations» Encourage cooperation: Rapidly collect information about emerging situations» Combine strengths: mix human insight with data analysis results 8
  9. 9. Hunch Mechanism» Detect an interesting “weak signal”» Hypothesize (make a hunch) about the nature of the signal» Share the hunch with your social graph» Attract related signals and evidence» Verify hunch by engaging communities of practice» Act» Use confirmed hunch to refine trust within the system 9
  10. 10. Issues: Community, Complementary skills 10
  11. 11. Issues: Encouraging use, encouraging Trust 11
  12. 12. Issues: Encouraging Action“is a hunch true enough to take action?” 12
  13. 13. Issues: Security, localisation, bandwidth 13
  14. 14. Issues: fun problems we’re working on» Hunch set management • Clustering: hunches are related • Merging: hunches are the same thing • Splitting: hunch has changed significantly» Mixing human and bot users • Autonomy: how to share information, decisions, responsibility • Managing culture differences between humans and bots» Managing credibility • Rating hunches, users, data • Overall and friends‟ ratings» Hunch network as a reasoning system • vs “a hunch is the discussion surrounding it” 14
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