Big data has limitations in solving complex problems. While data science can improve predictions by 10%, human intelligence can improve understanding by 10 times when dealing with small, messy datasets. To effectively use data for strategic problems requires a human-centered approach that recognizes the limits of human processing, acknowledges data biases and gaps, combines data with theory to build understanding, and integrates quantitative findings with qualitative stories. Progress requires collaborative partnerships between humans and machines.

1. DATA

2. David Brooks
Op-Ed, February 13th 2013
“What Data Can’t Do”

3. “Big Data has trouble
with Big Problems”
- David Brooks

4. Advertising

5. Advertising Prediction

7. DATA:SCIENCE

8. Jeff Hammerbacher! DJ Patil!

10. Data Science
Kosinski et al PNAS 2013

11. Liking Curly Fries
on Facebook is
top predictor of
intelligence

12. DATA:SCIENCE

13. DATA:intelligence

14. Iraq:2007

15. Open Source Data Collection
War IED

16. Iraq
Frequency
α = 2.31
xmin
Attack Size

17. Iraq
PREDICT?
Frequency
α = 2.31
xmin
Attack Size

18. Insurgent model: Nature 2009

19. Impact of increasing troop numbers
Zhao et al, Phys. Rev. Lett. 2009

20. DATA:SCIENCE
vs.
DATA:intelligence

21. Data:SCIENCE Data:Intelligence
Improvement 10% 10x

22. Data:SCIENCE Data:Intelligence
Improvement 10% 10x
Model goal Predict/Optimize Create/Change

23. Data:SCIENCE Data:Intelligence
Improvement 10% 10x
Model goal Predict/Optimize Create/Change
Decision Algorithm Human

24. Data:SCIENCE Data:Intelligence
Improvement 10% 10x
Model goal Predict/Optimize Create/Change
Decision Algorithm Human
Data Big/Clean Small/Messy

25. Data:SCIENCE Data:Intelligence
Improvement 10% 10x
Model goal Predict/Optimize Create/Change
Decision Algorithm Human
Data Big/Clean Small/Messy
Communication Equations Stories

26. Data:SCIENCE Data:Intelligence
Improvement 10% 10x
Model goal Predict/Optimize Create/Change
Decision Algorithm Human
Data Big/Clean Small/Messy
Communication Equations Stories
Problem Tactical Strategic

27. STRATEGIC TOOLKIT
Google + Excel + Powerpoint

29. “What is the most
effective way to allocate
capital to spur growth in
K-12 education
technology”!
**…and how will I know if we’re successful!

30. “What are the dominant
narratives about
climate change in
India”!
**…and how does it vary between age groups!

31. “What are my competitors
doing with advanced
flexible display
technology”!
**…should I compete or partner with them?!

32. “What is the
structure of the
insurgent groups
in Syria”!
**…what is the likely impact of peace keepers!

33. Five Heuristics
For Using Data to Solve
Big Problems

34. 1. Data needs to be designed
for human interaction

35. Human Machine

36. Human Centered UI

37. 2. Understand limits of
human processing.

39. 900 ms
Source: Nanex

40. 3. Data is messy,
incomplete and biased.

42. …Deal with it…

43. 4. Data needs theory

45. The future will look like the past…

46. Build model:Understand

47. 5. Data needs stories…
stories need data

49. Equa%on
governing
Insurgent
Dynamics
Mathematical

50. Myth:Hydra

51. BIG DATA &
BIG PROBLEMS

52. DATA:intelligence

53. Human + Machine
Interface

54. Human + Machine