UTS Bachelor of Creative Intelligence & Innovation (BCII) Creativity & Complexity school, February 1-12, 2016 (2 hour lecture/exercises)

1. Visualizing Complexity
utscic.edu.au
Simon Buckingham Shum
Director, Connected Intelligence Centre
Professor of Learning Informatics
University of Technology Sydney
@sbuckshum / http://Simon.BuckinghamShum.net
UTS Bachelor of Creative Intelligence & Innovation (BCII)
Creativity & Complexity school, February 1-12, 2016
(2 hour lecture/exercises)
Except where slides are linking to external resources using other licenses:
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2. how do humans
experience
complexity?
2

3. Welcome to “informed bewilderment”
“The 21st century will not be a dark
age. Neither will it deliver to most
people the bounties promised by the
most extraordinary technological
revolution in history. Rather, it may
well be characterised by informed
bewilderment.”
Manuel Castells

4. technology is a driver of complexity
can technology help with sensemaking?
4

5. key concepts
(are purple)
5

6. 3 visualization approaches to
grapple with complexity
…all of which you could use in your degree
…and your professional and personal life
6

7. 1. visualize models
of the complex system
7

8. 2. visualize possible meanings
with image/metaphor/narrative
8

9. 3. visualize the dialogue + debate
as you explore the dilemma
9

10. VUCA
Volatile • Uncertain
Complex • Ambiguous

11. From the known to the unknown
Unknown
Strange
Uncomfortable
What we know
Familiar
Comfortable

12. From the known to the unknown
Unknown
Strange
Uncomfortable
What we know
Familiar
Comfortable
“liminal space”

13. From the known to the unknown
Unknown
Strange
Uncomfortable
What we know
Familiar
Comfortable
“liminal space”

14. “Liminal Space… when you have left the tried and true
but have not yet been able to replace it with anything else.
Limina is the Latin word for threshold, the space betwixt and between
http://sojo.net/magazine/2002/01/grieving-sacred-space
…when you are between your old comfort zone and any possible new
answer… If you are not trained in how to hold
anxiety, how to live with ambiguity, how to
entrust and wait, you will run…
anything to flee this terrible cloud of unknowing.”
Richard Rohr O.F.M.
— on the spirituality of liminal space

15. 1968

16. San Francisco, Fall Joint Computer Conference — Dec. 9th 1968

17. h"p://dougengelbart.org/library/engelbart-­‐archives.html

18. h"p://dougengelbart.org/library/engelbart-­‐archives.html

19. “we need better tools to tackle
“humanity’s complex,
urgent problems”
19

20. 2000

21. Engelbart’s
work has
since been
recognised in
the highest
echelons of
computing…
http://DougEngelbart.org

22. Engelbart’s vision was not just personal
computing, but “Collective IQ”
http://visualinsight.net/_engelbart/engelbart_mural.jpg
…and cool tools alone would never be enough:
we needed culture shifts and new ways of working

23. The ‘Mother of All Demos’ 1968

24. wicked
problems
24

25. A I
artificial intelligence

26. I A
intelligence augmentation

27. collective
intelligence

28. contested
collective intelligence
…because different viewpoints are
important, and must be visible

29. 1. visualize models
of the complex system
classic scientific computing approach,
and now ‘Big Data’/Analytics in society at large
sense • model • analyse • visualise
• act / recommend action
29

30. Information Visualization & Visual Analytics
Using the power of sensors, computational processing, and computer graphics to
make the invisible visible.
30

31. 31
Hand-crafted, co-designed, systems models
(cf. the work of UTS Institute for Sustainable Futures)

32. Hand-crafted, co-designed, systems models
32
http://www.paconsulting.com/afghanistan-causal-diagram

33. Hand-crafted systems models
More of this from the Institute for Sustainable Futures later this week…
33

34. interpreting visualizations
34

35. Visualising a meeting
(Flashmeeting, Open University UK)

36. Visualising a meeting: video conference analytics
(Flashmeeting, Open University UK)

37. Session
AV Chat AV Chat
1
2
3
Mentor 1 Mentor 2
Which mentor would you want to have?...
Analytics from introductory foreign language tutorials

38. https://twitter.com/Wiswijzer2/status/414055472451575808
“Note: check the
huge difference
between knowing
and measuring…”
38

39. Bowker, G. C. and Star, L. S. (1999). Sorting Things Out: Classification and Its Consequences. MIT Press, Cambridge, MA, pp. 277, 278, 281
“Classification systems provide both a warrant
and a tool for forgetting [...] what to forget and
how to forget it [...] The argument comes down
to asking not only what gets coded in but what
gets coded out of a given scheme.”
39

41. “sensemaking”
41

42. Sensemaking: the search for plausible connections
In their review of sensemaking, Klein, et al. conclude:
“By sensemaking, modern researchers seem to mean something
different from creativity, comprehension, curiosity, mental modeling,
explanation, or situational awareness, although all these factors or
phenomena can be involved in or related to sensemaking. Sensemaking
is a motivated, continuous effort to understand connections (which can be
among people, places, and events) in order to anticipate their trajectories
and act effectively.
[…] A frame functions as a hypothesis about the connections among
data.” 42

43. Sensemaking
Karl Weick proposes that:
“Sensemaking is about such things as placement of items
into frameworks, comprehending, redressing surprise,
constructing meaning, interacting in pursuit of mutual
understanding, and patterning.”
Sensemaking in Organizations, p.6
43

44. Sensemaking
Karl Weick:
“The point we want to make here is that sensemaking is
about plausibility, coherence, and reasonableness.
Sensemaking is about accounts that are socially acceptable
and credible” (p.61)
44

45. 2. visualize possible meanings
with image/metaphor/narrative
45

46. Leadership Competencies for Complex Challenges
Palus, C.J., & Drath, W.H. (2001). Putting Something in the Middle:
An Approach to Dialogue. Reflections. 3(2), pp.28-39.
http://www.leadingeffectively.com/interdependent-leadership/wp-content/uploads/
2012/10/Mediated_dialogue_Palus-and-Drath.pdf

47. slowing down
perception and dialogue in
order to see more clearly,
and in new ways
47

51. Visual Explorer
group exercise
Chuck Palus & David Horth: Center for Creative Leadership
http://www.leadingeffectively.com/leadership-explorer/category/visualexplorer
51

52. Visual Explorer exercise
“This how I’m thinking/feeling about finding a job.”
Or: choose your own challenge or dilemma
Pick a picture that resonates with this and study it
closely,
52

53. Visual Explorer — Star Model:
Dialogue by “putting something in the middle”
2. Group members describe what
they see, using the phrase “If that
were my image…”
3. The image is ‘given back’ to
the originator so that the
originator has the last word (new
insights).
1. One person at a time describe
your image, then explain how it
relates to the question.

54. feedback?
54

55. 3. visualize the dialogue + debate
as you explore the dilemma
55

56. Issue Mapping: Questions, Ideas, Decisions, Pros + Cons
Compendium: http://compendiumng.org

57. Issue Mapping: Questions, Ideas, Decisions, Pros + Cons
Cognexus Institute: http://cognexus.org

58. Demo:
let’s visualize the collective
intelligence in the room…
58

59. My 11 year old…
59

60. My 11 year old…
60

61. My 11 year old…
61

62. My 11 year old…
62

63. My 11 year old…
63

64. My 11 year old…
64

65. My 11 year old…
65

66. My 11 year old…
66

67. Issue Mapping: BCII example from yesterday
Compendium: http://compendiumng.org

68. Compendium: http://compendiumng.org

69. 69
Key
Ques(on
An
Idea
in
response
Glyma: integrating websites into the map
Glyma: http://glyma.co

70. 70
Node
summarises
video
clip
Key
Ques(on
An
Idea
in
response
Glyma: integrating websites into the map
Glyma: http://glyma.co

71. Glyma: integrating websites into the map
71
Node
summarises
video
clip
Node
links
to
web
doc
Key
Ques(on
An
Idea
in
response
Glyma: http://glyma.co

72. Stirling Alliance: Long Term Transport Plan (Perth, AUS)
Also used for:
• Corporate strategy and org redesign
(private and public sector)
• Procurement strategy for $500M+ civil
infrastructure projects
• Project inceptions and lessons learnt
Copyright SevenSigma 2011
http://www.sevensigma.com.au/what-we-have-done/case-studies.html

73. Mapping important conversations in real time
73
Organisational scenario planning
(Open University UK)
Workflow analysis
(Shuttle Launch Control, NASA)

74. Hostage recovery scenario: how to apply political pressure?
The collective intelligence available in
the room and online: Dialogue Map
capturing the team’s deliberations
Visual background structures
the display for planning

75. 75
NASA Mobile Agents Field Trials:
Simulating an Earth/Mars work system
http://bit.ly/MarsFieldTrials

76. General
Election
debates, 2010
76
http://people.kmi.open.ac.uk/sbs/2010/04/debate-replay-with-map

77. generating documents from
conversational maps
77

78. Document generation from IBIS maps
78

79. Document generation from IBIS maps
79

80. Collaboratively built
map from a meeting
From a map template to documentation (Y2K planning)
Requirements
specification in
the org template
B uild
Ass ignable
Inventory
Ass ignable
Inventory
D evia tions /
C ha nge s
(E ngr S c hed)
A pprova ls
Integrate d/
R e vise d
R e quire me nts
F ield
S pec ific
As signm ents
/As signm e nt
Lis t
Insta lla tion
D e tails/
S pe cs /N D O
As signa ble
Inventory
N otice (E 1)
Data flow diagram for engineer

81. Hands-on:
mapping a conversation as a
network of ideas
81

82. Recording from a fictional meeting with a telecoms client
Summarise this as clearly as possible as an issue map which you will send your client
as a record of the key issues, the options considered, the decisions made, and why.
Client: Could you run some analytics on customer comments to see if there’s anything interesting?
You: Well there are many approaches we could take: what are you looking for?
Client: Basically, can we predict if they’re about to switch from us?
You: There’s research evidence that they follow their friends and family in switching phone provider. As for comments, the evidence
seems to be that most tweet this, though some will complain to you first. Sentiment mining is a possibility. Twitter gives you social
networks too.
Client: That social stuff is really interesting, and I know Belstra are testing this. But won’t customers find it creepy that we analyse
their tweets?
You: Possibly, and remember that twitter feed is always filtered. OK, well it’s safer to analyse your own databases. Is it just phone
or are you interested in other services too?... And do you have data on any social ties between customers?
Client: Internet and TV are also relevant but let’s start with phone. The customer DB knows about families. OK let’s just mine our
CRM data for telltale comments to start with, and see if that tallies with family members following each other out the door.
You: OK, we can merge datasets and test a predictive model of each independently, and combined. 82

83. Issue Mapping: Questions, Ideas, Decisions, Pros + Cons
Compendium: http://compendiumng.org

84. Example map from this exercise
84

85. Example map from this exercise
85

86. Hybrid: fusing different
ways of knowing

88. scaling this for the web
Towards “Contested Collective Intelligence”
88

89. An Evidence Hub shows who in the community
is tackling which parts of the problem
People / Organizations / Projects / Claims / Evidence
Evidence Hub for Research by Children & Young People: http://rcyp.evidence-hub.net
89

90. Impact Map: how much evidence is there to
support an improvement hypothesis?
http://oermap.org/hypothesis/586/hypothesis-i-transition 90

91. Knowledge Art
91

92. some people know how to create the
right representation
at the
right moment
to harness a
group’s energy and insights
…shared meaning

93. Improv kitchen sensemaking

94. 94
A language for talking about the skills and dispositions
needed to use the right representation at the right moment
to help a team make sense of a problem

95. 95

96. 96

97. Book: “Constructing Knowledge Art”
https://www.facebook.com/constructingknowledgeart
97

98. Summary
Towards Contested
Collective Intelligence tools
for complex problems
98

99. “Augmenting human intellect” http://DougEngelbart.org
Phenomena in complex social systems Role for Human+Computer Collective Intelligence?
Dangers of entrained thinking from experts who fail to recognise a novel
phenomenon
• Technology should pay particular attention to exceptions
• Computer-supported argumentation for rigorous reflection
• Design tools that encourage diverse perspectives and highlight
inconsistencies
Human systems sometimes can be modelled but outcomes are
unpredictable — we often make sense of them retrospectively through
the construction of plausible narratives
• Stories and coherent pathways are important
• Reflection and overlaying of interpretation(s) is critical
• Imagery, metaphor, narrative
Patterns are emergent through the interaction of agents, both machine
and human
• Generate gestalt views from the data evidenced in the platform, not
from preconceptions
Much of the relevant knowledge in the network is tacit, shared through
behaviour and discourse, not formal codifications
• Scaffold the formation of significant inter-personal, learning
relationships — not everything can be written down
Many small signals can build over time into a significant force/change • Enable individuals to monitor the environment, highlighting
important events and connections — aggregate and analyse
Sources include: Weick (1995); Kurtz & Snowden (2003); Browning, L. and Boudès, T. (2005); Hagel et al (2010). See also http://oro.open.ac.uk/23352

100. “liminal space tools” should help us grapple
with uncertainty + complexity…
manage webs of connections
think critically + engage in debate
hold conflicting perspectives in tension
wield tools for collective sensemaking
integrate identity + aspiration with work

101. These slides, videos + readings:
http://Simon.BuckinghamShum.net/2016/02/bcii-visualizing-complexity
utscic.edu.au