BCII 2016 - Visualizing Complexity

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: This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License

how do humans experience complexity?

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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

technology is a driver of complexity

can technology help with sensemaking?

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key concepts (are purple)

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3 visualization approaches to grapple with complexity

…all of which you could use in your degree …and your professional and personal life

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1. visualize models of the complex system

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2. visualize possible meanings with image/metaphor/narrative

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

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VUCA

Volatile • Uncertain

Complex • Ambiguous

From the known to the unknown

Unknown Strange Uncomfortable

What we know Familiar

Comfortable

From the known to the unknown

Unknown Strange Uncomfortable

What we know Familiar

Comfortable

“liminal space”

“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

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

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

“we need better tools to tackle “humanity’s complex,

urgent problems”

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Engelbart’s work has since been recognised in the highest echelons of computing…

http://DougEngelbart.org

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

The ‘Mother of All Demos’ 1968

wicked problems

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A I artificial intelligence

I A intelligence augmentation

collective intelligence

contested collective intelligence …because different viewpoints are

important, and must be visible

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

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

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

Hand-crafted, co-designed, systems models

32 http://www.paconsulting.com/afghanistan-causal-diagram

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

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interpreting visualizations

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Visualising a meeting (Flashmeeting, Open University UK)

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

Sess

ion

AV Chat AV Chat

1

2

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Mentor 1 Mentor 2

Which mentor would you want to have?... Analytics from introductory foreign language tutorials

http

s://t

witt

er.co

m/W

isw

ijzer

2/st

atus

/414

0554

7245

1575

808

“Note: check the huge difference between knowing and measuring…”

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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.”

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“sensemaking” 41

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.”

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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

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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)

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2. visualize possible meanings with image/metaphor/narrative

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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

slowing down perception and dialogue in order to see more clearly,

and in new ways 47

Visual Explorer group exercise

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

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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,

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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.

feedback? 54

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

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Issue Mapping: Questions, Ideas, Decisions, Pros + Cons

Compendium: http://compendiumng.org


Cognexus Institute: http://cognexus.org

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

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My 11 year old…

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My 11 year old…

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My 11 year old…

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My 11 year old…

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My 11 year old…

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My 11 year old…

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My 11 year old…

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My 11 year old…

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Issue Mapping: BCII example from yesterday


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Key Ques(on

An Idea in response

Glyma: integrating websites into the map

Glyma: http://glyma.co

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Node summarises video clip

Key Ques(on

An Idea in response




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Node summarises video clip

Node links to web doc

Key Ques(on

An Idea in response


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

Mapping important conversations in real time

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Organisational scenario planning (Open University UK)

Workflow analysis (Shuttle Launch Control, NASA)

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

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NASA Mobile Agents Field Trials: Simulating an Earth/Mars work system

http://bit.ly/MarsFieldTrials

General Election debates, 2010

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

generating documents from conversational maps

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Document generation from IBIS maps

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Document generation from IBIS maps

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Collaboratively built map from a meeting

From a map template to documentation (Y2K planning)

Requirements specification in the org template

B uildAss ign ableInventory

Ass ign ableInventory

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 ieldS pec ific

As signm ents/As signm e nt

Lis t

Insta lla tionD e tails/

S pe cs /N D O

As signa bleInventory

N otice (E 1)

Data flow diagram for engineer

Hands-on: mapping a conversation as a

network of ideas

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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

Example map from this exercise

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Example map from this exercise

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Hybrid: fusing different ways of knowing

scaling this for the web

Towards “Contested Collective Intelligence” 88

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

Impact Map: how much evidence is there to support an improvement hypothesis?

http://oermap.org/hypothesis/586/hypothesis-i-transition 90

Knowledge Art

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some people know how to create the right representation

at the right moment

to harness a group’s energy and insights

…shared meaning

Improv kitchen sensemaking

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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

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

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Summary Towards Contested

Collective Intelligence tools for complex problems

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“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

“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

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

utscic.edu.au

BCII 2016 - Visualizing Complexity

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