Patterns that Connect: Exploring the concept of pattern in the face of growing complexity

Patterns that Connect
Exploring the concept of pattern
in the face of growing complexity
Helene Finidori
ECCO/GBI Seminar – 2 December 2016

We will examine:
•  The challenges brought about by complexity and the types of responses needed in order to
address these challenges from a systemic and interconnected agency perspective.
•  The various mediating and connective functions underlying the concept of pattern and how
they could be operationalized at the service of systemic literacy and collective intelligence.
My objective
•  Gather input for my PhD on the topic
•  Orient my research in a way that can benefit the Global Brain Project
•  Establish an agenda for future collaborative work
Patterns that Connect
Exploring the Concept of Pattern in the Face of Growing Complexity
Helene Finidori – ECCO Seminar - December 2016

Helene Finidori – PLoP October 2016 -
We live in an increasingly complex world…

Detail
Complexity
is
growing

Helene Finidori - September 2015 -

Increasing
numbers
of
variables
and
moving
parts
of
diﬀerent
kinds.

In
any
given
domain,
knowledge
grows
at
a
pace
at
which
it
can’t
be

curated,

integrated

fast
enough


Dynamic
Complexity
is
growing
and
accelera5ng


Increasing
numbers
of

interac=ons
among
greater
varie=es
of
systemic
processes
and

dynamics
aggrega=ng
at
various
levels
and
scales
that
can’t
be
fully
grasped.

Where
are
the
leverage
points?


Diﬀerent
types
of
systems
in
interac5on

Yaneer
Bar-‐Yam
(1997)
hHp://www.necsi.edu/projects/yaneer/EOLSSComplexityRising.pdf

Simple or complex?

Different types of systems with different types of individual and collective behaviors interact

Determinis5c
System
(mindless)

No-‐choice
of
parts/
no-‐choice
of
the
whole

Ecological
System
(hybrid)

Choice
of
parts
/
no
choice
of
the
whole

Social
System
(mul5-‐minded)

Choice
of
the
part
/
choice
of
the
whole

Animate
System
(uni-‐minded)

No-‐choice
of
parts
/
choice
of
the
whole

How
agency
comes
in
the
picture

Ackoﬀ
&
Gharajedaghi
(1966/2003)
hHp://www.acasa.upenn.edu/System_MismatchesA.pdf

There
is
a
problem
when
a
system
of
a
certain

type
is
managed
with
a
model
of
another
type

Systems interact with different degrees of agency of their parts or as a whole

How
do
code
and
AI
enter
the
picture?


Construc5on:
components
are
the
result
of
applied

work
aimed
at
producing
a
given
direct
effect

(determinis=c,
mechanical
system)

A
variety
of
genera5ve
processes
combined

source: Bonnitta Roy
Development:
the
system
is
transformed
through

the
realiza=on
of
its
poten=als.
Work
is
applied

towards
genera=ng
capacity
/
capability.

Autopoiésis:
the
system
(re)generates
itself
in

interac=on
with
its
environment,
maintaining
its

proper=es
and
con=nuously
regenera=ng
its
own

organiza=on
(ecological,
living
system).

Emergence:
(unexpected)
proper=es
(synergies)

result
from
the
interac=on
between
parts
which
do

not
prefigure
these
proper=es
when

taken

individually
-‐
ex:
the
wetness
of
H2O
that
can
be

prefigured
neither
in
H
nor
in
O…

Evolu5on:
the
system
transforms
itself
through

adapta=ons
and
evolu=ons
at
different
levels
and

scales
of
diversified
processes
which
interact
with

one
another
(complex
adap=ve
systems,
social

systems)

The
“system”
or
the
medium
take
control,
influence
et
even
drives
the
actors...

Diversity
and
choice,
and
therefore
the
capacity
to
act
are
reduced
or
biased.

or

or

Helene
Finidori
–
PLoP
October
2016
-‐

Different
types
of
aggregated
effects

When
visible
>
AHrac=on
(pull),
accelerated/amplified
by
the
instant
diffusion

–and
manipula=on
(push)?-‐
of
informa=on

Invisible
to
start
with,
reveal
themselves
with
=me
>
Tipping
points

PaHerns
of
behavior
>
Informa=on
in
the
environment
/
Tracks
in
the
“medium”

▪  Non-‐linear,
mul=ple
intricate
factors
/
causes
of
different
nature:
physical,

biological,
psycho-‐cogni=ve
(individual
level)

and
cultural-‐cogni=ve
(social

system
level)

▪  Effects
manifest
at
different
levels
and
scales

▪  At
mul=ple
rhythms
/
paces,

▪  Structures
and
behaviors
evolve
over
=me,
there
is
no
stable
state

“Wicked problems” emerge within complex systems

Consequences for problem solving
→  Information, the signals to act upon, are scattered and evolve over time
→  No ‘higher order’ from which to look, integrate and plan coherent responses
→  No history or best practice to rely upon, to project for higher orders of emergence
→  Language and perspectives differ: no shared articulations, priorities or pathways
→  No right or wrong: tradeoffs may be involved
Complexity

high
interdependence
of

mul5dimensional
factors


Responses

→  Social systems form around social objects (scientific, political, economic, spiritual etc…).
→  As they seek efficiency in resource allocation, their foci of action tend to narrow and domains of
specialty tend to increase in number, competing for resources.
→  At the same time, knowledge, language and culture become increasingly specialized and
differentiated. Agency is distributed and covers an increasingly wide range of variety.
→  As a result there is as a whole an increasing number of logics of action and signals of different types
to perceive, make sense of and integrate: more objects of focus, more contexts, more content, more
knowledge representations, more interpretations
→  This competition and differentiation is an impediment to collaboration and trans-disciplinary
approach to agency despite increasing efforts to federate diversity and complementarity.
Responses

of
mul5ple
nature
-‐

Agency
distributed

highly
fragmented

: local efficiency without global coherence

Object

of
Focus

&
Ac5on

(What)

Internal

Drivers
&

Reflec5vity

(Why)

External

Rela5ons
&

Expressions

(How)

Agency

Meaning

Helene
Finidori
-‐
September
2015
-‐

Agency:
the
capacity
to
‘effect’

Its
form:
the
result
of
(co)individua=on
processes

Differences
in
priori=za=on:

epistemological
rather
than
ontological

The triadic form of agency
Object
directed
Socially
directed
Development
directed

Helene
Finidori
-‐
September
2015
-‐

The
Fable
of
the
Elephant

Cartoon
by
Leunig

(Co)individua=on
processes
shape
representa=on/expression
and
interpreta=on.

To
cut
through,
‘objec5ve
truth’ & ‘translation’ are not enough
Not
‘just’
a
ques=on
of
language,
and
ﬁnding
the
‘beHer
truth’
or
vantage
point.

A
desire
to
collaborate
across
disciplines
does
not
imply
a
desire
to
unify
these
and
align

visions,
pathways
and
priori=es.
Forms
of
agency
/
ac=on
logics
are
not
interchangeable.

Diﬀerent
‘objec=ve
truths’
>
challenge
for
mutual
understanding
and
alignment
around
shared

visions
and
pathways.

Simple
local
rules,
emergence
of
complex
adap5ve
behavior

Coherence
and
convergence:
The
analogy
of
the
swarm

Separa5on:
steer
to
avoid
crowding

local
flockmates

Alignment:
steer
towards
the
average

heading
of
local
flockmates

Cohesion:
steer
to
move
toward
the

average
posi=on
of
local
flockmates

hHp://www.red3d.com/cwr/boids/

This may apply within social systems where internal drivers may align, and external
expressions are cohesive by ‘construction’ (because built around a shared social object)
Achieving alignment and cohesion across boundaries requires whole sets of new organs to
look into other objects, understand and mediate other drivers and expressions, understand
how the three components of agency work together.

Clusters
of
ac=on
cooperate
or
compete
in
the
ac=on
space
with
variable

degrees
of
cohesiveness
and
overlap
on
one
or
several
of
their
triadic
agency

components.
There
may
be
some
convergent
or
coherent
evolu=onary

trajectories
as
a
result.

Agency
and
connec5vity

Overlaps,
convergences
and

divergences

are
more
or
less

implicit,
or
are
dealt
with
as
dis=nct

domains
horizontally
or
ver=cally.

As
a
whole,
the
networks
of

phenomena
and
outcomes
that

cons=tute
dynamic
complexity
are

not
matched
by
an
equivalent

degree
of
networked
agency
which

would
enable
us
to
tap
in
the

diversity
and
realize
the
poten=al
it

oﬀers.


Agency
and
connec5vity

Expressions: Social
sciences, anthropology;
practical knowledge;
formal causes; systems
of communication
At best connectivity exists within domains of science, and between them ‘as a whole’:
Objects: Hard natural
sciences; working
knowledge; efficient
causes; systems of
causality
Drivers: Cognitive sciences,
behavioral sciences,
developmental psychology;
emancipatory knowledge,
final causes; systems of
inferences
The main question is: How can different embodiments of agency be interconnected at
various levels of granularity on all their dimensions to produce more coherence and
convergence of resources (material, cognitive, relational)? How can we humans make
better sense of the world around us, convergences and divergences and potentials for
coherence towards sustainable trajectories.

▪  perceive
and
interpret
weak
signals,
tracks

within
the
systems/domains
we
directly

inﬂuence
or
control,
and
steer
their
trajectories

through
complex
adap=ve
modeling

New
organs
for
systemic
literacy
and
connec5vity

Making
sense
of
systems
and
their
evolu5on
individual
and
collec5ve,
in
space

and
5me.

?
?
?

▪  perceive
and
interpret
weak
signals,
tracks
and

trajectories
beyond
our
own,
explore
overlaps

and
gaps
at
boundaries,
to
collaborate,

compete,
or
merely
‘posi=on’
oneself
in
the

bigger
picture.

▪  mediate
percep=ons
and
interpreta=ons,
and

interconnect
knowledge
representa=ons
across

boundaries
to
collec=vely
model
or
design
goal

seeking
trajectories,
and
navigate
a
broader

picture
of
reality.

PaHerns
are
everywhere,
but
not
explicitely
acknowledged
as
such.

Making
the
func=on
of
paHern
explicit
can
help
see
its
poten=al
as
cue,

concept
and
ar=fact
to
develop
new
sensory
skills
for
understanding,

crea=vity
and
adapta=on
.

Let’s
examine
the
various
func=ons
/
proper=es
of
the
concept
of
paHern

as
unit
for
inference
processing,
media=on
and
connec=vity,
in
the
areas

of:

•  Semio=cs

•  Cyberne=cs

•  Cogni=on

•  Formaliza=on

•  Modeling

•  Design

•  Ac=on
research

Seen
from
the
perspec=ve
of
the
lifecycle
of
ac=on
and
the
triadic
form
of

agency

The
unfulﬁlled
poten5al
of
the
paVern
as
concept


The
Piercean
triadic
semio=c
sign
is
at
the
same
=me:

▪  an
object
or
elementary
system
under
focus
(a
phenomenological

ontological
‘form’,
sta=c
or
dynamic,
in
its
abstractness)

▪  the
sign-‐vehicle
that
represents,
signiﬁes
or
‘encodes’
this
object

in
rela=on
to
its
context
(a
physical
or
explicit
formal

representa=on
such
as
a
symbol
or
ar=fact,
a
design),

▪  the
interpretant
or
understanding,
inference
and
interpreta=on
of

form,
or
‘decoding’
of
the
connec=on
between
the
object
and
its

representa=on
(the
form
it
takes
in
the
mind).

Semio5c
Func5on
/
PaVern
as
semio5c
sign

Helene
Finidori
–
PLoP
October
2016
-‐

Source: Charles Pierce

Semio5c
Func5on
/
PaVern
as
semio5c
sign

Helene
Finidori
–
PLoP
October
2016
-‐

Object

Phenomenological

Ontological

Form

Interpretant

Inference,

Interpreta=on

Understanding

Sign-‐Vehicle

Expression,

Representa=on,

Track

PaVern

Meaning

This
maps
the
triadic
form
of
agency.

PaHerns
can
be
found
in
each
of
the
sign
‘categories’.

The
concept
of
paHern
does
not
currently
encompass
all
of
them

Object

of
Focus

&
Ac5on

(What)

Internal

Drivers
&

Reﬂec5vity

(Why)

External

Rela5ons
&

Expressions

(How)

Agency

Meaning


The
same
phenomenological
object
can

have
mul=ple
inferences
/
mental

models.

Similar
mental
models
of
an
object
can

have
mul=ple
representa=ons

The
same
representa=on
can
have

mul=ple
interpreta=ons.

These
could
be
connected
in
mul=ple

ways,
forming
networks
of
meaning,

and
media=ng
the
diﬀerent
forms
of

agency.

Enabling
networks
of
meaning

Helene
Finidori
–
PLoP
October
2016
-‐

Source Soren Brier
Semio5c
Func5on
/
PaVern
as
semio5c
sign


[First
Order]

The
phenomenological
object
–
seen
from
speciﬁc
frames
of
reference

and
study

➔
Pa4erns
can
help
make
domain
related
knowledge
explicit

Cyberne5c
Func5on
/
PaVern
as
Cyberne5c
Cue

Helene
Finidori
–
PLoP
October
2016
-‐

Unpacking
Complexity
through
Cyberne5c
orders


[Second
Order]

The
lenses
of
observa=on,
diﬀerent
ways
to
interpret
and
represent

➔
Pa4erns
can
help
mediate
and
navigate
meaning
among

frames/domains

[Third
Order]

The
dynamics
and
transforma=ons
resul=ng
from
observa=on
and
ac=on

over
=me,
power
rela=ons:
the
medium
taking
a
life
of
its
own

➔
Pa4erns
can
help
iden<fy
traces
and
change
in
structure
and
behavior

[Fourth
Order]

The
emergent
outcomes
of
the
previous
orders
in
interac=on,
and
the

changes
in
the
context

➔
Pa4erns
can
help
reveal
the
mul<ple
processes
of
systems
evolu<on

Yolles
&
Fink’s
Cyberne5c
Agency
Model

From:
Yolles,
M.
&
Fink,
G.
(2014).

Generic
agency
model,
cyberne=c
orders
and
new
paradigms.

Working
Paper
of
the
Organisa<onal
Coherence
and
Trajectory
(OCT)
Project.
July
2014

Helene
Finidori
–
PLoP
October
2016
-‐

Cyberne5c
Func5on
/
PaVern
as
Cyberne5c
Cue


Hofstadter
&
Sanders

▪  Human
ability
to
make
analogies
lies
at
the
root
of
all

conceptualiza=on
and
capacity
to
selec=vely
evoke
concepts,
from

the
most
basic
in
childhood
language
development
to
the
most

abstract
leading
to
scien=ﬁc
discoveries

Dyson

▪  Brain
uses
maps
to
process
informa=on
and
navigates
from
one
map

to
the
other

Poincaré

▪  Analogical
reasoning:
ﬁnding
hidden
similari=es
and
revealing
deep

iden=ty
of
structure
among
what
appears
divergent
in
associa=ons

between
seemingly
disparate
concepts
or
ideas
brought
about
by

intui=on
(Paty,
1994)

Helene
Finidori
–
PLoP
October
2016
-‐

Analogical
func5oning
of
the
brain

Cogni5ve
Func5on/
PaVern
as
Unit
of
recogni5on
of
form
&
inference


Helene
Finidori
-‐
September
2015
-‐

Margolis’
P-‐Cogni5on
cycles

P -cognitive spirals: ‘Each spiral represents a cognitive cycle where a pattern prompted by cues in a
context, becomes itself part of the context, and cues another pattern. Conscious or not, this cycle is
essentially a-logical and can happen in multiple cognitive dimensions at once, such as playing the
piano while having a conversation. Only a small fraction of these prompted patterns could be expected
to come to conscious attention.’
Source: (Margolis 1987: 2)
Cogni5ve
Func5on/
PaVern
as
Unit
of
recogni5on
of
form
&
inference

Pattern
as cue
Pattern
as cue
Pattern
as cue
Pattern
in Mind
Pattern
in Mind
Pattern
in Mind

The
Pragma5c
Cycle

Helene
Finidori
-‐
September
2015
-‐

Making
inferences
&
Connec5ng
‘moments’
of
inference:

Image: Sowa
Cogni5ve
Func5on/
PaVern
as
Unit
of
recogni5on
of
form
&
inference

Pierce’s
Pragma5c
Cycle

Different types of
patterns are involved at
each ‘moment’ of the
perception to action
cycle, connected
through different types
of cognitive
metaprocesses

Note how orientation shapes observation, shapes decision, shapes action, and in turn is shaped by the feedback
and other phenomena coming into our sensing or observing window.
Also note how the entire “loop” (not just orientation) is an ongoing many-sided implicit cross-referencing process of
projection, empathy, correlation, and rejection.
From “The Essence of Winning and Losing,” John R. Boyd, January 1996.
Ini=ally
meant
to
act
and
change
direc=on
faster
than
the
enemy
in
fighter
jet
situa=ons,
is
now
used
at
different
paces

Helene
Finidori
–
PLoP
October
2016
-‐

The
promp5ng
of
paVerns:
Boyd’s
OODA
Loop

Cogni5ve
Func5on
/
PaVern
as
Mental
filter
&
interpreta5on
framework
Cogni5ve
Func5on/
PaVern
as
Unit
of
recogni5on
of
form
&
inference


The
Ladder
of
Inference
-‐
Argyris,
Senge

Helene
Finidori
–
PLoP
October
2016
-‐

Cogni5ve
Func5on
/
PaVern
as
Mental
ﬁlter
&
inference
framework

Interpreta=on
is
inference
from
a
point
of
view

The formation of the self sealing logic
It’s not only about values, beliefs, meaning,
assumptions…

Cogni5ve
Func5on
/
PaVern
as
Mental
ﬁlter
&
inference
framework

Helene
Finidori
–
PLoP
October
2016
-‐

Informa5on
processing
and
mental
func5ons
-‐
Jung

(i) INTROVERSION
Focus on the inner world of our
thoughts, feelings and reflections
EXTRAVERSION (e)
Focus on the outer world of
things, people and events
(N) INTUITION
Bigger picture approach,
hunches, visionary ability

SENSING (S)
Step by step detailed
approach, concrete data
(T) THINKING
Stepping back from situation,
judging on facts

(P) PERCEIVING
Seeking experience,
preference for exploration

FEELING (F)
Immersion in situation
empathetic view
JUDGING (J)
Seeking order, preference
for organization & decision
Orientation of
energy & attention
Perceiving
Functions
Judging/Decision
Functions
Attitude to the
external world
Preferences of how inferences are made and processed
… It’s also about how we infer and process data / patterns

The
cogni=ve
process
through
which
paHerns
change
their
form:

Cogni5ve
Func5on
/
PaVern
as
Mental
filter
&
inference
framework

Helene
Finidori
–
PLoP
October
2016
-‐

Three
types
of
reten5ons
-‐
S5egler
a_er
Husserl

Individua=on
and
co-‐individua=on
processes
shape
the
3
facets
of
the
paHern

as
semio=c
sign.
From
inferred
cue
in
the
environment,
to
configura=on
of

form
in
the
mind,
to
individual
and
shared
representa=ons.


▪  Primary
reten5ons:
the
salient
cues
in
the
environment
that

are
perceived
by
the
mind,
consciously
or
not

▪  Secondary
reten5ons:

the
filters
/
funnel
through
which

primary
reten=ons
are
selected,
made
of
the
aggregate
of
past

primary
reten=ons
(memory,
habits
of
mind)

▪  Ter5ary
reten5ons:
the
tracks
we
leave
in
the
environment
for

others
to
process
(cultural
ar=facts).

Helene
Finidori
-‐
September
2015
-‐

Human
thought
as
model
building
ac5vity

(Lake
&
al
-‐
https://arxiv.org/pdf/1604.00289v3.pdf)

The
human
mind
can
:

■  Recognize,
decompose
and
recompose
concepts

■  Make
inferences
using
intui=ve
physics
and
intui=ve
psychology

■  Construct
causal
models
of
the
world

■  Learn
in
the
process

PaHerns
learnt
through
experience
are
the
basis
of
understanding
and
learning

which
supports
model
building.

§  Experience
is
gathered
in
the
form
of
previously
encountered
paHerns,
used
to

match
sensory
input
from
a
context,
at
various
levels.

§  The
self-‐organiza=on
of
matching
paHerns
is
the
understanding
of
a
situa=on

(situa=on
seman=cs
Monica
Anderson)

§  Context
determines
what
paHerns
are
to
be
used,
diﬀerent
from
reduc=onism.

§  Learning
is
crea=ng
more
paHerns
to
match
new
previously
unseen
sensory

input,
or
make
sense
of
higher
order
complexity.

PaHern
recogni=on
capability
is
an
evolu=onary
driving
force
that
helps
survival

(Monica
Andersen
-‐
hHp://videos.syn=ence.com/ai-‐meetups/modelsvspaHerns.html)

Cogni5ve
Func5on
/
PaVern
as
Mental
ﬁlter
&
inference
framework


▪  Building
conﬁgura=ons
that
bring

harmony
between
two
intangibles:
forms

not
yet
conceived
and
contexts
that

cannot
be
fully
described

(Alexander).

▪  Near
decomposability
of
complex

systems
–
graspable
by
the
mind-‐
&

gramma=za=on
enabling
to
segment
into

smaller
paHerns
and
probe
each

associa=on
(Simon,
Quillien,
Jacobs)

▪  Purpose-‐seeking:
constantly
adap=ng

intermediary
goals
to
an
ideal
outcome

(Jones).
Agile
technology
(Cunningham
&

Mehaﬀy)

▪  Enabling
context
adap=ve
modeling,
and

networks
of
adap=ve
solu=ons.

Modeling
Func5on
/
PaVern
as
Unit
of
systemic
Fitness

Helene
Finidori
–
PLoP
October
2016
-‐

Modeling the complexity of the world similarly as human thought processes?
▪  PaHern
Language
inspired
by
the

process
of
design
of
vernacular

cultures
-‐their
‘=meless
way
of

building’,
grounded
in
tacit/implicit

knowledge
(Alexander).


•  A
hacker
approach
to
render
configura=ons,
processes,
flows
–
sensory
as

well
as
cogni=ve
approach

▪  Connect
through
systemic
isomorphies
(Bertalanffy)
and
iden=ty
of

structure
/
analogical
reasoning
(Poincaré)

▪  Enable
experimental
design
and
post-‐hoc
data
analysis
for
the

reconstruc=on
of
phenomena
and
mul=dimensional
dynamics
–
reverse

engineering.
Including
of
algorithms.

▪  Enable
intent
cas=ng,
and
a
pharmacological
approach

▪  Providing
prac=cal
tools
for
cri=cal/apprecia=ve
hermeneu=cal
approach/
probing
quality,
systemic
trajectories
and
sustainability
(pharmacological

approach).

▪  Connect
via
the
modeling
rela=on
(Rosen)
–
encoding
/
decoding
the

rela=ons
among
the
three
facets
of
the
semio=c
triad.

Modeling
Func5on
/
PaVern
as
Connec5ve
Building
Block

Helene
Finidori
–
PLoP
October
2016
-‐


Helene
Finidori
-‐
September
2015
-‐

Rosen’s
Modeling
Rela5on

A natural system N is modeled by a
formal system F. Each system has its
own internal entailment structures
(arrows 1 and 3), and the two
systems are connected by the
encoding and decoding processes
(arrows 2 and 4).
« The encoding and decoding mappings are independent of the formal and natural systems,
respectively. In other words, there is no way to arrive at them from within the formal system or natural
system.»
Andreas Schierwagen. 2011. Reverse Engineering for Biologically Inspired Cognitive Architectures: A Critical Analysis
Cogni5ve
Func5on
/
PaVern
as
Mental
ﬁlter
&
inference
framework

« The act of modeling is really the act of relating two systems in a subjective way. An ‘art’ says Rosen. »

▪  Visual,
sound,
ar=fact

▪  Designs:
carvings
–
=les
–
carpets

▪  Religious
shamanic
symbols
and
rituals

▪  Templates
or
blueprints:
clothes,
machinery

▪  Repeatable
processes:
recipe,
produc=on
process

▪  Recurrent
conﬁgura=ons:
maths,
physics,
biology
–
DNA

▪  Archetypes
(Jung),
Systems
Archetypes

Formal
Func5on
/
PaVern
as
Unit
of
representa5on
of
form

Helene
Finidori
–
PLoP
October
2016
-‐

A
“Standard”,
recognizable,
reproducible,
shareable

>
Cues,
captured
becoming
models?
Units
of
exchange?
Memes?


“Each
pa4ern
describes
a
problem
which
occurs
over
and
over
again
in
our

environment,
and
then
describes
the
core
of
the
solu<on
to
that
problem,
in

such
a
way
that
you
can
use
this
solu<on
a
million
<mes
over,
without
ever

doing
it
the
same
way
twice.”
A Pattern Language, Alexander (1977, p X)

Distributed
nature
of
the
paVern
as
rich
versa5le
knowledge
objects.

Structured
objects,
connectable
into
PaVern
Languages…

▪  Has
an
internal
reproducible
structure
(Alexander)

▪  Could
become
a
standard,
with
interoperable
features
(wiki)

▪  Connectable
via
hyperlink
or
other
‘seman=c
web’
technologies

to
cross
over
diﬀerent
dimensions
of
complexity

à
What
forms
of
standard interoperable vehicles and what protocols to
connect them? To embedded the pattern in all its facets into other
digital or non digital tools?

Formal
Func5on
/
PaVern
as
connectable
Unit
of
knowledge

Helene
Finidori
–
PLoP
October
2016
-‐


Formal
Func5on
/
PaVern
as
connectable
Unit
of
knowledge

Helene
Finidori
–
PLoP
October
2016
-‐

The Alexandrian Pattern structure

In
par5cipatory
ac5on
research
and
hermeneu5cal
inquiry

▪  Using
a
shared
representa=on
format
to
explore,
compare
and

confront
percep=ons,
representa=ons
and
interpreta=ons

around
shared
objects
of
study.
Using
simple
ar=facts
to

‘construct’
together.

▪  Keep
track
of
controversies
and
their
evolu=ons
(wikipedia)

▪  Explore
boundaries,
diﬀerences,
similari=es,
what
lies
in
between

à
Learning
paHern
thinking
and
to
‘speak
the
language
of
paHerns’

Methodological
Func5on
/
PaVern
as
Boundary
object

Helene
Finidori
–
PLoP
October
2016
-‐


The
Johari
Window

Joint
discovery
of
blind
spots
and
the
unknown

Helene
Finidori
–
PLoP
October
2016
-‐

Methodological
Func5on
/
PaVern
as
Boundary
object


▪  Learning
to
ﬁnd
‘paHerns
that
connect’
across
dimensions
and

boundaries

▪  To
connect
and
navigate
the
spa=al
and
temporal
dimensions
of

complexity
and
change

▪  To
navigate
the
‘adjacent
possible’
for
joint
discovery
and
co-‐
evolu=on

Methodological
Func5on
/
PaVern
as
Media5ng
&
connec5ve
object

Helene
Finidori
–
PLoP
October
2016
-‐

At the end of the day, it is about…

How
to
expand
and
opera=onalize
the
concept
of
paHern

that
connect
to
encompass
the
whole
percep=on-‐to-‐ac=on

cycle
and
unpack
the
diﬀerent
dimensions
of
complexity?

The
broader
research
ques5on


Opera5onalizing
PaVerns
that
Connect

Some
Orienta5ons


Helene
Finidori
–
PLoP
October
2016
-‐

Opera5onalizing
PaVerns
that
Connect
–
some
orienta5ons

Visual tools / artifacts - to play, construct, deconstruct, probe
A Systemic Connective Language - the units to be combined
Collaborative sketching and annotation
Semantic capability - the various ways to associate patterns
Formats and protocols for interoperability of patterns
AI deep learning systems to infer / suggest / simulate / play
Visual tools to navigate data and knowledge (anoptical, holoptical)

Visual
Construc5on
Tools:
Card
Games
-‐
Groupworks

Helene
Finidori
–
PLoP
October
2016
-‐

Opera5onalizing
the
PaVerns
that
Connect
–
some
orienta5ons

A Pattern Language for bringing life to meetings and gatherings
http://groupworksdeck.org/

Visual
Construc5on
Tools:
Tangible
tokens
-‐
S.
Huron
Inria

Helene
Finidori
–
PLoP
October
2016
-‐

Opera5onalizing
the
PaVerns
that
Connect
–
some
orienta5ons

Investigating how people construct visual mappings
•  Create
•  Update
•  Annotate
http://constructive.gforge.inria.fr/#!index.md

Visual
Construc5on
Tools:
Lego
Serious
Play
©

Helene
Finidori
–
PLoP
October
2016
-‐

Opera5onalizing
the
PaVerns
that
Connect
–
some
orienta5ons

Lego 3D models used a shared language for group discussion, knowledge sharing,
problem solving and decision making
•  Based on creative
imaginations & metaphor
•  Learning to ‘think
with one’s hands’
Source: Avea partners

Seeing
the
big
picture
emerge:
The
Poie5c
Generator
-‐
O.
Auber

Helene
Finidori
–
PLoP
October
2016
-‐

Opera5onalizing
the
PaVerns
that
Connect
–
some
orienta5ons

Each player draws on a small part
of a global mosaic that each can
see evolve as they draw
By OlivierAuber - Own work, FAL,
http://commons.wikimedia.org/w/index.php?
curid=19849563

Seeing
the
picture
emerge:
Real
5me
coding
feedback
–B.
Victor

Helene
Finidori
–
PLoP
October
2016
-‐

Opera5onalizing
the
PaVerns
that
Connect
–
some
orienta5ons

The image moves as
the code variables are
changed
https://www.youtube.com/watch?v=I8F7tzc1Tco

Helene
Finidori
–
PLoP
October
2016
-‐

Bertalanffy:
Approaching
the
Unity
of
Science

There
are
correspondences
in
the
principles
that
govern
the
behaviour
of
en<<es

that
are,
intrinsically,
widely
different.
Isomorphisms:
structural
similari<es
exis<ng

in
different
fields.
(p.33)

More
than
mere
analogy.
It
is
a
consequence
of
the
fact
that,
in
certain
respects,

corresponding
abstrac<ons
and
conceptual
models
can
be
applied
to
different

phenomena.
(p.36)

…
general
system
laws
[exist]
which
apply
to
any
system
of
a
certain
type,

irrespec<ve
of
the
par<cular
proper<es
of
the
system
and
of
the
elements
involved.

(p.37)

…
major
aims
of
General
System
Theory…
developing
unifying
principles
running

'ver<cally'
through
the
universe
of
the
individual
sciences,
this
theory
brings
us

nearer
to
the
goal
of
the
unity
of
science.
(p.38)

Bertalanffy,
L.,
1968

“ “
”
Unifying
Principles,
Isomorphy
&
Systemic
Connec5ve
Language

Opera5onalizing
the
PaVerns
that
Connect
–
some
orienta5ons


Scien=sts
have
been
on
a
quest
for
‘universal
paHerns’
for

while.

Can
this
be
done?

Are
other
other
ways
to
‘tend’
towards
that
without
deﬁning
it?

For
example
through:

Clusters
of
isomorphic
/
homomorphic
‘semio=cally’
interconnected

forms?
With
discussions
on
dis=nc=ons
and
similari=es?

Isomorphic
/
homomorphic
ideograms
used
to
tell
systemic
stories,

diagram
paHerns,
and
‘tag’
contexts
or
situa=ons?

Helene
Finidori
–
PLoP
October
2016
-‐

From
universal
paVerns
to
clusters
of
iso/homomorphic
paVerns?

Unifying
Principles,
Isomorphy
&
Systemic
Connec5ve
Language

Opera5onalizing
the
PaVerns
that
Connect
–
some
orienta5ons


Level of scale
Strong Center
Boundaries
Alternating
repetition
Positive
Space
(complementarity)
Good Shape
(adaptation)
Local
Symmetry

Alexander’s
15
Fundamental
proper5es

AlexanderBy TKWA Iba Leitner
Deep
Interlock &
Ambiguity
Contrast
(difference)
Gradients
Roughness
(individuality)
Echoes
(similarities)
The Void
(open space)
Simplicity &
Inner Calm
Not
Separatedness
(connectedness)

1. BOOTSTRAP
4. ATTRACTION
10.
ACCOMPANY
7. BUILDING UP
19. AIMING
13. SELECTION
22.
DIFFERENTIATING
16. ROUGHNESS
17. FLEXIBILITY
23. OVERLAPPING
14.
SIMPLIFICATION
20.
CONNECTING
12. EMPATHY
9. REFLECTING
3. SPREADING
6. TOGETHERNESS
2. SOURCE
5. INVOLVING
11. ENHANCING
8. GROWTH
24.
CONTINUATION
15. CONSISTENCY
21. POSITIONING
18. ABUNDANCE

Iba
Lab’s
24
Fundamental
Behavioral
Proper5es


Systemic
Interpreta5on

Grammar

(Elementary
Components)

Dynamics

(Movement)

◆ 

Sta5cs

(Space
-‐
Structure)

◆ 

Heuris5cs

(Inﬂexions
–
Limits
–

Angles
–
Switches)

Systemic
PaHerns

Generic

Domain
Related

Contexts

PaHern
Languages

Domain
Related

Genera=ve
processes
-‐
Nature
of
movement
–
Direc=on
–
Rhythm

–
Eﬀect
of
=me
&
scale
etc…

Func=on
-‐
Rela=onships
–
Proximity
–
Mutuality
–
Boundary
-‐
Posi=on
–
feedback
etc…

Logics
of
Change
-‐
Cogni=ve
Processes
(Jung)
–
Learning
Styles
–
Process
Narra=ves
(Roy)

–
Inference
(What/what/how,
Aristotelian
ethics)
–
Pharmakon/window
of
viability

(S=egler,
Lietaer)
–
One
level
up/down
–
etc…
-‐
Switches
(DNA)

Systemic
operators
-‐
Variables
–
Principles
for
combina=on
–
etc…

A
Systemic
Interpreta5on
Language

Bridging
the
Systemic
&
the
Seman5c
Spheres


Patterns that Connect: Exploring the concept of pattern in the face of growing complexity

Cards
used
to
tell
‘systemic
stories’
at
Purplsoc
2015

Helene
Finidori
–
PLoP
October
2016
-‐


Cards
used
to
tell
‘systemic
stories’
at
Plop
2016

Helene
Finidori
–
PLoP
October
2016
-‐

Find pictures

PaVern
Dynamics
consul5ng
prac5ce

1.  A series of stages or
layers
2.  Series showing changes
in magnitude
3.  Circle showing
separation in divisions
4.  Pyramid showing parts
to wholes, subunits to
units
5.  Outline showing
subheadings at several
levels
6.  Circles showing
clustering and inclusion
7.  Series showing
subsumption
⬜  Icons represent the essence of an idea in abstract; simplify (all-at-once)
ALL SHOW COMMON ID FEATURES OF LEVELS,GAPS, CLUSTERING, HETEROGENEOUS SEPARATION, ETC.

Systems
Sciences:
Len
Truncale
-‐
Icons
for
Hierarchy

✓  From “cyclus” (Gr.) = circle,
wheel. Some key features are:
✓  Stages of a cycle
•  Steps in a process
•  A cycle may seem like a smooth
transition; not; very specific
intermediates
✓  Obligate sequence
•  Transformation of one stage into
next
•  Next stage requires previous stage
✓  Return to beginning
•  Oscillations
✓  SO NEED TO KNOW THE SEQUENCE
& STAGE NAMES
ICONS for
Identifying
Features
of Cycles and
Cycling

Systems
Sciences:
Len
Truncale
–
Features
of
Cycles
I

•  Importance of Initiating
Conditions
•  Steps in a process
•  A cycle may seem like a
smooth transition; not; very
specific intermediates
•  Control of Stages
•  When one starts; when one
ends
•  Source of embedding cycles in
net context for a function
•  Entrainment (all cycle)
•  Periodicity
•  Spin /or/ Rotation /or/ angular
momentum
ICONS for
Cycles and
Cycling

Systems
Sciences:
Len
Truncale
–
Features
of
Cycles
II

Adapted
from
the
12
principles
of
Mo5on
Design-‐
Olie
Johnson
&
Frank
Thomas

Ques=ons
on
the
theory
and
objec=ve?

Points
of
intersec=on
with
your
own
experience
or
objec=ve?

How
does
this
connect
to
the
GBI
approach?

Other
points
of
view
to
explore?
Research,
angles
or
people
to
discover

for
my
PhD?

Other
possibili=es
for
opera=onaliza=on?
How
can
soxware
and
ar=ﬁcial

intelligence
be
put
at
the
service
of
paHern
languages
and
collec=ve

intelligence?

Discussion.

Ques5on
for
discussion

Helene
Finidori
–
PLoP
October
2016
-‐

Back
to
the
big
picture


If you would like to join me in my PhD explorations:
@HeleneFinidori
Thank You!

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