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 Helene Finidori – ECCO Seminar - December 2016

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



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


Source: Charles Pierce




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


Source Soren Brier



[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


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


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)


Analogical func5oning of the brain

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



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)


Pattern as cue

Pattern as cue

Pattern as cue

Pattern in Mind

Pattern in Mind

Pattern in Mind


The Pragma5c Cycle


Making inferences & Connec5ng ‘moments’ of inference:

Image: Sowa


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


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


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…




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:



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).


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)



▪  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


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 – ECCO Seminar - December 2016


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


« 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


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


Formal Func5on / PaVern as connectable Unit of knowledge


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


The Johari Window

Joint discovery of blind spots and the unknown


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


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



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


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



Investigating how people construct visual mappings

•  Create

•  Update

•  Annotate


http://constructive.gforge.inria.fr/#!index.md

Visual Construc5on Tools: Lego Serious Play ©



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



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



The image moves as the code variables are changed

https://www.youtube.com/watch?v=I8F7tzc1Tco



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



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?


From universal paVerns to clusters of iso/homomorphic paVerns? Unifying Principles, Isomorphy & Systemic Connec5ve Language



Level of scale

Strong Center

Boundaries

Alternating repetition

Positive Space (complementarity)

Good Shape (adaptation)

Local Symmetry

Alexander’s 15 Fundamental proper5es

Alexander By 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


Cards used to tell ‘systemic stories’ at Purplsoc 2015


Cards used to tell ‘systemic stories’ at Plop 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


Back to the big picture


If you would like to join me in my PhD explorations:

@HeleneFinidori

Thank You!