TOWARDS AN ANTICIPATION LITERATE COMMUNITY

1. TOWARDS AN ANTICIPATION LITERATE COMMUNITY by Andrée C. EHRESMANN* and Mathias BEJEAN *Université de Picardie Jules Verne ehres@u-picardie.fr http://ehres.pagesperso-orange.fr http://vbm-ehr.pagesperso-orange.fr FUMEE V. EPFL Lausanne 2013

2. Anticipation as a collective proceptual capacity • Characterization of different kinds of futures • Optimization • Contingency • True innovation • Anticipation as a collective proceptual capacity • Collective: not produced by isolated individuals, but by a community of anticipators merging their multiple views and diverse expertises. • Proceptual: aimed at providing an active and constructive relation to the future within the present (cf. « effectuation theory »). • Capacity: implying robust but flexible (evolving) memory with a higher dynamic internal model, the "Archetypal Core". Methodology to study anticipation In the frame of an Anticipation LiterateCommunity, ALC, whoseorganization and dynamics are represented by a Memory Evolutive System (Ehresmann & Vanbremeersch 2007).

3. MEMORY EVOLUTIVE SYSTEMS Studying "becoming" frominside • Relational ontology (based on a 'dynamic' Category Theory) • Components are defined by their links (and their composition).. • Any component of the system, be it human or not, is considered as a process of individuation with its own dynamic (and not as a substance).. • The system develops multiple processes of individuation, themselves forming (by interplay) new relations generating processes of individuation of higher complexity levels. • These higher level processes of individuation (can) form higher level components, the composition of which can change over time while preserving the same operative role within the system. • Internal point of view • Becoming is not entirely deductible from its past and actual states. • Novelty can occur within the process of becoming. It requires, and arises from, the “Multiplicity Principle” (Emergence Theorem, EV 1996). • Intentional action is described from inside the system as the formation and implementation of “procepts” by internal "co-regulators".

4. COMPONENTS OF ALC The MES for anticipation, ALC, has different kinds of components. The links between them model their interactions, e.g. action or transfer of informa-tion. A link has a propagation delay and a strength, and can be active or passive at a given time. Both components and links may vary over time. Anticipators Individuals and a hierarchy of groups of interacting individuals interested in learning and developing anticipation skills, from local KnowLabs up to possibly large institutions, each operating with its own "thick present". We name them anticipators Memory components Conceptual knowledge related to different disciplines, historical and contextual documents, proper practices and ethical rules; but also unconscious or implicit knowledge such as ad hoc methods, cultural values and symbolic systems, affects and emotions; all these components would form the flexible memory of ALC. 'Material' components Artifacts, computers,… acting as 'microscopes' or 'macroscopes' to scrutinize the environment and detect seeds of change.

5. THE ROLE OF THE DIFFERENT "TIMES" In ALC, we have to deal with different notions of time: = The "objective" continuous clock-time Time which allows coordinating the whole system. In particular it is used to measure the propagation delays of the links between components. AN3 AN2 AN1 Time = The "thick relational" times of the anticipators ANi, each determined by a discrete timescale (included in Time), a "thick present" extending between 2 instants of this timescale. They may slightly change over time.

6. level n+1 transition CHARACTERISTICS OF A MES C C level n C level n-1 level 0 Time t' t The system is modeled by a family (Ht)tєT of categories (= graphs with a composition of paths) indexed by Time, called its successive configurations. The change from t to t' is represented by a (partial) transition functor from Ht to Ht' . The transitions respect a transitivity condition so that a component of the system is a maximal family of objects connected by transitions; and idem for a link between components. The components are distributed into levels, so that each component C of level n+1 has an internal organization into at least one pattern P of linked components of lower levels which it 'binds', so that C and P have the same operational role. Formally C = colimit P.

7. INDIVIDUATION OF A COMPONENT. MP Ct" Ct' level n+1 Ct0 Ct level ≤ n Q Q P Pt P0 switch Time t" t' t0 t A component C of level n+1 'appears' at a time t0 as the colimit of a pattern P0 contained in the levels ≤ n. This internal organization varies progressively. C is n-multifacetedif it binds ( = is colimit) of structurally different and not well connected patterns P and Q of levels ≤ n between which it can switch. The Multiplicity PrincipleMPasserts the existence of such multifaceted components which, depending on the context, can operate through P or Q. MP is a kind of'flexible redundancy'. In particular it allows developing a robust though flexible adaptive memory Mem in which a component can be recalled through its different decompositions, providing plasticity over time.

8. COMPLEXITY ORDER OF A COMPONENT C level n+1 levels ≤ n Pi P Pi P level 0 A component C binds at least one pattern P of strictly lower levels; each Pi also binds a pattern of lower levels, and so on. Whence a ramification of Cdown to the level 0. A ramification of C reflects its stepwise construction. Complexity order of C = smallest length of a ramification down to level 0. COMPLEXITY THEOREM (EV 1996). MP is a necessary condition for the existence of components of complexity order strictly more than 1. Without MP ---> Pure reductionnism.

9. EMERGENCE OF COMPLEX LINKS complex link N M' M simple link simple link cluster cluster Q' P' P Q Pi A (P,P')-simple linkfrom M to M' binds a cluster of links between decompositions P and P' of M and M'. MP allows for the existence of complex links which are composites of simple links binding non-adjacent clusters. A complex link from N to M' represents emergent properties at the level of N and M' which are not observable at the lower levels though dependent on the global structure of these levels. They lead to what Popper calls "change in the conditions of change".

10. STRUCTURAL CHANGES ALLOWING FOR EMERGENCE transition level n+1 level n C level n-1 level 0 Time t' t In a MES the transition from t to t' can reflect structural changes of the following types: ’adding’ external elements, ’suppressing’ or ’decomposing’ some components, adding a colimit to some given patterns. Modeled by the complexification process: given a procedurePr on Ht with objectives of the above kinds, the complexification of Ht for Pr is the category Ht'in which these objectives are optimally satisfied. It is explicitely constructed. EMERGENCE THEOREM.MP is preserved by complexification and it leads to the emergence of components of increasing complexity orders through iterated complexifications.

11. MULTI-SCALE SELF-ORGANIZATION Proc The dynamic of a MES, e.g. of ALC, is internally modulated by: = A net of co-regulators (CRs). A co-regulator is an evolutive subsystem with its own function, complexity, operating at its own temporality. In ALC they correspond to the different (groups of) anticipators which organize ALC in view of developing a discipline of anticipation. They operate with the help of: = The flexible long-term memoryMem, and in particular its sub-systems: (i) the procedural memory Proc, whose components, called procepts, command patterns of effectors of procedures of various kinds; (ii) the archetypal core AC which acts as an internal dynamic model.

12. THE ARCHETYPAL CORE AC In ALC, through exchanges between anticipators, MP allows the develop-ment, over time, of higher order memory components integrating significant memories of various modalities, with many ramifications and possibility of switches. They constitute the Archetpal Core AC,a central subsystem of Mem in which they are connected by strong and fast links; these links form archetypal loops self-maintaining their activation for a long time. AC acts as a dynamic flexible internal model which plays an important role in anticipation. It is a crucial yet overlooked notion resulting from MES theory.

13. HOW DOES AN ANTICIPATOR OPERATES? Formation of Archetyipal objects Scenarios Global Landscape Let AN be an anticipator whose members can be simple indviduals or anticipators of lower levels. Processing an anticipation assignment will consist in iteration of the following overlapping phases: (i) Formation of an archetypal pattern AOof concepts and procepts in relation with the assignement,representing explicit or tacit knowledge shared by its members, to improve the communication between them. Prospection Retrospection (iii) Prospection in GL by formation of various scenarios simulating possible futures, which are tested "in the mind" (by "proceptivation" in GL) with infinitesimal cost. Prospection covers forecasting, foresighting, visioning, and may later lead to transformation by realization of a scenario. (ii) Retrospection leading to the construction and analysis of global landscapes GL recollecting past and present information, for framing and scanning, make sense and sense making, detecting and understanding.

14. FORMATION OF AN ARCHETYPAL PATTERN AC AN AO f N' N Ai P Q The first task of an anticipator AN will be to develop the pattern AO of specific archetypal objects Ai, such as concepts and procepts related to its assignment, shared by its members to facilitate their communication. Recall of Ai diffuses in AO through archetypal loops, and propagates to lower levels through ramifications of Ai and switches between them. Initially two members N and N' of AN only receive information of Ai related to different specific ramifications. Through interactions f between them they will exchange their (explicit or even tacit) perspectives; it allows for the formation of a common enriched perspective of Ai encompassing both.

15. AF FSS FE FS BF F=forest, E=Engineer, B=boundary, S=scientist, SS = space scientist The formation of the archetypal pattern AO helps sharing both explicit and some tacit knowledge (e.g. tacit procedures, skills, but also emotions) as a common resource, possibly even making the tacit explicit (as in the above "spiral of knowledge creation"). "Ba" could be a by-product. AO (which can be simulated by maps of enriched concepts, Novak) provides formal conditions for developing a productive collective intelligence. ROLE OF THE ARCHETYPAL PATTERN An archetypal object A becomes more than a boundary object. Indeed a boundary object allows some cooperation, but without a common meaning for different members of AN (formally represented by a projective limit instead of a colimit). On the opposite, A leads to a rich consensus in AN, thanks to the integration by all of the information of different kinds and levels obtained by unfolding of ramifications and switches.

16. Fromboundaryobjects to archetypalobjectsExample • Field : • Spatial Earth Observation • Issue: • a scientific community specialized in earth monitoring was willing to scrutinize « forests » thanks to « lidar technologies » • They asked CNES, French Spatial Agency, to design a spatial mission dedicated to this project and recruited other scientists to form the mission team (in situ forests specialists) • the problem was that neither the CNES engineers, nor the space or forest scientists did have the same definition of “forest” • The mission was first abandoned, but then a CNES senior engineer realized that if everybody was talking about “forest”, no one had the same definition • She organized several meetings to build a common understanding of “forest” from a space point of view, which was a new object integrating information from all the participants • They managed to design a space mission sustaining the research goals

17. MAKING SENSE BY RETROSPECTION AC AN AO Pr N Ai u At a time t, the members N of AN collect information through active links u from ramifications of AO; these links are objects of a category GL, the global landscape of AN at t. As archetypal loops of AO are self-maintained, GL persists during the thick present of AN. A complete analysis of it, through exchanges between members, allows making sense of the present situation, its trends and future potential, in relation with the past (by unfolding ramifications), then searching for possible archetypal procepts Pr, related to the practices of AN, to anticipate different kinds of future. P Q These operations necessitate the cooperation of the different members of AN. If they have different 'thick presents' and divergent interests, their viewpoints must be harmonized by 'interplay' between them.

18. WHAT KINDS OF ANTICIPATION? Following the retrospection process during which GL has been constructed and analyzed, the anticipator will develop a prospection process in GL. Different methods (memorized as procepts in the procedural memory) can be used e.g.: (i) forecasting does not imply structural changes ('closed' procept); (ii) foresighting implies structural changes ('open' procept); and (iii) visioning leads to really novel futures. In each case, the selection of a method and its implementation are carried out in global landscapes. We call proceptivation the passage from GL to what it should be in the expected future; it is simulated by scenarios which allow evaluating the consequences with infinitesimal cost. The proceptivation can lead to 3 different kinds of futures, possibly partially mixed upitr : = Optimization futures, withour structural changes, = Contingent futures with some expected for structural changes; = Novel futures with structural changes leading to the emergence of "change in the conditions of change" (Popper), themselves at the root of non expected new structural changes.

19. OPTIMIZATION AND CONTINGENT FUTURES In the optimization method, the anticipator proceeds by simple extrapolation of some present trends, or search for desired futures (BEAR/GBU model stressing values/preferences, Miller 2005). Mathematical models rely on probabilities and/or partial differential equations (in terms of delays and weights of links). Generally the proceptivation does not introduce structural change, except if there are non-linear equations leading to the formation of an attractor (which can be represented by a colimit in ALC). . The contingency method tries to take account of possible external forces. Similar mathematical models are used, often leading to attractors at the root of structural change. AN may have members using different methods, for instance one using optimization, another contingency. Through their interplay they may arrive to a hybrid method consisting of iteration of proceptivations related to each alternative method (Hybrid Scenario Strategic method, Miller 2005)

20. NOVEL FUTURES Transition Transition GL' v GL Time To envision novel futures, the proceptivation must lead to structural changes which cannot be directly deduced from the present as seen in GL. As said before, in ALC structural changes are obtained by a complexification process. Thus the proceptivation should at least require a complexification GL' of GL for some procedure Pr. However, it is not sufficient for 'real' novelty: AN must iterate the process by complexifying GL'; this complexification will produce a novel future ("transformational creativity, Boden 2008) because of: THEOREM. A double complexification where complex links play a role cannot be reduced to a unique complexification.

21. cP" cP C C p p G G p" p" G' G' p' p' Q' Q' Q' Q' A A E E GL' GL HOW COMPLEX LINKS EMERGE c = cG' cG Objectives: Suppress E, Add A, Bind given patterns P and P'. Complexification: E is suppressed as well as all links with one extremity in E, and A becomes a sub-graph. Then iteration of the following operations, each necessitating some delay: A cone of basis P and vertex a new cP is added. For cP to be its colimit, we must add a simple link from cP to C binding the cluster G. A cone of basis P' and vertex a new cP' is added. Since C is the colimit of Q', we must add a simple ink from C to cP' binding the cluster G'. Finally we have an emerging complex link c composite of cG and cG'.

22. INTERPLAY LEADING TO A NOVEL FUTURE Example • Field: engineering design • The issue: • A world leading aeronautic firm wants to anticipate future propulsion systems • A study of all the products designed by the firm over the last decades reveals that optimization of existing engines would not allow the firm to meet the anticipated objectives • The various engineers of the firm works on different concepts. • Some groups worked on future propulsion technologies • But one of them also worked on “mission” : this induced engineers to think out of the traditional scope (propulsion system) and to anticipate brand new ecosystems (contingency) • This, in return, provided radical new ideas of architecture of propulsion system to the other groups (complex links)

23. CONCLUSION The MES methodology has been used to describe the organization and functioning of an Anticipation Literate Community ALC. Its components develop through an individuation process using an important property of ALC, its 'flexible redundancy', formalized by the Multiplicity Principle, necessary for the emergence of components of higher complexity order. In ALC a given anticipator AN of any level, possibly ALC itself, will search for possible futures by an iterated 3 steps process: (i) formation of an archetypal pattern AO with its objects having a common meaning for all the members; (ii) 'retrospection' by construction of a global landscape GL for making sense of the present; (iii) 'prospection' by selection of procepts in GL and their evaluation by proceptivation simulated in a scenario. The maturity level of AN increases with the size of AN and of GL. If AN becomes sufficiently anticipation literate, it may be able to anticipate novel futures, obtained by iteration of a complexification process. Imagination of such a future can modify our apprehension of the present.

24. FOR MORE INFORMATION Memory Evolutive Systems: Hierarchy, Emergence, Cognition, Elsevier, 2007. MENS, a mathematical model for cognitive systems, JMT 0-2, 2009. MENS, an info-computational model for (neuro-)cognitive systems up to creativity, Entropy 14, 2012, 1703-1716. A theoretical frame for Future Studies, On the Horizon, Volume 21 issue 1, 2013. Internet sites where most papers can be downloaded http://ehres.pagesperso-orange.fr http://vbm-ehr.pagesperso-orange.fr THANKS

25. GRAPHS AND CATEGORIES k f'fg Graph = vertices and oriented edges (or links)between them. Path of the graph = sequence of consecutive links. Category = graph + internal compos-ition associating to a 2-path (f, g) a composite fg, which is associative and each object A has an identity iA. The paths of a graph form a category (composition = convolution) . Each category is a quotient of the category of its own paths by the equivalence: "2 paths are functionally equivalent if they have the same composite".

26. COLIMIT OF A PATTERN IN A CATEGORY C = colimP - H s A ci si si = = sj sj Pi Pi f f Pj P Pj Pattern P = finite sub-graph of H. Collective link from P to an object A = family of links si: Pi → A correlated by the links in P ; represented as a cone from (the basis) P to (the vertex) A.. C = colimP P admits C as a colimit (or "binding") if there is a cone (ci) from P to C through which any other cone with basis P factors uniquely ==> C et P have the same operational role. P