The Project



The UNESCO Chair in Anticipatory Systems

The purpose of the Chair in Anticipatory Systems is to both develop and promote the Discipline of Anticipation, thereby bringing a critical idea to life. To this end, we have a two pronged strategy consisting of knowledge development and communication. The two are equally important. While many academic projects naturally emphasize knowledge development, we must also reach a large and disparate audience, and open minds locked within the longstanding legacy of reactive science. Thus, from a practical standpoint, how we conceptualize and communicate the Discipline of Anticipation is as important as the Discipline of Anticipation itself.

While anticipation has been widely studied within a number of different disciplines – including biology, anthropology, cognitive and social sciences – to date nobody has collected and systematically compared the results. For a preliminary survey see, however, R. Poli, The Many Aspects of Anticipation, Foresight, 2010, 12, p. 7-17, and the bibliography M. Nadin, Annotated Bibliography: Anticipation, International Journal of General Systems, 2010, 39(1), p. 35-133. Two figures stand as central contributors to the discipline of anticipation: the mathematical biologist Robert Rosen (see his Anticipatory Systems. Philosophical, Mathematical and Methodological Foundations, New York, Springer, 2nd ed. 2012, and Life Itself. A Comprehensive Inquiry into the Nature, Origin, and Fabrication of Life, New York, Columbia University Press, 1991) and the anthropologist John W. Bennett (see his Human Ecology as Human Behavior: Essays in Environmental and Development Anthropology, New Brunswick and London, Transaction Publishers, 2nd ed. 2002). The former established the theory of anticipatory systems; the latter the connection between anticipation and resilience. 

We propose to centralize the study of anticipation for the first time, and to define the Discipline of Anticipation as a cohesive body of knowledge. To this end, the chair will address a number of key questions, such as:



Objectives

The project’s main objective is the development of the Discipline of Anticipation, including the development of a system of anticipatory strategies and techniques. The more the culture of anticipation spreads, the easier it will be to develop socially acceptable anticipatory strategies. It will then be possible to accumulate relevant experience on how to think about the future and to use anticipatory methods. It will also be possible to try and develop a language and a body of practices that are more adapted for thinking about the future and for developing new ways to address threads and opportunities. 

The following outcomes are envisaged:



Futures Studies and the Discipline of Anticipation


Table summarizing major distinctions

The following table summarizes the multi-dimensional components that distinguish forecasts, foresights and anticipations.

Forecast
  • Predictive, Point-based
  • Closed system
  • Structure prevails
  • Predicative (deterministic)
  • Past-grounded (e.g., time series)
Foresight
  • Predictive within paths, Set of points (scenarios)
  • Semi closed system
  • Structure prevails
  • Predicative (deterministic)
  • Future-grounded
Anticipation
  • Non-predictive
  • Open system
  • Function prevails
  • Impredicative
  • Present-grounded

 Selected excerpts from the papers of two highly regarded professional futurists, Peter Bishop and Riel Miller

 

 

 

Peter Bishop, Ph.D., futurist and Associate Professor of Strategic Foresight, University of Houston, directs the graduate program in Futures Studies at UH, and co-authored Thinking about the Future: Guidelines for Strategic Foresight and Teaching about the Future. He is a founding member and former board member of the Association of Professional Futurists.
 

 

 

Riel Miller, Ph.D., futurist, is Head of Foresight at UNESCO in Paris and has published widely including articles in Foresight and Futures journals. He previously consulted for Xperidox: Futures Consultancy, was an economist and futurist for the OECD, and served as a board member of the Association of Professional Futurists.

Peter Bishop, Propositions based on Toronto, Oxford, in The Future of Foresight Working Document, Association of Professional Futurists, 2013

All professional futurists …


Riel Miller, Framing Propositions for Professional Futurists, in The Future of Foresight Working Document, Association of Professional Futurists, 2013

An imperative or principles version:

Implications:


The  Discipline of Anticipation

Excerpts from the paper R. Miller, R. Poli, P. Rossel, The Discipline of Anticipation. Key Issues. The paper can be downloaded from here.

All efforts to know the future in the sense of thinking about and using the future are forms of anticipation. Equally the future is incorporated into all phenomena, conscious or unconscious, physical or ideational, as anticipation.

The DoA [= Discipline of Anticipation] covers all ways of knowing the later-than-now as anticipation, from those forms of anticipation that are observed, for instance, in a tree that loses its leaves in the Autumn to human planning that attempts to colonize the future and efforts to make sense of emergent novelty in the present by finding inspiration in systemically discontinuous imaginary futures. Looked at as a way-of-knowing the DoA addresses the codification of the myriad of systems of anticipation, both conscious and non-conscious. The DoA develops, sorts, and diffuses descriptions of the processes/systems of anticipation or how the later-than-now enters into reality. […]

Specifically, the DoA provides ideas and tools that can alter and expand the role of anticipation in shaping what humans perceive, including our capacity to make sense of novelty. This is because the theory and practice of the DoA develops and extends the categories and methods of anticipation that can be used to improve discovery and sense making. […]

As every other discipline, the DoA exploits a remarkable variety of methods. This document, however, intentionally leaves aside the discussion on methods in order to remain focused on basic issues. As far as the theories composing the DoA are concerned, the discussion is at such an early phase of development that very little can be said. For this reason we shortly present only two issues, namely Futures Literacy (FL) and complexity.

Futures Literacy

The main strength of the FL proposal is the distinction among different ways of using the future. As said, anticipation (either explicit or implicit) is a way of generating the of necessity imaginary futures on the basis of probabilistic or non-probabilistic thinking in order to understand and act in the present. Concerning explicit anticipation, three main uses can be distinguished: optimization, contingency, and novelty. […] The point of distinguishing these three categories is to assist with the challenge of linking specific tasks to specific methods or approaches for both thinking about and shaping the future. Because optimization actively attempts to impose patterns from the past on the future it privileges causal-predictive methods, often implemented through formal (usually algorithmic) models running historical data. Contingency planning is how we try to prepare for already recognized possible surprises (often with the aim of surviving or continuing without systemic disruption). Using novel futures to discover new ways of making sense of the emergent present provides one way of taking advantage of the unknowable as it starts to become knowable, enhancing the capacity to discover the present. Novelty includes objects and processes emerging from our activities and the subsequent actions we exert upon and with them. […]

The distinction among the three ways of using the future is meant to be analytical. It does not imply that at any given time people, communities or institutions individually use only one of them. As a matter of fact, all the ways of using the future are usually employed together, in different proportions. The analytic distinction into three main types is a conceptual tool for better classifying and understanding the way in which communities and other relevant subjects use the future.

Complexity

During the past sixty years complexity has been defined in so many different ways that the term risks becoming meaningless. Furthermore, complexity is one of those issues that quickly veers into difficult technicalities. Leaving aside many otherwise needed details, embracing complexity for the DoA means awareness that complex systems are such that (1) they can never aver be fully captured by any model (i.e., models are always incomplete); and (2) under suitable conditions small changes may generate huge effects.

One of the simplest ways to start grasping complexity is by distinguishing complex from complicated problems and systems. Complicated problems originate from causes that can be individually distinguished; can be addressed piece-by-piece; for each input to the system there is a proportionate output; the relevant systems can be controlled and the problems they present admit permanent solutions. On the other hand, complex problems and systems result from networks of multiple interacting causes that cannot be individually distinguished; must be addressed as entire systems, that is they cannot be addressed in a piecemeal way; they are such that small inputs may result in disproportionate effects; the problems they present cannot be solved once and for ever, but require to be systematically managed and typically any intervention merges into new problems as the result of the interventions to deal with them; and the relevant systems cannot be controlled – the best one can do is to influence them, learn to dance with them as Donella Meadows aptly said. […]

The DoA is in its early stages of development. In this regard, the DoA is not different from any other discipline (or science for that matter). Further developments of the DoA require not only theory enhancement but also systematic testing against reality. The latter in particular helps to verify the capacities of the DoA before aiming at its broader implementation. Finally, it is worth noting that there is nothing mysterious in the DoA: as difficult as it may appear, all the components of the DoA can be learned.

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