Social sciences are experiencing an anticipatory turn. A core issue of this turn are the so-called ‘weak signals’. In order to speak of this type of signals, we must use the distinction between weak and strong. The question may be raised, who handles this distinction? That is, who is the observer? It seems that only two answers are possible: the observer is either outside or inside, i.e., either he is a world-observer, or he is a extra-world-observer. In the latter case, the problem of weak signals disappears; after the fact, everybody is able to say “I told you!”. In the former case, the system has to face the dilemma of warning signals. As social systems cannot observe themselves from the outside, the issue of weak signals should be explained as the outcome of a self-referential dynamics that finally leads to the paradox of knowing the unknown. In fact, the difference between weak and strong refers not to the future as such (to what is signalized), but to the observing system itself. The main hypothesis of this contribution is that a signal is weak for a lack of redundancy that hinders the system to combine a reference to an environmental event with a concomitant reference to a systemic cognitive map. By means of a system theory of sign, it should be possible to see the difference between weak and strong as an unfolding device for temporal paradoxes arising in social systems, and to support the hypothesis that, since in social systems cognitive maps are contingent on time, signals can be only weak, never strong.
|Data di pubblicazione:||2016|
|Titolo:||The Strongness of Weak Signals: Self-reference and Paradox in Anticipatory Systems|
|Digital Object Identifier (DOI):||10.1007/s40309-016-0085-1|
|Codice identificativo ISI:||WOS:000387958100001|
|Citazione:||The Strongness of Weak Signals: Self-reference and Paradox in Anticipatory Systems / Cevolini, Alberto. - In: EUROPEAN JOURNAL OF FUTURES RESEARCH. - ISSN 2195-2248. - ELETTRONICO. - 4(4)(2016), pp. 1-13.|
|Tipologia||Articolo su rivista|
I documenti presenti in Iris Unimore sono rilasciati con licenza Creative Commons Attribuzione - Non commerciale - Non opere derivate 3.0 Italia, salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris