Humanities & Social Sciences 7 (2016 9) 1553-1561 ~ ~ ~ УДК 009:004.94 Fictions of Possibility: Simulation for the Humanities from its History in the Technosciences Willard McCarty* King’s College London, 26-29 Drury Lane, London WC2B 5RL UK Received 29.01.2016, received in revised form 13.05.2016, accepted 21.06.2016 Even a brief sketch of the history of simulation, given here for physics, climatology and biology, reveals from the perspective of the humanities possibilities for expansive and adventurous imaginative work. <...> Despite the fact that simulation as we know it began its rapid and transformative growth with digital computing 70 years ago, it is only within the last decade that it has received critical attention in the humanities. <...> Simulation began at the end of World War II with digital computing, and by the end of the 1960s had spread throughout the social sciences. <...> But it has remained almost unknown to the humanities, receiving minor critical attention only within the last decade. <...> My aim here is to lay a suggestive basis for more and better critical attention to it. © Siberian Federal University. <...> My argument will be that simulation is a way, a technological logos, for “imagining what you don’t know” (McGann 2002) and in some cases cannot know in any other way. <...> Simulation is closely twinned with modelling, so I must say something at the Willard McCarty Fictions of Possibility: Simulation for the Humanities from its History in the Technosciences outset about modelling itself, and so about ‘model’. <...> But the idea it points to is fundamental to scholarly thought, as the great Lithuanian sociologist Teodor Shanin has shown (Shanin 1972), and at the basis of all computing, hence largely unnoticed and therefore a topic of considerable importance. <...> This process is what I mean by ‘modelling’ (McCarty 2005). <...> But unlike modelling, in which you isolate an aspect of that which you wish to study and subject that aspect to close analysis, simulation addresses systems that cannot be known merely from considering their parts in isolation – complex systems (Jervis 1997). <...> Simulation instead models the system itself, its components and dynamic structures, then turns this model loose to see what happens. <...> On the one <...>