“The new conquerors, who we’ll call the cyberneticians, do not comprise an organized party — which would have made our work here a lot easier — but rather a diffuse constellation of agents, all driven, possessed, and blinded by the same fable.”
– Tikkun, The Cybernetic Hypothesis
“Everything is becoming science fiction.”
– J.G. Ballard
Reading Luciana Parisi’s essay for the acceleration reader one realizes just how technical algorithmic discourse can become. Parisi herself has seen a great shift from the early modes of computational design based on deductive forms of reasoning and digital architectures toward more inductive and material forms in which “physical properties are said to be the motor of simulations” wherein “the local behavior of materials from which complex structures emerge” (405) are becoming central.1 Instead of computational design based on some a priori and passive acceptance of established proofs and truths this inductive path allows for process and adaptation to various data driven material influxions to drive the designs.
This form of computational design is anti-representational to the degree that it is less concerned with contemplation of the artifact and more oriented toward “action, operation, and processing” in which computation is a pragmatic effort that aligns itself with the activities of material process than as some passive datum (405). Instead of a computational model based on the notions of shaping matter, this one is guided by an inducement to follow the movement of matter, tracking it in practical functional terms, which carefully incorporates the movement of material through reflective processes back into the design in an ongoing revisionary feedback-loop.
Ultimately she tells us as a “part of the generic tendency to accelerate automation, the turn to inductive reasoning in computation does not simply aim to instrumentalise or mechanise reason and thus establish the formal condition from which truths can be delivered, but more explicitly allows matter to become the motor of truth, to become one with the ultimately constitutive of formal reason, of the rules and the patterns that emerge in the automation of space and time” (406). Rather than a concern for the material realm per se she is more interested in the computational and automatic production of its physically induced models, and rather than simulating material behavior in itself, which she sees as a meta-biological form of computation – that continuously scans the properties of matter for data analysis – she is more interested in the process itself, the feed-back loops reinscribed into the system of the computational design as an ongoing open ended process. For her the important thing is not the design itself but rather the type of computational reasoning that is used to delimit the algorithmic processes that drive the process. She asks: What and how is algorithmic reason? The rest of the essay tries to answer that question.
One of the problems she sees within current computational design theory is its investment in a deductive form of materialist idealism in which an almost Parmedian seamless fusion of thought and matter are embraced (407). One of the things we have to admit is that there is a gap or disconnect between what algorithms do and our perception of those processes. The subject as subject needs to be pulled out of the equation: these processes are not for us. In fact they are intrinsic to the scientific image itself not to our common sense or manifest image of their properties and actions. Another thing she tells us we have to face is the notion of incompleteness, the Godel paradox; or, even Turing test of incomputability. The point being that mathematics is incomplete so that no finite set of axioms or rules can provide the perfect computational algorithm to cover all aspects of physical processes or data. There will always be something left out, an excess that cannot be computed into the equation.
What she is saying is that reality is far more complex than any mathematical algorithm we might invent to capture it or represent it can describe in representational terms: reality is for all intents and purposes unrepresentable, yet expressible in actions. All we have are probabilistic or statistical estimations, etc. This is the problem of randomness in computational design. She covers the history of this problem in detail then summarizes the basic quandary about the uncertainty or incomputability in any system (i.e., the issue that computation works within this open-incomplete system in such a way that it continuously updates, revises, and produces new axioms as part of an ongoing project that may be interminable. The outcome of this is the acceptance of a universe that is uncertain, incomplete, complex, and open-ended).
What’s interesting is her conclusions. She admits that computational design is based on the premise that a pragmatics of doing and practicing is needed actually to activate and inscribe the real processes of the world. That’s because the acceleration of automation “perfectly coincides with the technocapitalist illusion that matter can generate infinitesimal variations, an inexhaustible abundance that turns continuously smaller elements into vast resources for the productive eternity of the whole” (417). She follows Whitehead in affirming the need for speculative form of reason that allows for encounters with finitude and limits, one that accounts for the incomputability of parts that interfere and perturb the mechanisms of the whole (419).
She also follows Whitehead in his suggestion that we cannot bind ourselves to the complete formalism of practical or sufficient reason, because as he argued “the one-to-one relation between mental cogitations and actual entities underestimates the speculative power of reason” (419). Instead of a formal or practical reason Whitehead’s speculative reason is oriented toward “final causation, and not merely by the law of the efficient cause” (420). What this entails is the acceptance of unproven ideas rather than the reliance on strict facts and data. The point being that conceptual prehensions are based on a notion of selection and evaluation that both displaces the fact beyond observation and, also, recognizes it at another level of reality (421). Speculative reason is a rule-based system that adds novelty as one of its criteria of judgment because of the very fact that we do not have access to all the facts of the case, but are bound to a whole that is always in excess of itself thereby in need of the novelty of speculative reason to obviate through indirect access what practical or formal reason cannot do through direct access to the facts of the case.
Yet, Whitehead’s notion of final cause is not to be construed as teleological in the mundane sense but rather as the affirmation of an open-ended and incomplete universe that can never be ultimate tabulated even by speculative reason. As Parisi puts it for “Whitehead speculative reason implies the asymmetrical and non-unified entanglement of efficient and final cause, and must be conceived as a machine of emphasis upon novelty” (422).
At the heart of the new incorporation of speculative reason into computational architectures, and the attendent algorithmic automation of its processes, is the accompaniment of an infinite amount of complexity that is always in an operative and optative mode of continuous update and revisioning that reveals the very axiomatic truths that are immanently enfolded into the systems it expresses in action (423). She admits that technocapitalism has already adjusted from its earlier deductive to this newer inductive mode of speculative reasoning, and that in fact it is working even now on the complexities of data and structure that will lead to the point when “automated algorithms are able to redirect their own final reason in the computational processing of infinite amounts of data” (424). This would be what so many have termed the ‘Singularity’: the moment when computational machines begin to manifest thought that appears to be aware. A post-intentional future when machines become fully aware organized beyond human intentions or affective relations, expressing only the complexity of the world without end.
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A few observations on the book so far. Maybe this is good for the specialized journals of academia but I wonder how effective it is for a book presenting the basis of a supposed movement – if we can even call it that. Accelerationism is more of a catch word, a notion around which ideas circumambulate from many domains of knowledge. For a while now Hartmut Rosa has dealt with social accelerationism in books like Alienation and Acceleration: Towards a Critical Theory of Late-Modern Temporality, Social Acceleration: A New Theory of Modernity, High-Speed Society: Social Acceleration, Power, and Modernity. Yet, I have not seen mention of her work within the accelerationist discourse along with other authors such as Stefen Breuer, Herfried Munkler, William E. Connolly, William E. Scheuerman, etc. Even in this work there has been no mention of such luminaries as Henry Adams, Georg Simmel, Filippo Tommaso Marinetti, John Dewey, and, even those of the far right like Carl Scmitt. All of these precursors of accelerationism offered aspects of this theme within their own writings. It may be an oversight or maybe an ideological filter applied to their selection; or, even a blanketed preference for certain themes rather than others. Either way, it’s curious to one outside the box so to speak. As an outsider I’ve pondered accelerationism for a while but have wondered if it affords any real traction and staying power in the market of ideas being presented around the philososphere or not? Beyond a few meetings here and there I haven’t seen much real activity going on with this idea or whether it will produce any real results in the political spectrum at all. Time will tell I suppose.
1. #Accelerate# the accelerationist reader. Editors Robin Mackay & Armen Avanessian (Urbanomic, 2014)