{"resolved":true,"match_type":"uuid","source_type":"original_book","book_id":"24410bf1-91f1-4e6b-9613-e64f0132d341","title":"The Stack On Software and Sovereignty","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9780262029575","requested_by":"printed_page","book":{"source_type":"original_book","book_id":"24410bf1-91f1-4e6b-9613-e64f0132d341","id":"24410bf1-91f1-4e6b-9613-e64f0132d341","uuid":"24410bf1-91f1-4e6b-9613-e64f0132d341","title":"The Stack On Software and Sovereignty","normalized_title":"thestackonsoftwareandsovereignty","author":null,"edition":null,"publisher":null,"year":null,"isbn":"9780262029575","isbns":["9780262029575"],"parsed":true,"ai_readable":true,"document_type":"book","page_count":517,"navigation_url":"https://workshop.closeclaw.top/ai/book/24410bf1-91f1-4e6b-9613-e64f0132d341","title_url":"https://workshop.closeclaw.top/ai/title/The%20Stack%20On%20Software%20and%20Sovereignty","fixed_page_url_template":"https://workshop.closeclaw.top/ai/book/24410bf1-91f1-4e6b-9613-e64f0132d341/page/{printed_page}","path_api_url_template":"https://workshop.closeclaw.top/api/ai/book/24410bf1-91f1-4e6b-9613-e64f0132d341/page/{printed_page}","read_url":"https://workshop.closeclaw.top/api/ai/read/24410bf1-91f1-4e6b-9613-e64f0132d341","page_url":"https://workshop.closeclaw.top/api/ai/books/24410bf1-91f1-4e6b-9613-e64f0132d341/page","search_url":"https://workshop.closeclaw.top/api/ai/books/24410bf1-91f1-4e6b-9613-e64f0132d341/search"},"page":{"printed_page":334,"pdf_page":348,"physical_index":348,"physical_index_base":0,"printed_page_status":"recognized","page_sha256":"ef05abac788bd415655c8c12555d83a6bca92180944bf185459e2e1ab84e2989"},"chapter":"Fheck The Stack |On Software and Sovereignty Benjamin H. Bratton","content":"Tarde ’ s Monadology and Sociology (1893). <sup>60</sup> Tarde writes, “ If statistics continues to progress as it has done for several years, if the information which it gives us continues to gain in accuracy, in dispatch, in bulk, and in regularity, a time may come when upon the accomplishment of every social event a figure will at once issue forth automatically, so to speak, to take its place on the statistical registers that will be continuously communicated to the public and spread abroad pictorially, ” and so big data optimism is born, at least in theory. With the benefit of second-order cybernetics in hindsight, we understand that the “ registration ” process is bidirectional, that reporting agents in such a system both send and receive information to a higher-order governing abstraction. The swarm is measured in relation to how algorithmic governance feeds back to it, resensing its reactions, and so on. From the opposite perspective of the User looking to the platform, what may appear as data visualization may prove to be an Interface allowing delimited access and even control of the platform network and its data, and so between the edge-and-node visualizing one another, the Interface also becomes a visual diagram indexing the current state of this multiscalar recursion (at least in principle). The immediate question to ask on behalf of governance to this idealized cybernetic flow is where to locate anything like planning. Is the plan still a future model pushing from the center out, or is it now an emergent pricing index pushing from the periphery in? Neither extreme is really adequate on its own, and so instead we would focus on how planning and programming, some with the force of law, may be situated at (if not originate from) the Interface layer in the form of the model-simulation. We hold that the epistemic significance of big data would be realized by their ability to find and surface utterly alien patterns and relationships among the measured, and thereby to disturb our doxic conventions, even, and especially when, those interpretations are sensible only to machine Users (more on this below). Unfortunately, to date these methods seem to more disposed to optimize surgical correlations, confirming basic presumptions, and delivering high-resolution skeuomorphologies that don ’ t feel as fragile as they really are only because everyone else is making queries and visualizing test data based on the same conceptual conventions.\n\nIn the Address chapter, I introduced the notion of “ deep address, ” an expansive concept suggesting the identification of objects and events with a granularity that far surpasses the scales at which humans perceive physical space and duration. We observe the world as given by the capabilities of binocular vision that can register light between infrared and ultraviolet wavelengths, memory that can capture and forget events that happen in seconds or years, and so on. The physical world itself also works much faster and slower than that, and between nanometric and astronomic magnitudes, there is much we miss without using microscopes and telescopes. As for all of the things and events beyond natural perception, the design program of deep address considers how it is that some as yet unspecifiable means to sense their presence and to identify them according to a generic addressing matrix, and even to network them one to the other, would crack open the world ’ s information portraiture well beyond the normal scale of Internet of Things. <sup>61</sup> That is, the governable space of deep address is not only limited by the technological ability to see and sense something but also by the conceptual categorical systems in place that interpret what is seen and sensed as being something worthy of a discrete address or not. As discussed, any governing system, especially those situated as Cloud Polis, congeals into a functioning governing platform by the combination of these two contingent forms of power and knowledge. The platform sees what it can, what it is programmed to sense, and it identifies and addresses those perceptions according to how it is programmed to “ think, ” seeing what it thinks and thinking what it sees. At the same time, this is a highly dynamic process and one feeds back into the other, and any durable platform will evolve according to how and what it thinks about anomalous signals. The “ alien insights ” we hope appear from any sufficiently smart data analysis may begin as entropic noise and in time become foundational typologies and ontologies. This is where the nomos of the Cloud really works itself out, inch by inch. As Stewart Elden writes, “ Territory should be understood as a political technology, or perhaps better as a bundle of political technologies. Territory is not simply land, in the political-economic sense of rights of use, appropriation, and possession attached to a place; nor is it a narrowly political-strategic question that is closer to a notion of terrain. Territory comprises techniques for measuring land and controlling terrain. ” <sup>62</sup>\n\n334\n\nThe Stack to Come","previous_page":333,"next_page":335}