The Human/Nonhuman Assemblage The Cultural Heritage as Big Data the police. Archives are good at covering this on the level of "analogue" materials (papers, documents, pictures, analogue files), but when dealing with digitized or born-digital material, the models of curating and organizing tends to adhere to analogue models. Today computation - another word for what codes, programs, software, protocols and algorithms do - is involved in almost all working processes in a society. Businesses and states, including the police, hospitals, armies etc., would not be able to do their job without computation. Sometimes a specific program or algorithm was inevitable and crucial for completing a task. Should not state archives be interested in harvesting some of these programs and algorithms? Indeed, their job is to collect important documents in a work-process, and if one of the key-elements of this process is algorithms, we cannot easily circumvent this. Collecting them should essentially not be any different from the traditional collecting of context information (for instance, the organization of work-processes), which is needed to understand the collected records. All key elements of a work-process should be available. Even if most programs contain many minor algorithms, we can also talk about unique algorithms. Books like, John McCormick's Nine Algorithms That Changed the Future (2011), explores this. Tech-giants - Google, Facebook, Amazon and Microsoft - are totally reliant on specific algorithms for their success. The Google Search Algorithm is probably the most powerful algorithm in the world right now. Many of these algorithms are of course business secrets, but most of them are not, and they are usually available and out in the open after a certain time. GitHubs are good at tracking these declassifications of algorithms. Google Map, TomTom and other GPS systems used by drivers all over the world are the result of the US Department of Defense's decision to declassify their Geographical Positioning Algorithm in 1983 after a tragedy involving a civilian airplane. The algorithm was suddenly available for everybody. It changed driving habits around the world. "The robots are coming for Wall Street," reads a headline from New York Times recently (25/02/16). It predicts that within a decade between a third and a half of the current employees in finance will lose their jobs to automation software. The algorithms will take over. Will the same happen within the archives? Yes and no. However, it is important to note that "intelligent" machines may both liberate the archivists from tedious routines and foster a new kind of creativity which will demand more people and researchers. Humans are not eradicated from the equation, but humans have to form a new creative assemblage with machines. The new archivist is the human/nonhuman assemblage. This makes the archives' services more interesting - perhaps even mind-blowing. I will here briefly discuss three areas where creativity and research is of utmost importance: Big Data, Articulation and Curation. Big Data is the new catch-all term. Everything has become big data in the sense that all human activities emit and generate data that can be stored and assessed to produce new knowledge. This knowledge is usually characterized as predictive analytics. Virtually all big companies run according to this model. Big Data analytics originates in the military/space industrial complex. As armies implemented cameras, satellites and computers in their surveillance and intelligence efforts they gathered so much data that human cognition could no longer assess it. Only computers can deal with Big Data. Big Data algorithms have travelled from

Periodiekviewer Koninklijke Vereniging van Archivarissen

Schetsboek | 2016 | | pagina 37