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      The Nooscope manifested: AI as instrument of knowledge extractivism

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          Abstract

          Some enlightenment regarding the project to mechanise reason. The assembly line of machine learning: data, algorithm, model. The training dataset: the social origins of machine intelligence. The history of AI as the automation of perception. The learning algorithm: compressing the world into a statistical model. All models are wrong, but some are useful. World to vector: the society of classification and prediction bots. Faults of a statistical instrument: the undetection of the new. Adversarial intelligence vs. statistical intelligence: labour in the age of AI.

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          ImageNet classification with deep convolutional neural networks

          Alex Krizhevsky, Ilya Sutskever, Geoffrey E Hinton (2017)
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            How we know universals; the perception of auditory and visual forms.

            W PITTS, W S McCULLOCH (1947)
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              Could Big Data be the end of theory in science? A few remarks on the epistemology of data-driven science.

              Fulvio Mazzocchi (2015)
              Article 0 comments Cited 44 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Matteo Pasquinelli: mpasquinelli@hfg-karlsruhe.de
                Journal
                Journal ID (nlm-ta): AI Soc
                Journal ID (iso-abbrev): AI Soc
                Title: Ai & Society
                Publisher: Springer London (London )
                ISSN (Print): 0951-5666
                ISSN (Electronic): 1435-5655
                Publication date (Electronic): 21 November 2020
                Publication date PMC-release: 21 November 2020
                Pages: 1-18
                Affiliations
                [1 ]GRID grid.448697.0, ISNI 0000 0000 8636 9001, Media Philosophy Department, , Karlsruhe University of Arts and Design, ; Karlsruhe, Germany
                [2 ]GRID grid.10822.39, ISNI 0000 0001 2149 743X, New Media Department, Academy of Arts, , University of Novi Sad, ; Novi Sad, Serbia
                Article
                Publisher ID: 1097
                DOI: 10.1007/s00146-020-01097-6
                PMC ID: 7680082
                PubMed ID: 33250587
                SO-VID: eb7819be-e12c-463d-b89b-83a28f67be8a
                Copyright © © The Author(s) 2020
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                Date received : 27 March 2020
                Date accepted : 14 October 2020
                Funding
                Funded by: Staatliche Hochschule für Gestaltung Karlsruhe (5131)
                Open Access :

                Open Access funding enabled and organized by Projekt DEAL.

                Categories
                Subject: Original Article

                Keywords: nooscope,political economy,mechanised knowledge,information compression,ethical machine learning
                Data availability:
                Keywords: nooscope, political economy, mechanised knowledge, information compression, ethical machine learning

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