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The democratization of artificial intelligence. Net politics in the era of learning algorithms

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dc.contributor.editorSudmann, Andreas
dc.date.accessioned2020-03-10T12:47:32Z
dc.date.available2020-03-10T12:47:32Z
dc.date.issued2019
dc.description.abstractAfter a long time of neglect, Artificial Intelligence is once again at the center of most of our political, economic, and socio-cultural debates. Recent advances in the field of Artifical Neural Networks have led to a renaissance of dystopian and utopian speculations on an AI-rendered future. Algorithmic technologies are deployed for identifying potential terrorists through vast surveillance networks, for producing sentencing guidelines and recidivism risk profiles in criminal justice systems, for demographic and psychographic targeting of bodies for advertising or propaganda, and more generally for automating the analysis of language, text, and images. Against this background, the aim of this book is to discuss the heterogenous conditions, implications, and effects of modern AI and Internet technologies in terms of their political dimension: What does it mean to critically investigate efforts of net politics in the age of machine learning algorithms?en
dc.description.tableofcontents<ul> <li><a href='https://doi.org/10.25969/mediarep/13537'>Andreas Sudmann: <i>The Democratization of Artificial Intelligence. Net Politics in the Era of Learning Algorithms</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13538'>Anne Dippel: <i>Metaphors We Live By. Three Commentaries on Artificial Intelligence and the Human Condition</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13548'>V. N. Alexander: <i>AI, Stereotyping on Steroids and Alan Turing's Biological Turn</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13549'>Axel Volmar: <i>Productive Sounds. Touch-Tone Dialing, the Rise of the Call Center Industry and the Politics of Virtual Voice Assistants</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13550'>Armin Beverungen: <i>Algorithmic Trading, Artificial Intelligence and the Politics of Cognition</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13551'>Lisa Reutter/Hendrik Storstein Spilker: <i>The Quest for Workable Data. Building Machine Learning Algorithms from Public Sector Archives</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13552'>Tobias Matzner: <i>Plural, Situated Subjects in the Critique of Artificial Intelligence</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13553'>Jonathan Roberge et al.: <i>Deep Learning’s Governmentality. The Other Black Box</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13554'>Stefan Rieger: <i>Reduction and Participation</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13555'>Dan McQuillan: <i>The Political Affinities of AI</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13539'>Yvonne Förster: <i>Artificial Intelligence. Invisible Agencies in the Folds of Technological Cultures</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13540'>Alexander Monea: <i>Race and Computer Vision</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13541'>Marcus Burkhardt: <i>Mapping the Democratization of AI on GitHub. A First Approach</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13542'>Andreas Sudmann: <i>On the Media-political Dimension of Artificial Intelligence. Deep Learning as a Black Box and OpenAI</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13543'>Ina Schieferdecker et al.: <i>How to Safeguard AI</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13544'>Christian Djeffal: <i>AI, Democracy and the Law</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13545'>Frank Pasquale: <i>Rethinking the Knowledge Problem in an Era of Corporate Gigantism</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13546'>Jens Schröter: <i>Artificial Intelligence and the Democratization of Art</i></a></li> <li><a href='https://doi.org/10.25969/mediarep/13547'>Andreas Sudmann/Alexander Waibel: <i>“That is a 1984 Orwellian future at our doorstep, right?“ Natural Language Processing, Artificial Neural Networks and the Politics of (Democratizing) AI</i></a></li> </ul>
dc.identifier.doi10.25969/mediarep/13536
dc.identifier.doi10.14361/9783839447192
dc.identifier.isbnisbn:978-3-8394-4719-2
dc.identifier.urihttps://mediarep.org/handle/doc/14462
dc.languageeng
dc.publishertranscript
dc.publisher.placeBielefeld
dc.rightsCreative Commons Attribution Non Commercial No Derivatives 4.0 Generic
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0
dc.subjectKünstliche Intelligenzde
dc.subjectPolitikde
dc.subjectDemokratiede
dc.subjectpoliticsen
dc.subjectartificial intelligenceen
dc.subjectmachine learningen
dc.subjectdigital technologiesen
dc.subjectmedia politicsen
dc.subject.ddcddc:004
dc.subject.ddcddc:320
dc.titleThe democratization of artificial intelligence. Net politics in the era of learning algorithmsen
dc.typebook
dc.type.statuspublishedVersion
dcterms.bibliographicCitationAndreas Sudmann (Hg.): The democratization of artificial intelligence. Net politics in the era of learning algorithms. Bielefeld: transcript (2019). DOI: http://dx.doi.org/10.25969/mediarep/13536.
dspace.entity.typeMiscen
local.academicbookseriesAI Critique
local.coverpage2021-05-29T01:33:52
local.identifier.firstpublishedhttps://doi.org/10.14361/9783839447192
local.source.volume1

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