%0 Journal Article %1 esposito2017artificial %A Esposito, Elena %D 2017 %J Zeitschrift für Soziologie %K Artificial_Intelligence Big_Data Deep_Learning Doppelte_Kontingenz Double_Contingency Künstliche_Intelligenz Neural_Networks Neuronale_Netzwerke Social_Algorithms Soziale_Algorithmen Systems_Theory Systemtheorie Tiefgehendes_Lernen %N 4 %P 249--265 %R 10.1515/zfsoz-2017-1014 %T Artificial Communication? The Production of Contingency by Algorithms %U https://www.degruyter.com/view/journals/zfsoz/46/4/article-p249.xml %V 46 %X Discourse about smart algorithms and digital social agents still refers primarily to the construction of artificial intelligence that reproduces the faculties of individuals. Recent developments, however, show that algorithms are more efficient when they abandon this goal and try instead to reproduce the ability to communicate. Algorithms that do not “think” like people can affect the ability to obtain and process information in society. Referring to the concept of communication in Niklas Luhmann’s theory of social systems, this paper critically reconstructs the debate on the computational turn of big data as the artificial reproduction not of intelligence but of communication. Self-learning algorithms parasitically take advantage – be it consciously or unaware – of the contribution of web users to a “virtual double contingency.” This provides society with information that is not part of the thoughts of anyone, but, nevertheless, enters the communication circuit and raises its complexity. The concept of communication should be reconsidered to take account of these developments, including (or not) the possibility of communicating with algorithms.

@article{esposito2017artificial, abstract = {Discourse about smart algorithms and digital social agents still refers primarily to the construction of artificial intelligence that reproduces the faculties of individuals. Recent developments, however, show that algorithms are more efficient when they abandon this goal and try instead to reproduce the ability to communicate. Algorithms that do not “think” like people can affect the ability to obtain and process information in society. Referring to the concept of communication in Niklas Luhmann’s theory of social systems, this paper critically reconstructs the debate on the computational turn of big data as the artificial reproduction not of intelligence but of communication. Self-learning algorithms parasitically take advantage – be it consciously or unaware – of the contribution of web users to a “virtual double contingency.” This provides society with information that is not part of the thoughts of anyone, but, nevertheless, enters the communication circuit and raises its complexity. The concept of communication should be reconsidered to take account of these developments, including (or not) the possibility of communicating with algorithms.}, added-at = {2020-06-29T15:54:56.000+0200}, author = {Esposito, Elena}, biburl = {https://www.bibsonomy.org/bibtex/229a0a853b635767c87bd66ce8b671013/meneteqel}, doi = {10.1515/zfsoz-2017-1014}, file = {[23660325 - Zeitschrift für Soziologie] Artificial Communication The Production of Contingency by Algorithms:J\:\\Publikationen\\6_Citavi\\Projects\\Fachliteratur Mitbestimmung\\Citavi Attachments\\[23660325 - Zeitschrift für Soziologie] Artificial Communication The Production of Contingency by Algorithms.pdf:pdf}, interhash = {2c727205d5b2726926fcbdeb1f6b815f}, intrahash = {29a0a853b635767c87bd66ce8b671013}, issn = {0340-1804}, journal = {Zeitschrift für Soziologie}, keywords = {Artificial_Intelligence Big_Data Deep_Learning Doppelte_Kontingenz Double_Contingency Künstliche_Intelligenz Neural_Networks Neuronale_Netzwerke Social_Algorithms Soziale_Algorithmen Systems_Theory Systemtheorie Tiefgehendes_Lernen}, language = {ger}, number = 4, pages = {249--265}, timestamp = {2020-06-29T15:54:56.000+0200}, title = {Artificial Communication? The Production of Contingency by Algorithms}, url = {https://www.degruyter.com/view/journals/zfsoz/46/4/article-p249.xml}, urldate = {29.06.2020}, volume = 46, year = 2017 }