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The Scary Black Box: AI Driven Recommender Algorithms as The Most Powerful Social Force
dc.creator | Bojić, Ljubiša | |
dc.creator | Bulatović, Aleksandra | |
dc.creator | Žikić, Simona | |
dc.date.accessioned | 2022-12-23T10:05:10Z | |
dc.date.available | 2022-12-23T10:05:10Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | http://rifdt.instifdt.bg.ac.rs/123456789/2716 | |
dc.description.abstract | Recommender algorithms shape societies by individually expo sing online users to everything they see, hear and feel in real time. We examine the development of recommender algorithms from t he Page Rank and advertising platforms to social media trending tools to draw conclusions about their social effects. Decisions on how to simplify the complex world around us into dozens of possibilities immensely affect societies and individuals. Similar to our perceptive apparatus, algorithms are eyes and ears in the online world, as they focus our attention towards what they „think” should be important, which is similar to news priming. That is why recommender algorithms are compared to mass media, given their similar roles to sell products and prolong content exposure of online users. This inquiry concludes that AI driven recommender algorithms represent the most powerful social force at present. | sr |
dc.language.iso | en | sr |
dc.publisher | Filozofski fakultet Univerziteta u Beogradu, Odeljenje za etnologiju i antropologiju | sr |
dc.relation | info:eu-repo/grantAgreement/MESTD/inst-2020/200025/RS// | sr |
dc.rights | openAccess | sr |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.source | Etnoantropološki problemi | sr |
dc.subject | recommender systems | sr |
dc.subject | mass media | sr |
dc.subject | social polarization | sr |
dc.subject | echo chambers | sr |
dc.subject | negative news | sr |
dc.title | The Scary Black Box: AI Driven Recommender Algorithms as The Most Powerful Social Force | sr |
dc.type | article | sr |
dc.rights.license | BY | sr |
dc.citation.issue | 2 | |
dc.citation.volume | 17 | |
dc.identifier.doi | 10.21301/eap.v17i2.11 | |
dc.type.version | publishedVersion | sr |
dc.identifier.fulltext | http://rifdt.instifdt.bg.ac.rs/bitstream/id/9479/bitstream_9479.pdf |