Worrying Impact of Artificial Intelligence and Big Data Through the Prism of Recommender Systems
Transfer from social to semantic web brought us to an era of algorithmic society, placing issues such as privacy, big data and AI in the spotlight. although neutral by their nature, the power of big data algorithms to impact societies became major concern outcoming with fines issued to Facebook in t...
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University of Belgrade
2021
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oai:doaj.org-article:7b929030a1e143f5b8118c24c725bbb52021-11-17T19:15:42ZWorrying Impact of Artificial Intelligence and Big Data Through the Prism of Recommender Systems10.21301/eap.v16i3.130353-15892334-8801https://doaj.org/article/7b929030a1e143f5b8118c24c725bbb52021-11-01T00:00:00Zhttps://www.eap-iea.org/index.php/eap/article/view/207https://doaj.org/toc/0353-1589https://doaj.org/toc/2334-8801Transfer from social to semantic web brought us to an era of algorithmic society, placing issues such as privacy, big data and AI in the spotlight. although neutral by their nature, the power of big data algorithms to impact societies became major concern outcoming with fines issued to Facebook in the US. These events were initiated by alleged breaches of data privacy connected to recommender system technology, which can provide individualized content to internet users. This paper seeks to explain recommender systems, while elaborating on their social effects, to conclude that their overall impacts might be increase in retail sales, democratization of advertising, increase in internet addictions, social polarization (echo chamber issue), and improvement of political communication. Also, more research should be deployed into low intensity addictions, as potential outcome of recommender systems, and it should be explored how they affect political participation and democracy. Ljubiša BojićMaja ZarićSimona ŽikićUniversity of Belgradearticlerecommender systemsaibig datainternet addictionecho chamberAnthropologyGN1-890ENFRSREtnoantropološki Problemi, Vol 16, Iss 3 (2021) |
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recommender systems ai big data internet addiction echo chamber Anthropology GN1-890 |
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recommender systems ai big data internet addiction echo chamber Anthropology GN1-890 Ljubiša Bojić Maja Zarić Simona Žikić Worrying Impact of Artificial Intelligence and Big Data Through the Prism of Recommender Systems |
description |
Transfer from social to semantic web brought us to an era of algorithmic society, placing issues such as privacy, big data and AI in the spotlight. although neutral by their nature, the power of big data algorithms to impact societies became major concern outcoming with fines issued to Facebook in the US. These events were initiated by alleged breaches of data privacy connected to recommender system technology, which can provide individualized content to internet users. This paper seeks to explain recommender systems, while elaborating on their social effects, to conclude that their overall impacts might be increase in retail sales, democratization of advertising, increase in internet addictions, social polarization (echo chamber issue), and improvement of political communication. Also, more research should be deployed into low intensity addictions, as potential outcome of recommender systems, and it should be explored how they affect political participation and democracy.
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format |
article |
author |
Ljubiša Bojić Maja Zarić Simona Žikić |
author_facet |
Ljubiša Bojić Maja Zarić Simona Žikić |
author_sort |
Ljubiša Bojić |
title |
Worrying Impact of Artificial Intelligence and Big Data Through the Prism of Recommender Systems |
title_short |
Worrying Impact of Artificial Intelligence and Big Data Through the Prism of Recommender Systems |
title_full |
Worrying Impact of Artificial Intelligence and Big Data Through the Prism of Recommender Systems |
title_fullStr |
Worrying Impact of Artificial Intelligence and Big Data Through the Prism of Recommender Systems |
title_full_unstemmed |
Worrying Impact of Artificial Intelligence and Big Data Through the Prism of Recommender Systems |
title_sort |
worrying impact of artificial intelligence and big data through the prism of recommender systems |
publisher |
University of Belgrade |
publishDate |
2021 |
url |
https://doaj.org/article/7b929030a1e143f5b8118c24c725bbb5 |
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AT ljubisabojic worryingimpactofartificialintelligenceandbigdatathroughtheprismofrecommendersystems AT majazaric worryingimpactofartificialintelligenceandbigdatathroughtheprismofrecommendersystems AT simonazikic worryingimpactofartificialintelligenceandbigdatathroughtheprismofrecommendersystems |
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