从推荐系统的角度看人工智能和大数据的影响

Ljubiša Bojić, M. Zarić, Simona Žikić
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引用次数: 4

摘要

从社交网络到语义网络的转变将我们带入了一个算法社会时代,将隐私、大数据和人工智能等问题置于聚光灯下。尽管大数据算法本质上是中立的,但其影响社会的力量已成为人们关注的焦点,Facebook在美国遭到罚款。这些事件的起因是据称与推荐系统技术有关的数据隐私泄露,该技术可以向互联网用户提供个性化内容。本文试图解释推荐系统,同时阐述其社会效应,得出其总体影响可能是零售销售的增加、广告的民主化、网络成瘾的增加、社会两极分化(回音室问题)和政治沟通的改善。此外,作为推荐系统的潜在结果,应该对低强度成瘾进行更多的研究,并探讨它们如何影响政治参与和民主。
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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 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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自引率
50.00%
发文量
1
审稿时长
10 weeks
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