Worrying Impact of Artificial Intelligence and Big Data Through the Prism of Recommender Systems
Bibliographic Data
| ID | 14713747 |
|---|---|
| Authors | Ljubisa Bojic (0000-0002-5371-7975, University of Belgrade), Maja Zarić, Simona Žikić (0000-0001-6093-1665, Singidunum University) |
| Year | 2021 |
| Volume | 16 |
| Issue | 3 |
| Publication date | 2021-11-16 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Etnoantropološki problemi / Issues in Ethnology and Anthropology (JOURNAL) |
| Journal identifiers | ISSN: 0353-1589 • E-ISSN: 2334-8801 |
| Publisher | University of Belgrade - Faculty of Philosophy - Department of Ethnology and Anthropology (PUBLISHER) |
| DOI | 10.21301/eap.v16i3.13 |
| OpenAlex | W3213394930 |
| Language | EN |
| Citations received | 3 |
| References cited | 20 |
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
Big data · Data mining · Data science · Internet privacy · Political science · Politics · Popularity · Prism · Recommender system · Sentiment analysis · Social media · The Internet · World Wide Web · Artificial Intelligence · Computer Science · FinTech, Crowdfunding, Digital Finance · Impact of AI and Big Data on Business and Society · Law · Mental Health via Writing
Internet Addiction or Excessive Internet Use
Private traits and attributes are predictable from digital records of human behavior
Breaking the filter bubble
Covid-Induced Economic Uncertainty
Ten simple rules for responsible big data research
Exposure diversity as a design principle for recommender systems
Internet Addiction
Prevalence of pathological internet use among adolescents in E urope
Big data and human geography
Cyberpiracy and morality
Big data privacy
A model of opinion and propagation structure polarization in social media
Who is responsible for Twitter’s echo chamber problem? Evidence from 2016 U.S. election networks
Aristotle and Natural Law
Deep neural networks are more accurate than humans at detecting sexual orientation from facial images
Recommender systems and their ethical challenges
What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets
Critical data studies
Big Data from the bottom up
Big Data ethics
| Unique citing works | 3 |
|---|---|
| Citations per year | 0,75 |
| Citation span | 2022 - 2024 (3) |
| Citation velocity | recent |
| Highly cited | No |
| Citation types | Neutral: 3 |