Big Data, Artificial Intelligence, and Machine Learning Algorithms: A Descriptive Analysis of the Digital Threats in the Post-truth Era
Abstract
Did the utilization of big data change everything about how information circulates? Our digital data have been kept in big warehouses that we name ‘big data’. All the things that we do in virtual life leave a digital footprint and thanks to machine learning algorithms; in our newsfeed, we mostly face contents, which are similar to the subjects that we looked for before. Big data are being used for manipulating people to buy new products, to travel to new places, to read new books, etc. However, as it emerged in 2016 with Cambridge Analytica Scandal of Facebook, sometimes those technologies construct a threat for democracy. The underlying reason is that in our days, big data and AI algorithms have been used by political campaign managers to manipulate and/or persuade people through diffusion of promoted ‘false’ contents. The aim of this study, by doing a descriptive analysis of very recent historical events like the failure of Microsoft’s AI Tay and Youtube’s effects on the presidential election in Brazil, is to define very current digital threats against democracy. Additionally, to better describe and discuss these digital threats we did semi-structured interviews with four experts who work on AI algorithms, big data, and social engineering. Our analyses and findings that we gathered from semi-structured interviews showed that there are several digital threats in the post-truth era that we live in like digital manipulation, violation of data privacy and misuse of big data, personalized search engine algorithms that create filter bubbles, the ease of production and diffusion of fake contents.
Keywords
References
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Details
Primary Language
English
Subjects
-
Journal Section
Research Article
Authors
Tirse Filibeli
*
0000-0003-4642-2279
Türkiye
Publication Date
December 28, 2019
Submission Date
September 1, 2019
Acceptance Date
December 5, 2019
Published in Issue
Year 2019 Number: 31
Cited By
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