# Unsupervised Neural Networks for detecting Fake News

Go back to [[Week 3 - Introduction]]

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The same [[Unsupervised Learning]] algorithms that can detect signal from noise in radio and patterns from junk data can find verifiable news from fake news. 

Also, the ability to chew through so much information and unstructured data in such a short period of time to cross-reference and verify claims makes the barrier to entry on creating fake news much higher. 

Page (9)

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Integration or Replacement: Journalism in the Era of Artificial Intelligence and Robot Journalism

Go back to the [[Readings list]] or the [[Master of Philosophy - Main Page]]

Reference: Saad Saad, D., & Issa, T. A. (2020). Integration or Replacement: Journalism in the Era of Artificial Intelligence and Robot Journalism. International Journal of Media, Journalism and Mass Communications. 6(3).

The [relevant section is available here.](https://www.researchgate.net/profile/Saad_Saad13/publication/343263293_International_Journal_of_Media_Journalism_and_Mass_Communications_IJMJMC_Page_1_Integration_or_Replacement_Journalism_in_the_Era_of_Artificial_Intelligence_and_Robot_Journalism/links/5f203ecd92851cd5fa4e48e1/International-Journal-of-Media-Journalism-and-Mass-Communications-IJMJMC-Page-1-Integration-or-Replacement-Journalism-in-the-Era-of-Artificial-Intelligence-and-Robot-Journalism.pdf)

#AIBusinessCase