The proliferation of fake news on Facebook and Google has been a hot-button topic after the
2016 US presidential election. Fake news phenomenon is not limited in the political sphere. The porn
industries have been using affiliate marketers to send fake news to reach more consumers, even children.
Easy availability of pornography for children on the internet has been an issue. In US, the average age of
exposure to porn is 11 to 12. Frequent exposure to pornography may lead to normalization of harmful
behaviors. Starting late 2013, internet service providers in Britain made “family-friendly filters,” which
block X-rated websites, the default for customers, because kids are exposed to pornography at a young age.
Google banned pornographic ads from its search engine from July 2014. Prostitution and escort services
extend its market despite these efforts for the sake of the upsurge porn fake news. Porn fake news is
produced purposefully to click, share, react, and comment. To mitigate the damage caused by porn fake
news, designing a fully automated fake news detector is currently infeasible, because the problem at hand is
too complex for technology alone. Even the subproblem of defining the criteria under which to classify
news as “fake” creates ambiguity that requires human judgment. The ability to determine whether an article
is real or fake requires more than just information about the article; it requires an understanding of cultural
factors, for example “tea” maybe used by prostitution and escort services in Taiwan. This paper suggests
one way to use artificial intelligence and human judgment to make it more valid to quarantine porn fake
news.
