The fight against fake news has been a big data problem for a long time and is being fought by organizations, academics and data scientists. In this age of big data, science has a big problem, because it does not matter how fast we are processing data if the data is incorrect.

Fake news affects big data veracity because it is news that’s incorrect —due to intentional misinformation— and experts acknowledge that this is a problem that cannot be resolved by manually checking the authenticity of data.

A Case Against Fake News!

In 2016, it was reported that a German 13-year-old girl was raped by refugees in Berlin from the Middle East. This fake news caused massive outrage and hundreds of people took to the streets in protest of this grievous act. Imagine the impact this news had on public safety and peaceful governance.

All over the world — from France, Italy to India — there are instances of fake news causing damage to institutions, communities, and governments. Social media networks play a major role in helping the spread of rumors and fake news today. So even though we applaud the advancements of social media, the fight against fake news is one that major social networks should have begun a long time ago.

Facebook, Google, and other large organizations have recently taken up the fake news fight. But this is not a problem only for social networks and big organizations, we all have to play a small part to ensure that the information we share is accurate. Every organization that presents data to the public, no matter how small the data is, should be a part of this fight.

How Artificial Intelligence Can Help Reduce Fake News

Given how error-prone a manual strategy could be for analyzing big data, the clear answer is artificial intelligence (AI). Artificial Intelligence can be used to detect word patterns that could be fake news stories. Some experts note that it could be a problem for AI’s to understand the data and sort it efficiently. However, for this to work we have to streamline how data is currently classified and indexed in search engines for better results.

Artificial Intelligence systems can continually learn and improve over time, so identifying fake news based upon what system users have already flagged can help improve the veracity of the news.

Data veracity checking with artificial intelligence is a work in progress, but one thing is for sure, fake news is here to stay. As data grows in volume, humans will lack the ability to distinguish the fake from real, and using AI technology to authenticate data will be the only way out of this conundrum.


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