Recent technological advancements like the internet have vastly improved the speed and the mode of communication, but they have given rise to a new problem, “fake news.”

Fake news is a false story or information peddled to push a narrative or the cause of the source. Every internet user, at some point, has come across fake news. The stories are usually written to sensationalize or muddle the truth and are spread faster than the truth, according to a 2018 research.

Essentially, the chances of an internet user receiving accurate information are relatively small. As a result, most internet users are susceptible to consuming twisted or falsified materials that fit a narrative.

How A.I. combats fake news and bias

With the fake news menace fast spreading, new technological advancements in artificial intelligence (A.I.) have been developed to curb its spread.

A.I. programs can perform linguistic analysis on the textual content to look for word patterns, syntactic structure, and readability. This analysis helps A.I. distinguish between computer-generated content and the ones produced by humans. The programs can also examine texts to check for hate speech in word vectors, word placements, and even connotations.

Fake News

Source: Merriam Webster

One major project that has helped in combating fake news is Fandango. Fandango is the brainchild of the European Union aimed at addressing “the aggressive emergence of fake news and post-truth effect.” The program crawls the internet to identify identical claims that fact-checkers have verified as false.

The program helps journalists track the source of false information and curb it before they get out of hand.

To verify claims and combat misinformation, PolitifactSnopes, and FactCheck engage human specialists to investigate the authenticity of reports. Upon proving a false claim, A.I. programs are deployed to crawl the web for similar information. These programs also issue reputation scores to website articles after it has verified their authenticity.

However, the reputation scores are issued following the completion of Sentiment Analysis, Opinion Analysis, Revision Analysis, and Propaganda Analysis. Sentiment analysis entails the examination of the journalist’s attitude toward the news. At the same time, Opinion Analysis examines whether the article is riddled with personal feelings, viewpoints, convictions, or assessments.

Revision analysis checks for a news story’s impact on public perception and mood. Propaganda Analysis also helps discover potential false information using different persuasion strategies. By combining the four analyses, A.I. helps verify the authenticity of claims and eliminate bias from the writers.

The challenges

While A.I. technologies like G.P.T. -3 have come close to replicating human-made materials, it is still far from attaining perfection. At some point, most A.I.s have even been accused of contributing to the spread of fake news and even bias. However, this can be credited to their use of Machine Learning which relies on human information.

There have also been issues of racial discrimination when using A.I. technologies. An M.I.T. Media Labs investigation uncovered flaws in facial recognition that resulted in a Netflix documentary.

Another visible issue is the inability of A.I. technologies to recognize humor and parody. As a result, it can misread real stories for fake ones if they are presented in a joking manner.

This article is originally from MetaNews.

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