Fighting Fake News
Fake news was most likely one of the most heard and used terms in 2017. The term is used to describe untrustworthy or false reporting in the mainstream media. It is also used to explain the phenomena where Facebook users randomly share false Facebook headlines which were published, i.e. by an ultra-left or ultra-right Facebook page. Both channels are the reason why as many people as never before have been in contact with the actual fake news.
I think that fake news and biased reporting are a problem. But as they reflect a problem, they also represent huge business opportunities for startups. I think the world finally requires a reliable technology to flag fake news or biased news. Here are a few ways how I think we can develop technology to fight fake news:
- Flagging Fake News: I think that flagging wrong stories which are undoubtedly fake is the most straightforward task. This might work by match the story with the millions of other stories, Facebook updates, Instagram posts, Tweets, etc. published online. If there is an inconsistency, the post will be flagged as “untrustworthy” or “fake.”
- Analyzing language patterns: We must research different language patterns or how language is used in accurate reporting and how it is used in fake reporting. If there is a significant difference, the algorithm or AI may automatically flag the story and lower the trustworthiness score.
- Eyewitness Proof: The big data large companies gather today – whether it is Facebook, Google, or even Apple – will allow inventors to ask real eyewitnesses whether a published story is real or whether it contains a strong bias. This might also influence a trustworthiness index of a given story.
- Author Background Check: We can use today’s technology to automatically and critically check the backgrounds of all authors who publish a story. If a given author is known for releasing fake stories or badly researched articles in the past, this might immediately influence the current trustworthiness index. The same will be true the other way around, where credible authors will have a higher ponderosity.
- Read-Then-Comment: All large social media, as well as large publishers, can or should implement a feature which indicates whether a commentator has read a given news story or not. This might show a red flag for comments who merely comment below a story without having read the full story. I think this behavior is often leading to the dangerous spread of fake news as more and more users rely on the correctness of this comment.
- AI Fact Check: An AI might be used to fact check every single sentence in a given text. The AI might take a given sentence and check it by matching the written context with billions of web pages, books, research articles, patents, judicial decisions and so on. If the written sentence is not in accordance with any trustworthy source, the AI will immediately downgrade the trustworthiness index.
We have the technologies to implement such tools. Now it is about time for entrepreneurs and intrapreneurs to build such a tool for the manhood. However, we must make sure to do not forget our critical thinking abilities.
What do you think? Is it about time to invent a trustworthiness index?