A 2016 Stanford report found that children usually can’t tell the difference between fake and real news. According to the study, “most of [the] participants in our study believed fake news was actually real when they read it because of its persuasive nature. In other words, they were able to recognize a story as false but they were unable to distinguish whether or not it was true."
Fake news is something that we can see in the headlines, and it's something that has been around for a long time. But now, AI tools are being developed to help us fight fake news.
This means that there aren't only big implications for security: these new technologies could also have some negative side effects, particularly when it comes to free speech.
So how do we know what those side effects are? How do we make sure that we're protecting ourselves while also allowing companies like Facebook access to our data so they can help us distinguish real news from fake?
It all starts with understanding how AI works and how its applications will affect our lives as consumers and citizens of this internet age going forward—here's what you need to know about these questions first before letting AI into your life again.
Fake News is a Huge Problem
Fake news is a huge problem. It can be used to influence people, manipulate them, spread false information, and even spread propaganda.
It's not just a few rogue websites with poor SEO, but rather a more sophisticated, coordinated attack that spreads across multiple platforms and reaches millions of people.
This is what happened during the 2016 election when an army of Russian-backed trolls flooded social media with fake stories about Hillary Clinton and Democratic candidates. It was so successful that even mainstream media outlets fell for it.
It's not just about spreading misinformation, but also about amplifying existing biases by showing people what they want to see. Fake news does this by convincing your brain that it's true based on how it's presented to you — even if you know better.
Fake news has become so prevalent that it even has its own name: "post-truth." This term refers to political statements that are not based on facts or reality. The problem is that post-truth statements can be dangerous because they're designed to achieve an emotional response, such as fear or anger.
There's no doubt that fake news has affected U.S. politics in recent years. In fact, one study found that 86% of Americans believe fake stories are sometimes true—a level much higher than any other country surveyed by researchers at Oxford University's Computational Propaganda Project (C2).
AI Tools are Already being Developed to Help People Detect Fake News
AI tools are already being developed to help people detect fake news. Many companies are developing an algorithm that can identify and predict the likelihood of a story being true or false based on its text and other factors.
One of the most important factors in spotting a fake news story is checking its source, but this can be difficult when we're so used to getting our information from social media channels like Facebook or Twitter.
Fake blogs posing as credible new sites have also been able to slip by Google's algorithms before because they have never been published on sites with high domain authority. These blogs could also produce posts with links back to legitimate content on other domains as a way of deflecting suspicion.
Fake blog creators were also savvy enough to game popular keywords in headlines and meta tags. But all that has changed with the evolution of AI-specifically natural language processing (NLP) techniques.
New deep learning techniques provide computers an uncanny ability to read the text for meaning, allowing them access to text previously unsearchable by traditional means. These advances allow NLP software programs to scan articles on websites using advanced reading comprehension techniques.
Computers can now analyze articles' syntax structure, meaning graphs can detect whether or not a website displays signs of bias or falsehoods-including fake news articles created purely for financial gain.
AI can be Used to Pinpoint Fake News
AI is able to detect fake news by analyzing the text of a given article, comparing it with other articles on the same topic, and identifying changes in style or grammar that indicate the author may have been influenced by someone else's writing style.
AI also uses statistical analysis to determine if an article has been copied from another source; this allows it to differentiate between plagiarism and imitation in order for humans to make accurate judgments about whether or not something is actually false.
The most common applications of AI-based detection techniques involve using machine learning algorithms that allow computers themselves to learn how they work together: when combined together over time these algorithms become more sophisticated than any one individual could ever hope for—and thus capable of detecting all kinds of falsehoods across every platform imaginable (including social media).
But this Solution itself could have some Negative Side Effects, Particularly when it comes to Free Speech
But this solution itself could have some negative side effects, particularly when it comes to free speech. If AI is used to fight fake news, then people who are publishing real news will also be silenced.
And if you're publishing content that isn't considered "news," such as personal essays or opinion pieces, you could find yourself censored by algorithms designed by humans rather than machines.
AI is an area of technology that has the potential to be used in fighting fake news. In fact, it's already being used in this way by some companies and organizations. For example, Facebook uses AI to detect fake accounts on its platform, while Google and Microsoft are also experimenting with using AI for detecting clickbait websites.
While the current state of AI is still fairly limited when compared to human intelligence, there are some serious implications for security stemming from the potential for AI tools like these:
- They could help identify fake news articles more easily than humans do (which could lead them down a path where they don't realize what they're reading isn't factual).
- If people get accustomed to seeing things like this pop up as soon as they open their browser or turn on their computer screen—and then don't question them at all—it'll become part of our daily lives without us even knowing it!
- They could be used to identify security threats that humans may not have noticed. The technology is already being applied in some cases, as one example shows how an AI tool can be used in conjunction with human analysts to help detect malicious activity more quickly than either could alone.
- They could replace jobs for people who perform repetitive tasks (like scanning social media for content or reviewing data). This will likely happen sooner rather than later, and there's no doubt that it'll cause some problems for the individuals whose jobs are replaced.
The First Thing to Know about Fake News is that old-fashioned Reporting Standards are Still Failing Us
A recent study from Stanford University showed that fake news stories were shared more often than the top 20 news stories from well-known media sources, and were actually more widely believed than the truth.
Fake news is a problem because people are being misled, and we need to know how to tell the difference between real and fake news. We also need to be able to spot fake news when it pops up on our screens or devices, which means that AI tools will be instrumental in helping us do so.
Why should we give Companies Access to our Data so they can help us Distinguish Real News from Fake?
You've probably already given Facebook access to your data, but you may be surprised to learn that the company was able to use it in ways you hadn't intended.
Facebook has been collecting and sharing information about users' online activity with third parties since its inception. The company's privacy policy states that "Facebook may receive information" through cookies, web beacons, and other similar technologies—information such as what pages you have visited or how often you log in—and it is able to share this data with other companies for marketing purposes (as well as for research).
But what most people don't know is that companies like Facebook also collect data from social networks like Twitter or Instagram where users share links to news articles with friends or family members who might find them useful.
In some cases these links are actually genuine pieces of journalism; others may simply be clickbait titles designed only to attract attention while delivering none of its promised content.
Bottom Line
We need to know what the side effects of using AI on the internet will be before we let it take off.
It’s important that we understand what these side effects are, because they may not be obvious or easy to detect.
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