BOOM

Trending Searches

    SUPPORT
    BOOM

    Trending News

      • Fact Check 
        • Fast Check
        • Politics
        • Business
        • Entertainment
        • Social
        • Sports
        • World
      • Law
      • Explainers
      • News 
        • All News
      • Decode 
        • Impact
        • Scamcheck
        • Life
        • Voices
      • Media Buddhi 
        • Digital Buddhi
        • Senior Citizens
        • Videos
      • Web Stories
      • BOOM Research
      • BOOM Labs
      • Deepfake Tracker
      • Videos 
        • Facts Neeti
      • Home-icon
        Home
      • About Us-icon
        About Us
      • Authors-icon
        Authors
      • Team-icon
        Team
      • Careers-icon
        Careers
      • Internship-icon
        Internship
      • Contact Us-icon
        Contact Us
      • Methodology-icon
        Methodology
      • Correction Policy-icon
        Correction Policy
      • Non-Partnership Policy-icon
        Non-Partnership Policy
      • Cookie Policy-icon
        Cookie Policy
      • Grievance Redressal-icon
        Grievance Redressal
      • Republishing Guidelines-icon
        Republishing Guidelines
      • Fact Check-icon
        Fact Check
        Fast Check
        Politics
        Business
        Entertainment
        Social
        Sports
        World
      • Law-icon
        Law
      • Explainers-icon
        Explainers
      • News-icon
        News
        All News
      • Decode-icon
        Decode
        Impact
        Scamcheck
        Life
        Voices
      • Media Buddhi-icon
        Media Buddhi
        Digital Buddhi
        Senior Citizens
        Videos
      • Web Stories-icon
        Web Stories
      • BOOM Research-icon
        BOOM Research
      • BOOM Labs-icon
        BOOM Labs
      • Deepfake Tracker-icon
        Deepfake Tracker
      • Videos-icon
        Videos
        Facts Neeti
      Trending Tags
      TRENDING
      • #Operation Sindoor
      • #Pahalgam Terror Attack
      • #Narendra Modi
      • #Rahul Gandhi
      • #Waqf Amendment Bill
      • #Arvind Kejriwal
      • #Deepfake
      • #Artificial Intelligence
      • Home
      • Fact Check
      • How Artificial Intelligence Can...
      Fact Check

      How Artificial Intelligence Can Detect – And Create – Fake News

      By - The Conversation |
      Published -  5 May 2018 12:26 PM IST
    • Boomlive

      When Mark Zuckerberg told Congress Facebook would use artificial intelligence to detect fake news posted on the social media site, he wasn’t particularly specific about what that meant. Given my own work using image and video analytics, I suggest the company should be careful. Despite some basic potential flaws, AI can be a useful tool for spotting online propaganda – but it can also be startlingly good at creating misleading material.

      This sure looks like Barack Obama saying some things he probably would never say.

      Researchers already know that online fake news spreads much more quickly and more widely than real news. My research has similarly found that online posts with fake medical information get more views, comments and likes than those with accurate medical content. In an online world where viewers have limited attention and are saturated with content choices, it often appears as though fake information is more appealing or engaging to viewers.

      The problem is getting worse: By 2022, people in developed economies could be encountering more fake news than real information. This could bring about a phenomenon researchers have dubbed “reality vertigo” – in which computers can generate such convincing content that regular people may have a hard time figuring out what’s true anymore.

      Detecting falsehood

      Machine learning algorithms, one type of AI, have been successful for decades fighting spam email, by analyzing messages’ text and determining how likely it is that a particular message is a real communication from an actual person – or a mass-distributed solicitation for pharmaceuticals or claim of a long-lost fortune.

      Building on this type of text analysis in spam-fighting, AI systems can evaluate how well a post’s text, or a headline, compares with the actual content of an article someone is sharing online. Another method could examine similar articles to see whether other news media have differing facts. Similar systems can identify specific accounts and source websites that spread fake news.

      An endless cycle

      However, those methods assume the people who spread fake news don’t change their approaches. They often shift tactics, manipulating the content of fake posts in efforts to make them look more authentic.

      Using AI to evaluate information can also expose – and amplify – certain biases in society. This can relate to gender, racial background or neighborhood stereotypes. It can even have political consequences, potentially restricting expression of particular viewpoints. For example, YouTube has cut off advertising from certain types of video channels, costing their creators money.

      Context is also key. Words’ meanings can change over time. And the same word can mean different things on liberal sites and conservative ones. For example, a post with the terms “WikiLeaks” and “DNC” on a more liberal site could be more likely to be news, while on a conservative site it could refer to a particular set of conspiracy theories.

      Using AI to make fake news

      The biggest challenge, however, of using AI to detect fake news is that it puts technology in an arms race with itself. Machine learning systems are already proving spookily capable at creating what are being called “deepfakes” – photos and videos that realistically replace one person’s face with another, to make it appear that, for example, a celebrity was photographed in a revealing pose or a public figure is saying things he’d never actually say. Even smartphone apps are capable of this sort of substitution – which makes this technology available to just about anyone, even without Hollywood-level video editing skills.

      Researchers are already preparing to use AI to identify these AI-created fakes. For example, techniques for video magnification can detect changes in human pulse that would establish whether a person in a video is real or computer-generated. But both fakers and fake-detectors will get better. Some fakes could become so sophisticated that they become very hard to rebut or dismiss – unlike earlier generations of fakes, which used simple language and made easily refuted claims.

      Human intelligence is the real key

      The best way to combat the spread of fake news may be to depend on people. The societal consequences of fake news – greater political polarization, increased partisanship, and eroded trust in mainstream media and government – are significant. If more people knew the stakes were that high, they might be more wary of information, particularly if it is more emotionally based, because that’s an effective way to get people’s attention.

      When someone sees an enraging post, that person would do better to investigate the information, rather than sharing it immediately. The act of sharing also lends credibility to a post: When other people see it, they register that it was shared by someone they know and presumably trust at least a bit, and are less likely to notice whether the original source is questionable.

      Social media sites like YouTube and Facebook could voluntarily decide to label their content, showing clearly whether an item purporting to be news is verified by a reputable source. Zuckerberg told Congress he wants to mobilize the “community” of Facebook users to direct his company’s algorithms. Facebook could crowd-source verification efforts. Wikipedia also offers a model, of dedicated volunteers who track and verify information.

      Facebook could use its partnerships with news organizations and volunteers to train AI, continually tweaking the system to respond to propagandists’ changes in topics and tactics. This won’t catch every piece of news posted online, but it would make it easier for large numbers of people to tell fact from fake. That could reduce the chances that fictional and misleading stories would become popular online.

      Reassuringly, people who have some exposure to accurate news are better at distinguishing between real and fake information. The key is to make sure that at least some of what people see online is, in fact, true.

      This article was first published on theconversation.com

      Tags

      Barack Obamadetecting falsehoodfake newsGlobalinformationtechnologyFacebook
      Read Full Article
      Next Story
      Our website is made possible by displaying online advertisements to our visitors.
      Please consider supporting us by disabling your ad blocker. Please reload after ad blocker is disabled.
      X

      Subscribe to BOOM Newsletters

      👉 No spam, no paywall — but verified insights.

      Please enter a Email Address
      Subscribe for free!

      Stay Ahead of Misinformation!

      Please enter a Email Address
      Subscribe Now🛡️ 100% Privacy Protected | No Spam, Just Facts
      By subscribing, you agree with the Terms & conditions and Privacy Policy connected to the offer

      Thank you for subscribing!

      You’re now part of the BOOM community.

      Or, Subscribe to receive latest news via email
      Subscribed Successfully...
      Copy HTMLHTML is copied!
      There's no data to copy!