Our limited attention potential leaves us over-saturated with content choices. We are drawn to headlines and titles that are more appealing and engaging. Sensationalism, emotional appeals and big claims lure us in, where some content gets more attention than others. This has already been a factor in tabloid news magazines, but now it's playing out online and being propagated much more easily.
Lies can spread farther, faster, deeper, and more broadly than the truth in some cases, as a recent investigation has shown. The top 1% of false or fake news reaches between 1000 and 100,000 people, while accurate news rarely gets above 1000. In a world with fake news that can more easily be spread through the Internet and social media, artificial intelligence is being summoned into the information war.
Reality Vertigo
A strategic prediction model suggests that by 2022 people will encounter more fake, inaccurate or false information than real, accurate or true information. Computer scientists are developing AI systems that can put out realistic-seeming information which is being called "reality vertigo", where they are generating content that most people have a hard time discerning is false or true. The balance between reality and unreality is twisting in vertigo.
Computer algorithms have been good at detecting spam in emails by looking at the subject and messages text to evaluate if it's a real person or not. AI systems have more complex algorithms now for looking at content online. They can filter content based on headline and text comparisons, as well as looking to see if similar articles from different news media have differing "facts" to identify suspicious websites.
Amplified Fake News
As much as the spread of fake news can be hindered with AI, it can also be amplified. A neural networks AI system can model the shape of lips and replace what someone says with falsified audio as well. All they need is an audio file and they can make Barack Obama say what they want, as shown here:
Fake Obama created using AI video tool - BBC News
Face2Face is another AI neural network that has been developed. It can take the facial movements of someone (input source) and replicate them onto the screen of anyone they choose (target actor), like Obama, Trump or Putin. It can work with any webcam and works in real-time. This video explains how they do it all:
Face2Face: Real time Face Capture and Manipulation - CVPR 2016 Explanation
Through RGB overlays, algorithms, and Artificial Intelligence it is possible to simulate another person's speech, face, facial movements/expressions, and mannerisms in real time.
We present a novel approach for real-time facial reenactment of a monocular target video sequence (e.g., Youtube video). The source sequence is also a monocular video stream, captured live with a commodity webcam. Our goal is to animate the facial expressions of the target video by a source actor and re-render the manipulated output video in a photo-realistic fashion. To this end, we first address the under-constrained problem of facial identity recovery from monocular video by non-rigid model-based bundling. At run time, we track facial expressions of both source and target video using a dense photometric consistency measure. Reenactment is then achieved by fast and efficient deformation transfer between source and target. The mouth interior that best matches the re-targeted expression is retrieved from the target sequence and warped to produce an accurate fit. Finally, we convincingly re-render the synthesized target face on top of the corresponding video stream such that it seamlessly blends with the real-world illumination. We demonstrate our method in a live setup, where Youtube videos are reenacted in real time.
"Deepfakes" is a new term for altering videos and photos. One person's face is replaced with another seamlessly, which has been used to make celebrities look like they said something they never did, or be in "faceswap" porn. This could make spotting fake news even harder than previously done with fact checking and refuting false claims. What people see they will tend to believe, and try to get someone to dismiss what they have seen, even if it's fake.
Consciousness is the Cure
As technology gets more sophisticated and able to create better fake news, we can see more doubt cast on news media and governments, creating further divides as people fall for various lies that come from anywhere. The real solution to fake news is to develop our capacities of consciousness, of being more intelligent and thinking critically about the information we are exposed to.
One place to start is in our social media platforms. Instead of sharing news stories based on headlines alone that stir us up and motivate us to share with others, we should read them first. This can prevent false information from going viral more quickly. And if we read them, we should check if the information is credible or what source it comes from. Some sites are really bogus and just put out false information that is more easily detected that the current article you may be reading.
The more we are able to gather real and true information, the better we will be at detecting it. Our ability to filter our obvious fake news will get better. But for the fake videos and photos, we may have to rethink how much we can trust what we see. Seeing is believing, but believing isn't a de facto truth. Trust is a proxy for truth. Videos used to be relied upon for proof, but we may be seeing a dramatic shift in how much we can trust video sources for anything in our future.
References:
- The spread of true and false news online
- Gartner Top Strategic Predictions for 2018 and Beyond
- How artificial intelligence can detect – and create – fake news
- Go to YouTube and See Me Tomorrow: The Role of Social Media in Managing Chronic Conditions
- AI will solve Facebook’s most vexing problems, Mark Zuckerberg says. Just don’t ask when or how
- Astronomers explore uses for AI-generated images
- Watch Jordan Peele use AI to make Barack Obama deliver a PSA about fake news
- Go to YouTube and See Me Tomorrow: The Role of Social Media in Managing Chronic Conditions
- Fake News Detection on Social Media: A Data Mining Perspective
- Tracing Fake-News Footprints: Characterizing Social Media Messages by How They Propagate
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