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The spread of misinformation through deepfakes, document manipulation, and false narration is quite common on the internet today.
The term “fake news” has surfaced not only in journalism, but also in other supposedly credible sources. AI and computer vision must be used sensibly to check the authenticity of information on the web.
We are going through a dangerous phase in our history. Since the dawn of mankind, there haven’t been many instances of a deadly global pandemic, political and social unrest in different parts of the world, and the looming, inevitable threat of climate change at the same time. Unfortunately, along with these things, another threat to humanity has re-emerged over the past decade – widespread misinformation.
Although it has been a near continuous presence in the world for several centuries, misinformation in its current online avatar is a dangerous tool, especially during a pandemic. The World Health Organization (WHO) and other governing bodies have repeatedly urged caution when consuming information on the internet about drugs and treatments for COVID-19. Accordingly, individuals can report any false information on the Internet related to the disease to the WHO. The disseminators of misinformation intend to create discord among the masses and influence their opinions to go along with their plans. Most of the time, misinformation is used to sow prejudice and hatred among people. Unfortunately, misinformation is easily digested by people as, in many cases, it is a premade confirmation of their existing prejudices and false opinions. These days, misinformation is widespread in journalism and other fields. In fact, the spread of misinformation can be compared to that of a virus. The misinformation “infodemia” mutates and travels on social media platforms and is absorbed by thousands of people, knowingly or unknowingly. Ironically, AI is one of the reasons misinformation can spread as quickly and efficiently as it does today. The misinformation generators can use cutting-edge technology to spread their false theories to the public and make them appear to the masses as the truth of the gospel.
At the same time, AI and its component computer vision can also be used to eliminate misinformation from the web or at least provide a verification screen so that people can verify the authenticity of information online before digesting it. Here are a few tools we can use to address the rampant spread of misinformation:
Big data and AI against fake news
The problem of spreading misinformation can be effectively addressed using AI-powered tools. The main purpose of using automated tools is so that human intervention is minimized and the process can be carried out with no (or minimal) involvement of partial opinions in the mix.
Organizations like Google use special evaluation tools and methods to evaluate websites for their content based on the correctness of the information presented. The accuracy of the data published on news websites and other information providers on the Internet is the measure of the priority of websites in search results. According to Google, their algorithms set accuracy ratings for each website based on the true authenticity of their content. The use of third party links, plagiarism, and other factors play an important role in assigning the ranks to any website. Google’s efforts to contain misinformation on the internet have led other organizations to pursue the same cause. There are several AI and big data powered tools that are eliminating misinformation online in this day and age. One such tool is called a cross check. In 2017, the tool, supported by Google and Facebook, was used to clean up misinformation on the internet in the run-up to the French presidential elections held at this stage. At that time, the French news media had introduced Crosscheck to detect and eliminate or expose false information reports about the elections on the Internet. According to First Draft News, the media organization that developed Crosscheck, the tool was designed to find, review and publish election-related content on the Internet. Crosscheck included or was supported by other tools and components that made its operation easier:
a) CrowdTangle
CrowdTangle supported Crosscheck in discovering and closely following the developing content in connection with the elections in real time.
b) Google trends
Google made its tool available to monitor online searches related to the elections.
c) listening
A tool for gathering public questions about the elections. Once collected, Hearken would then, in its role as an engagement management system, provide easy-to-understand answers.
d) Check
The check tool was used to check information. The correctness of online information was verified by comparing it with huge amounts of (verified, correct) information in Crosscheck’s databases.
e) tip
This tool was used to predict viral incidents and events using big data and predictive analytics.
f) Le Décodex
Another big data powered tool that constantly saves inbound information from 600+ news and media websites. The information has been classified according to its usefulness and accuracy.
In addition, a tool invested by the EU, Pheme, assisted the French media in assessing the accuracy of content and questions found online related to the major elections. Developed in collaboration with other EU technology and information partners, Pheme leveraged big data, natural language processing and analysis, data mining, social network analysis and data visualization to eliminate misinformation from the web. As we can see from the examples from Google and Crosscheck, AI and Big Data are crucial to understanding how exactly something is published on the internet. These tools should be used by governments around the world and international bodies to expose and eliminate (or at least reduce) misinformation, lies, and baseless conspiracy theories on the internet through features such as email verification, social media analytics, and much more.
Computer vision to ensure the accuracy of visual data
Manipulated visual data on social media platforms should also be classified as misinformation. Advanced computer vision and tools derived from it can be used to eliminate incorrect information from these types of data. For example, Facebook uses ObjectDNA among other tools and technologies for this purpose. According to Facebook, the ObjectDNA laser focuses on specifics within an image (while overlooking background echoes or noise) to measure the accuracy of the information it contains, unlike most standard computer vision systems. These specifics then allow the website administrators to mark any image as inappropriate or inaccurate if found after review. The technology uses other tagged images for reference, even if two images have vast differences between them. Facebook also uses LASER, a word processing tool that embeds multiple languages ​​to find semantic similarities or differences in sentences in visual data. This means that Facebook’s tools work with both images and texts.
In addition to regular social media posts, deepfakes can also be classified under the brackets of false information disseminating elements. Problematic deepfakes have the power to spread misinformation among the masses on an industrial scale because of their impressive bogus capabilities. Nowadays, deepfakes can be dealt with using certain tools, including blockchain systems. As we shall see later, the people who consume this type of information need to be aware of the possibilities of manipulating visual data. To definitely deal with deepfakes, Facebook put together an AI Red team as well as a detection AI model with eight deep learning neural networks. The models were trained with unique data sets so that they can intuitively detect deepfakes, at least the controversial ones, and identify new ones in real time using advanced computer-aided data synthesis measures. Therefore, whenever the system encounters a brand new type of deepfake, it looks for similar ones to train its AI models for.
Using the example of Facebook, we can see that visual data such as social media content and deepfakes can be efficiently scanned in order to nip misinformation in the bud in such places.
Education and awareness for open minds
Most importantly, users need to educate themselves through various sources so as not to fall for misinformation on the Internet. Simple things such as B. not going to seedy, illegal websites, checking messages and posts before forwarding them and others can stop misinformation.
Big data, computer vision, and AI have come a long way in the last decade, but basic knowledge of what is right and wrong cannot be guaranteed by technology alone. Users must show curiosity to get to the bottom of information before they believe and act on it. Most importantly, nothing found on the internet should ever be taken at face value. Check three or four sources for accuracy (the more the better) and you’re good to go. As they say, take everything with a pinch of salt.
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