Machine Learning vs. Artificial Intelligence
When talking about Artificial Intelligence, we can’t go around the fact that many people don’t truly understand the meaning of the term. More often than not artificial intelligence is used as a synonym for machine learning algorithms, and sometimes people refer to both as parallel advancements. The terms are also often deliberately confused in order to create additional excitement for advertising and sales purposes.
In fact, machine learning is only a branch of artificial intelligence. Machine learning is the field of developing computer algorithms that learn and improve automatically through experience. Artificial intelligence, on the other hand, is a very broad term that encompasses all the science of making computers perform the tasks that, until recently, required human intelligence. This means the term, “artificial intelligence,” includes different technologies that change over time.
Linguistic Features
One of the most reliable ways to detect fake news is to examine the common linguistic features across various sources’ articles. Those features include sentiment, complexity, and structure. Another common feature of fake news is a sensational headline. As headlines are the key to capture the attention of the audience, they have become a tool of attracting the interest from a wider population. Fake news almost always uses a sensational headline since they are only partially limited by actual facts.
There is already a type of AI (machine learning algorithms) widely deployed to fight spam email. Those algorithms analyze the text and determine if the email comes from a genuine person or if it is a mass-distributed message, designed to sell something or spread a political message. Considering some aspects of artificial intelligence make it possible to learn from past behaviors, the best approach is to train the machine learning algorithms to improve based on past articles already proven to be fake.
Weighing the Facts
Weighing the facts that the news is relying on is another important aspect. Artificial intelligence has developed to a stage where it is possible to examine the facts in a certain article (a Natural Language Processing engine can be used to go through the headline and the subject of the story, including the geolocation) and compare them with the facts from other sites covering the same subject. After this is done, the facts can be weighed against each other, which adds another dimension to the credibility of the story.
In crypto weighing the facts could also backfire, because there are many cases when the initial report comes from within a crypto project. When the news is spread the untrue parts of the story are also replicated. That’s why it is important to add another crucial aspect of news assessment – keeping a good track of source reputation.
Source Reputation
Focusing on the news sources themselves is a very important aspect of assessing the news. Machine learning algorithms have already been successful in examining the accuracy and political bias of news sources. Artificial intelligence can also be used to find correlations with a source’s Wikipedia page, which can be examined and rated based on various criteria. For example, a longer Wikipedia description of a source is associated with a higher credibility. Furthermore, words like “extreme” or “conspiracy” are often used when describing an unreliable source.
Human Intelligence is Still Crucial
Humans will still play an important role in the process of news assessment. There are complex cases where humans will have to work together with technology to efficiently address the situation. The evolution of artificial intelligence should reduce the number of such situations, but it is likely human intervention will still be required for quite some time.
Audience awareness and critical thinking are additional aspects of human intelligence. People should be encouraged to always investigate information rather than simply sharing it. Sharing means giving credibility to an article. People who know you personally and trust you will more likely believe the shared post and won’t necessarily question its factuality.
Developing a Solution
All in all, artificial intelligence can be a very useful tool for detecting and exposing fake news and articles based on misconceptions. This is the reason why we are developing a platform that gathers, evaluates, and enriches crypto news and information. We are constantly improving the real-time accuracy of news evaluation using the combination of community knowledge and artificial intelligence.
If you are interested in learning more about AI and fake news, we invite you to check out the full article, available on our website. Check out our blog for other useful information that will help you out with your contribution decisions. Together, we know more!
