To combat fake news many institutions are promoting projects that make way to artificial intelligence. AI takes up the charge to improve the quality of information made available for everyone.
FREMONT, CA: Professors in the early period combined collections of well-researched data from peers and colleagues, from the selected course textbooks to the notes gave rise to the syllabus. Teachers then used the data to deliver the lecturers in their classes where students took notes and were accountable for the data. Technology, alongside the internet has changed the earlier approach. Today, students are as much a part of the research team as the teacher or a professor. Any topic introduced by the educator will have heaps of data available on the internet.
Hoax or Reality
Many people identify that not everything on the internet is true or factually right. Some information is false, and other portions might be built on inductive leaps and unclear thinking. The examination of online content for its authenticity and checking the facts can take time and requires more in-depth analysis. Most sites appear real with the tabs for activities, sightings, FAQs, links, events, and the media with the images posted, but what seems credible is not always real. So, one must learn how to fact-check.
Fact-Checking Made Simple
Automation is taking the deductive reasoning out of fact-checking. Researchers have built algorithms that detect fake photos, content, and even videos. In time, as artificial intelligence is taking on accountability to eliminate the guesswork in fact-checking, phony news will soon be a thing of the past. To combat the plethora of data that has invaded the internet, and by default, the media, many educational institutions are promoting projects that explore ways in AI to improve the quality of information.
Fake news is like gossip that spreads too quickly than the truth, and it is harder to eliminate it. Many organizations admit that one cannot wholly depend on the AI for fact-checking. The artificial intelligence algorithms used to dig out false news are accurate only two-third of the time. Misleading data is more difficult to recognize because of the different variables in the algorithms used to decide how dependable a news source can be. With machine learning’s considerable experience in identifying misinformation, fake news, hoaxes, AI-fact checking will become more reliable and accurate in the coming days.