Montreal: Disinformation has been used in warfare and military strategy over time. But it is undeniably being intensified by the use of smart technologies and social media. This is because these communication technologies provide a relatively low-cost, low-barrier way to disseminate information basically anywhere.
The million-dollar question then is: Can this technologically produced problem of scale and reach also be solved using technology? Indeed, the continuous development of new technological solutions, such as artificial intelligence (AI), may provide part of the solution.
Technology companies and social media enterprises are working on the automatic detection of fake news through natural language processing, machine learning and network analysis. The idea is that an algorithm will identify information as “fake news,” and rank it lower to decrease the probability of users encountering it.
Repetition and exposure
From a psychological perspective, repeated exposure to the same piece of information makes it likelier for someone to believe it. When AI detects disinformation and reduces the frequency of its circulation, this can break the cycle of reinforced information consumption patterns. However, AI detection still remains unreliable.
First, current detection is based on the assessment of text (content) and its social network to determine its credibility. Despite determining the origin of the sources and the dissemination pattern of fake news, the fundamental problem lies within how AI verifies the actual nature of the content.
Theoretically speaking, if the amount of training data is sufficient, the AI-backed classification model would be able to interpret whether an article contains fake news or not. Yet the reality is that making such distinctions requires prior political, cultural and social knowledge, or common sense, which natural language processing algorithms still lack. In addition, fake news can be highly nuanced when it is deliberately altered to “appear as real news but containing false or manipulative information,” as a pre-print study shows.