To illustrate the impact of language models on established fake news generating tactics, the news-rating group NewsGuard found evidence of Russian state media using AI-generated chatbot screenshots to advance false claims.
In a daily news segment posted on Mar 28, 2023, RT reported that “American-made AI-powered search engine ChatGPT lists the 2014 Maidan uprising in Ukraine as a coup that Washington had a hand in, among others. That’s in stark contrast to the US narrative that it doesn’t interfere in other countries”.
Additionally, a report published by NewsGuard last month found an alarming 217 (and counting) AI-generated news and information sites that were operating with little to no human oversight, showcasing the sheer scale of which LLMs can generate false narratives.
Should generative AI be deployed for hostile information campaigns from organisations with significant resources at their disposal, then we would certainly be presented with fake news at an unprecedented scale.
Despite the dangers, there lies a glimmer of hope that LLMs can be employed as tools to assist fact-checkers in their crucial work. The vast amount of information available to LLMs can be harnessed by independent fact-checkers to cross-reference claims, statements, and articles against known sources of truth.
By leveraging the speed and efficiency of these models, fact-checkers can potentially identify and debunk falsehoods with greater accuracy and at a faster rate, helping to combat the rapid spread of fake news in the digital age.
TRADITIONAL FACT-CHECKERS STILL NECESSARY
As we contemplate the potential role of LLMs in fact-checking, it is crucial to acknowledge the indispensable role of traditional fact-checkers. Human fact-checkers possess critical thinking abilities, subject matter expertise, and the capacity to discern shades of truth. They can delve into complex issues, cross-reference multiple sources, and evaluate the credibility of claims based on contextual understanding.
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