In a world increasingly saturated with information, it's becoming harder to tell fact from fiction, especially with the rise of sophisticated AI that can churn out convincing fake news articles. Researchers are tackling this challenge head-on, exploring how to equip people with the tools to identify AI-generated deception. A new study delves into the subtle markers that distinguish human-written news from AI-generated fakes. Researchers collected a massive dataset of 39,000 news articles, some written by humans and others by four different AI models with varying degrees of fakery. They developed a clever metric called Entropy-Shift Authorship Signature (ESAS) which analyzes word choice and sentence structure to pinpoint the telltale signs of AI authorship. The results are promising. Even a simple detection method using the ESAS metric achieves surprisingly high accuracy in spotting AI-generated articles. What's the secret sauce? Turns out, AI struggles with certain words and phrases. For example, AI uses the word "said" far less often than human writers. Similarly, certain POS tags, like apostrophes indicating possession, appear with different frequency in AI-generated text. By learning these patterns, readers can become more discerning consumers of online information, enhancing their skepticism towards suspicious articles and ultimately building greater trust in the news they consume. This research is just the beginning. Future investigations will explore how editing or manipulating AI-generated text affects its detectability, further refining the fight against misinformation.