Large language models (LLMs) are rapidly becoming integrated into our daily lives, from chatbots to educational tools. But as these AI systems become more sophisticated, a fascinating question arises: do they have personalities? New research introduces a groundbreaking system called the Language Model Linguistic Personality Assessment (LMLPA), designed to explore the distinct linguistic personalities of LLMs. Unlike traditional personality tests built for humans, LMLPA focuses on the nuances of language produced by AI, analyzing patterns and styles to quantify personality traits. This innovative approach moves beyond simply asking an LLM about its personality, as LLMs can be susceptible to biases in traditional questionnaires. Instead, LMLPA uses open-ended questions, prompting the LLM to explain its reasoning and providing richer, more reliable data. An AI “rater” then analyzes these responses, converting textual information into numerical scores. This allows researchers to compare and contrast the personalities of different LLMs, offering a fascinating glimpse into how these systems process and generate language. Initial findings reveal that LLMs do exhibit distinct and measurable linguistic personalities, although with some intriguing overlaps and quirks. For instance, LLMs seem programmed to avoid expressing extreme personality traits, perhaps as a safeguard against generating overly negative or harmful language. This research opens up exciting new possibilities for understanding and interacting with AI. By quantifying LLM personalities, we can tailor their communication styles for specific applications. Imagine educational AI tutors with encouraging, open personalities, or customer service bots with high agreeableness scores. This is a significant step towards creating more human-centered AI experiences, paving the way for richer, more personalized interactions between humans and machines.