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Expectations vs. reality: AI language models and human behavior One of the distinguishing features of Large Language Models (LLMs) is their ability to handle diverse tasks. For instance, a model that helps a graduate student draft an email is equally capable of assisting medical professionals in cancer diagnosis. The extensive a p plicability of these models  poses a challenge in systematic evaluation as creating a com prehensive benchmark dataset to test every  possible query is im practical. MIT researchers  presented a novel a p proach in a new  pa per on the arXiv  pre print server. They contend that because humans decide the deployment of large language models, assessment must include an examination of how peo ple form beliefs regarding their abilities. For exam ple, the graduate student must judge the model's hel pfulness in drafting an email, and the clinician must determine which scenarios are best suited for the model's a p plication. Building on this...