navigating the reliability of ai as a reference in scientific manuscript writing: a case study on the central limit theorem

This study delves into the potential of artificial intelligence as a beneficial tool in various domains while advising caution against its unchecked utilization as a reference in composing intricate scientific texts. although ai shows promise in supporting research endeavors, its role in producing comprehensive scientific content demands careful consideration. the research assesses the suitability and readability of ai-generated responses to scientific queries, shedding light on scenarios where ai outputs may prove inadequate or inaccurate. specifically, we focus on the central limit theorem, one of the most renowned and widely applicable theorems in statistics. in pursuit of investigating this matter, we leveraged artificial intelligence to facilitate our research. subsequently, we scrutinized the outcomes derived from artificial intelligence through nonparametric analysis, leading us to question the dependability of ai in scientific writing endeavors.