ChatGPT 的出现:数据分析师工作轻松还是失业

A. Owolabi, Oluwaseyi Oluwadamilare Okunlola, E. Adewuyi, Janet Iyabo Idowu, Olasunkanmi James Oladapo
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引用次数: 0

摘要

事实证明,人工智能(AI)在教育、科学、工程、技术、医学等几乎所有领域都具有重要价值。尽管人工智能具有广泛的实用性,但由于其高度发达的能力,人们开始担心人工智能可能会取代工作岗位,这就是通常所说的 "神人效应"。ChatGPT 就是一款出色的人工智能产品,它是由美国一家开放式人工智能公司开发的聊天机器人,能够进行类似人类互动的对话。本研究探讨了 ChatGPT 在数据分析方面的优势和局限性,主要目的是评估 ChatGPT 是否会对数据分析师的工作构成威胁。我们模拟了一个计量经济学数据集,样本量为三十(30)个,由一个因变量和三个自变量组成。该数据集是有意生成的,存在多重共线性、异常值和异方差等问题。随后,对数据集进行了多重测试,以确认是否存在这些问题。然后使用 ChatGPT 3.5 和 4.0 版本分析数据,以检验该聊天机器人在执行数据分析方面的能力。ChatGPT 3.5 和 4.0 准确预测了分析模拟数据集的合适统计工具。两个版本的 ChatGPT 都强调了专业数据分析师的专业知识是必要的。虽然它们可以提供数据分析方面的指导,但由于它们只是人工智能模型,因此无法亲自进行分析。当数据分析师遇到困难时,ChatGPT 可以帮助解决下一步该怎么做的问题。但是,它们不应被视为做出统计决策的权威。因此,ChatGPT 不一定能取代数据分析师,但可以在他们遇到困难时提供有用的资源,从而使他们的工作更轻松。
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The advent of ChatGPT: Job Made Easy or Job Loss to Data Analysts
Artificial Intelligence (AI) has proven valuable in almost every field of endeavour, including education, sciences, engineering, technology, medical sciences, and numerous other areas of application. Despite its widespread usefulness, concerns have arisen about AI potentially displacing jobs due to its highly advanced capabilities, commonly called the "god-man effect." One remarkable AI product is ChatGPT, a Chatbot developed by an open AI company in the USA that is capable of engaging in conversations that resemble human interactions. This study explores the strengths and limitations of ChatGPT for data analysis, with the primary objective of assessing whether ChatGPT poses a threat to the job of data analysts. An econometric dataset with a sample size of thirty (30), which consists of one dependent variable and three independent variables, was simulated. The dataset was intentionally generated with issues like multicollinearity, outliers, and heteroscedasticity. Subsequently, multiple tests were conducted on the datasets to confirm the presence of these problems. The ChatGPT 3.5 and 4.0 versions were then used to analyse the data to examine this chatbot's prowess in performing data analysis. ChatGPT 3.5 and 4.0 accurately predicted the suitable statistical tool for analyzing the simulated datasets. Both versions of ChatGPT emphasized that the expertise of a professional data analyst would be necessary. While they could offer guidance on data analysis, they cannot perform the analysis themselves as they are solely AI models. ChatGPT can help with what to do next when a data analyst gets stuck. However, they should not be recognized as an authority in making statistical decisions. Therefore, ChatGPT may not replace data analysts but could make their job easier by serving as a helpful resource to turn to when they encounter challenges.
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