Abstract

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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