How Factually Accurate is GPT-3? A Focused Case Study on Helping Malaysia’s B40s Through e-Commerce

Abstract

GPT-3 (Generative Pre-trained Transformer 3) is an advanced natural language processing model utilizing unsupervised learning to generate sophisticated human-like text. GPT-3 has been lauded for its potential to revolutionize the field of natural language processing, with its capacity to generate a variety of text with a high degree of fluency and accuracy. We examine the ability of GPT-3’s to produce text related to a focused subject matter: alleviating poverty in Malaysia through e-Commerce. We especially examine GPT-3’s ability to produce factual responses within this narrow context. It was discovered that GPT-3 could produce plausible statements, albeit some of them being factually debatable or incorrect due to how its training data was sourced. We also discuss how GPT-3 could be used unscrupulously to either produce academic-sounding responses that appear to be a product of research, but possibly untrue or inaccurate and discuss its potential ramifications (such as propaganda and disinformation). We end the paper with some suggestions to the brilliant team at OpenAI to further improve GPT-3 for the advancement of humankind.