Bias in Text Generative Open AI

Abstract

The rise of text generation models, especially those powered by advanced deep learning architectures like Open AI’s GPT-3, has unquestionably transformed various natural language processing applications. However, these models have recently faced examination due to their inherent biases, often evident in the generated text. This paper critically examines the issue of bias in text generation models, exploring the challenges posed, the ethical implications it entails, and the potential strategies to mitigate bias. Firstly, we go through the causes of the origin of the bias, ways to minimize it, and mathematical representation of Bias.