Date of Award

Spring 5-2023

Author's School

McKelvey School of Engineering

Author's Department

Computer Science & Engineering

Degree Name

Master of Science (MS)

Degree Type



As Large language models (LLMs) become increasingly pervasive in various domains, it is crucial to ensure that their outputs adhere to societal values and ethical considerations. In this thesis, we investigate the alignment of ChatGPT, a recent state-of-the-art large language model developed by OpenAI, with societal values. Specifically, we define the problem of societal values of LLMs and assemble a representative collection of 7 datasets covering 4 topics related to societal values. In-context learning techniques are applied and appropriate prompts are designed. The performance of each dataset is measured using a standardized evaluation system focused on accuracy. We then display the results and provide an analysis of ChatGPT's alignment with societal values. We contribute to the development of a framework for evaluating the alignment of language models with societal values, providing insights into the ability of ChatGPT to align with societal values.


English (en)


Chenguang Wang, Computer Science & Engineering

Committee Members

Ning Zhang, William Yeoh