How would artificial intelligence be useful for theological study? Yuechen Hou, a Ph.D. candidate from Olivet Institute of Technology (OIT), attempts to answer this question with his research project.

The study of theology typically involves analyzing a huge amount of scholarly and biblical texts. Many theologians conduct their studies primarily using manual techniques without much aid from the computer. However, with the recent advancement of deep learning-based natural language processing technology, it is possible that theological analysis can be automated and more efficient.

"The goal of my project is to explore a new avenue in theological study by automating the analysis of a massive body of documents," explained Hou during his panel presentation.

"The desired result is to identify the theological standpoint of a person or an organization by analyzing an article, a sermon, a book, or a research paper. Its application includes building IR (information retrieval) systems, recommender systems, personalization systems, and automated classifiers in the Christian field," added Hou.

Professor Thomas Kong provided feedback and guidance for this project regarding project positioning, its relevance to text classification, and relating models including FastText, Seq2seq with attention, Transformer, Autoencoder, and Bert. Kong also suggested the proper data preparation and evaluation method.

Hou's project is a unique take on applying natural language processing technology in theological study. It has a huge significance in the research of using artificial intelligence in the field of theology. OIT aims to publish this research project next year.