Problems AI Can Solve in Ministry

Internal & External Applications

Ministry leaders might think about applying AI in two different ways—internally and/or externally. Internally, AI could be used within the organization in various processes or in research. In this case, AI may supplement (and occasionally displace) existing roles within the organization and change how various people and departments relate to one another. Externally, organizations could use AI to deliver goods or services to their target population. In this case, AI will supplement how the organization fulfills its mandate and will alter how the organization relates to those it serves.

Chatbots

Some organizations are exploring how they might use AI-driven chatbots to engage people who are interested in learning more about Christianity. In many cases, organizations are using social media to elicit interest, and they receive more responses than their staff and volunteers can handle. Indeed, "the harvest is plentiful," and some see chatbots as a way to scale up the work of the few, so that true seekers can be engaged meaningfully.

Missiology Research

Christian ministries have published significant bodies of missiological research that Natural Language Processing (NLP), a subset of AI, could summarize and deliver to executives seeking to learn and develop new strategies. How might this research be collected and made available to NLP systems, and what outputs would be most beneficial to ministry leaders?

Low-Resource Languages

Many of the languages of UPGs have few texts on which to train an NLP. These limited resources pose a challenge for AI-enabled Scripture translation. This article provides an overview of low-resource machine translation, current solutions and remaining needs. Facebook has also done research and resourcing for low-resource machine translation.

At a recent Missional AI summit focused on NLP, ad hoc teams brainstormed solutions to the low-resource problem. One popular idea involved recording stories from existing low-resource language speakers as a way of gathering large bodies of text for use in training NLP systems.