One of the most powerful lessons I learned in seminary is that we actually do theology rather than simply accept it as passive recipients. In other words, theology is not a list of propositions that we must ascend to, but instead is birthed out of an informed experience of the Christian faith. Theology is not an extraction of principles from the Biblical text, instead it occurs in the battleground of life where the believer applies the biblical text to the context they are in. Scripture in itself was not neatly packaged truth that fell from heaven, but instead emerged from the experience of the faithful community first as Israel and then as the church.
So how can data analytics help us do theology? Before answering this question, let me first level-set view of what data analytics is and how it can be applied in this scenario. Data analytics is considered part of AI because it mimics how our brain gathers and absorbs information. This way, it help us understand the world around us. Through a disciplined approach, it collects, organizes and analyzes data. Data doesn’t always point to insights but often proves or disproves our preconceived ideas about the world. It acts as a gut check, a corroborating witness to reality, keeping us from getting lost in our biases. In an organizational environment, good data analytics produces intuitive dashboards, visuals and summaries that help us quickly understand our current state. For example, a simple upward sloping line can reveal a trend we can no longer ignore. In short, good data analytics is designed to make us stop and listen.
Doing theology entails a similar process of gathering, organizing and interpreting data. We gather different data points through the memory of experiences, books, articles, conversations and even observations. A good theologian should be a good reader of people. She should be good at asking questions, probing their soul and always attentively listening. Then this data is compared with knowledge accumulated from experience, reading and conversations with others. At that point, she is now ready to engage in prayer and reflection. This is where all this data is digested and the theologian imagine redemptive alternatives to the individual, a community or even a nation.
The process I described above already happens, at times unbeknownst to the theologian. Data analytics thinking therefore offers a powerful framework, where the theologian can observe the different stages of the process, refine its methods and delve deeper into knowing the people she serves. For example, as the theologian reflects on her data collection practices, she can ask questions like: Am I listening to a representative sample of my community or is my hearing limited to one group of people? Have I truly listened or did I introduce biases from my experience? Do I have good information about my community or do I need to research more? Is my reading of Scripture focused on a certain type of genre (letters, psalms or narrative) or is does it include all that Scripture can offer? By asking these questions, the theologian can evaluate her practices and make changes as necessary. This way, a data analytics framework can help the theologian listen better. As she stops to think about the process of gathering data, she can therefore become a better listener.
This blog only scratches the surface of how data analytics can help us do theology. As these disciplines enter into a dialogue, they challenge and shape one another. I will be further exploring the implications in future blogs. For now, suffice it to say that paying attention to the process of how to do theology is probably one of the first and most powerful applications that comes from this dialogue.
This then begs the question about how can theology inform data analytics. Can we do data analytics theologically? This is the topic for another blog.