Now more than ever, AI has the potential to lift the weight of leadership off your shoulders. But there is a burning question facing church leaders today: How can churches use AI ethically?
It's been a little over a year since Chat GPT launched, and the conversation is only getting faster. If you're like most pastors, you've probably felt AI knocking on your door.
AI may seem new, unclear, and mysterious in many ways, but the truth is that it will be integrated into every aspect of your life.
What has been clear throughout history is that people and ministries that thoughtfully adopt new technologies thrive. We can ignore this new technology, or we can do everything we can to learn more.
This is a guest post by Josh Burnett, CEO of Church.Tech.
7 Essential AI Terms Pastors Need to Know
These seven terms will give you a basic understanding of AI, how it works, and what sets one tool apart from another. This will allow AI to make more informed decisions about where it might be a good fit for ministry.
1. Artificial Intelligence
Artificial intelligence (AI) is a branch of computer science that focuses on creating computer systems and algorithms that can perform tasks that typically require human intelligence, such as understanding natural language, recognizing patterns, making decisions, and learning from data.
Predictive AI
Like tools that predict the weather or predict the end of a Google search, predictive AI has been commonly used for years. It works by “studying” past weather patterns or searches (for example) to predict what will happen next.
natural language processing
Like autocorrect and text support on your phone. This gives machines the ability to “understand” speech and language in a way that humans can.
It can generally be used to summarize large amounts of text.
Generating AI
Like ChatGPT! This AI can produce new content by creating new content and ideas such as stories, images, videos, and music.
2. Training data
AI training data is exactly what it sounds like: a set of data used to “train” an AI learning model.
A machine is given inputs and corresponding outputs. After consuming all this data, AI can reliably predict future patterns.
The goal is to turn data into meaningful knowledge that can be used to make decisions, predict, and understand people.
A variety of data sets are used to train AI tools on specific topics. For pastors and church leaders, this may mean the Bible and other faith-based data sets.
For example, ChatGPT may not be the best fit for pastors because it is trained on data from a variety of sources, such as the King James Bible, Quran, Torah, and other general online content. This means that they may produce content that does not serve the purposes of Christian pastors.
Or, AI tools designed specifically for faith leaders are trained on limited data sets. Church.Tech also uses pastors' sermons to create group guides, social clips, etc. That way, the material is sure to remain faithful to the pastor's unique message.
3. Algorithm
Algorithms are the rules and guidelines that AI systems use to analyze data and generate responses.
An algorithm is like a recipe or set of instructions for solving a problem or performing a task. Just as a recipe guides you to cook a specific dish, an algorithm guides a computer how to perform a specific task.
Computers use algorithms to perform a variety of tasks, from sorting data to playing games to recommending movies. A behind-the-scenes guide to ensuring things are done in an organized and effective manner.
The more efficient the algorithm, the faster and more efficient the computer can perform the task.
4. Machine learning
Machine learning includes various types of algorithms designed to help computers learn from data. Just as you improve your skills in sports or games by practicing them, your machine learning skills also improve with more examples.
The more data you give a computer, the better it can recognize patterns and “learn” what to do next. This way, when people like you use it, we can take your input and give you what you want.
This is another place to be wary of. Algorithms are prone to bias, mostly unintentional, based on the people writing the code or checking the output.
5. Large-scale language model
This is where training data and algorithms come together.
Different models or tools, such as ChatGPT, may have different training data, rules, or both, and therefore give different results.
Just as our brains help us write and speak based on a combination of knowledge and training, what makes one AI tool different from another is the training data and the variety of instructions for interpreting that data and generating responses. It's a combination.
6. AI bias
AI bias, also called machine learning bias, refers to AI systems that produce biased results that reflect and perpetuate human biases in society, both historical and contemporary.
This is caused by the biases of the training data, the developers who create the algorithm, and the biases of the people who interact with and “fix” the model.
When machines learn from human-generated data, there is a risk that the data will contain human biases, sometimes without the human knowledge. After learning biased data, the machine reproduces the bias in its output, creating AI bias.
This highlights the importance of knowing that data used for machine learning is sourced ethically and appropriately vetted for bias.
7. Chatbot
Like language models, chatbots learn by talking to many people. They use what they learn from conversations to better understand and respond. It's like practicing a language to get better at it.
As ChatBots have become increasingly common in areas like customer service, if you've tried to book a flight or make a doctor's appointment online in the past year, you've probably come across a ChatBot. You might not even have noticed!
ChatBot works by leveraging natural language processing and machine learning to answer questions and guide conversations based on conversations the machine has “studied.”
While this may be an easy way to serve customers in some cases, some ChatBots tend to lack human warmth in their conversations.
Bringing AI and Ethics into the Church
In conclusion, knowing the basics is the first step to ensuring the ethical use of AI in ministry. Before adopting AI, ask these questions:
- Where does the data come from?
- Was the data provided ethically?
- Does the training data align with our church’s beliefs?
If you want to feel confident using AI responsibly, consider Church.Tech. Our tools are designed to adhere to the most stringent considerations of ministry because they are created by church leaders, for church leaders.
You might be surprised, but you might want to talk to someone before making a decision.
And if you want to find practical ways to use AI in your ministry starting today, check out this free guide, 25 Ways to Use AI.