Challenges in AI Ministry Innovation

Ministry organizations face several significant hurdles when innovating with AI technology. Understanding these challenges helps organizations better prepare and plan their AI initiatives.

Organizational Decisions vs AI Decisions

The way that AI systems go about decision-making will be significantly different from current organizational strategies. While AI systems can be highly complex, their statistical precision will be unlike the hundreds of individual decisions individuals make across a company.

Whereas in human institutions dozens or hundreds of individuals apply their own complex reasoning, logic, experiences, sentiments, affections, beliefs, values, and instincts to their particular decisions, an AI system is subject to the boundaries of its parent algorithm and the data available to it.

This contrast is not to say a given AI system doesn't make hundreds, thousands, or millions of decisions. It's only to say, it won't use the same interplaying textures of reason, affection, and the rest that humans do. These methods are fundamentally different in many ways. Some will see these differences as an advantage—others as a liability. The reality is the approaches are simply quite different, and so their value depends in part on the contexts where they're applied.

As a result, the recommendations of an AI may also be a bit counter-intuitive. Putting trust in those recommendations will take time to prove out.

Data Scarcity

Unless organizations have already been collecting significant amounts of data, some AI systems will provide limited value to the organization. With a few exceptions, many AI systems must churn through magnitudes more data than the average human needs to choose a new ministry location, recommend a valuable article, or hire a new employee. Finding patterns in vast troves of data is both AI's great value and its liability. Unfortunately smaller organizations that don't have "big data" may benefit less. (Some exceptions could include modeling personalization, user engagement, and chatbots.)

One opportunity here is for multiple ministries to compile their data together so that they might learn from one another's data and make better decisions. If a mission data collection agency could be set up where data is collected, shared, analyzed, and interpreted by AI systems, organizations could optimize resources in the field and distribution to the people and places that most need their services.

Nonetheless, organizations may need to be continually generating more data for AI to be useful to them in an ongoing way. This need brings issues of surveillance and privacy into the mix. "As Christians think about the morality of AI, we need to reflect on the surveillance that allows machines to learn". And with large amounts of data, organizations will need commensurate security to protect their data sets.

Scale and Cost Savings

The value of AI systems may come only at scale, and incremental savings may be hard to show. Thus champions for AI systems may struggle to demonstrate their value to stakeholders within an organization. Because AI systems aggregate entire procedures of decision-making, advocates may find themselves trying to describe the organization's entire decision-making environment, which might feel a bit like describing water to a fish. In this case, the words "Artificial Intelligence" may win over some skeptics, as long as the dystopian movie fallacies don't overpower their perceptions.