In many ways, we are at the heyday of broadband. Huge numbers of households are being reached by new broadband networks funded by numerous state and federal grants. Many non-profit groups are working hard to make sure people have the computers and other devices needed to take advantage of connectivity. Many other people are teaching people how to use computers in order to navigate the online world. Digital navigators are helping folks find broadband connections they can afford.

Unfortunately, big changes in the federal government have meant that the funding for many of these activities is quickly evaporating. The administration killed the $2.75 billion Digital Equity Fund, which would have funded digital inclusion work around the country. There is still $21 billion of potential BEAD non-deployment funding, but that money seems to be stuck in limbo, and the general feeling is that even if some of these funds are released, they will only be available for specific purposes that might not include digital inclusion.

It has always been clear that the big federal funds aimed at digital inclusion work were only going to carry the national digital inclusion effort for a few years, but that funding would have given the digital inclusion practitioners the time to mature and be ready in a few years to self-fund and stand on their own. Folks involved in digital inclusion are now scrambling to survive after the abrupt end of funding.

One way forward is for digital inclusion efforts to become more efficient and better organized. That’s not as easy as it might sound. The digital inclusion ecosystem is still relatively new, and there are a lot of different groups in any state with different approaches for tackling digital inclusion solutions. Becoming more efficient might mean digital inclusion practitioners joining forces to gain efficiency. Being efficient with less funding will mean choosing projects where digital inclusion work will produce the best local results.

I’m working with some folks in North Carolina who have developed a tool that can help digital inclusion efforts be more efficient. The core of the tool was developed by Brian Rathbone of Broadband Catalyst. He’s named the new tool Marco Map AI, which is appropriate because it’s a gateway to discovery. This tool starts by gathering every possible data source and database available that has information that could inform the digital inclusion effort. In North Carolina, that means dozens of different data sources.

Some of the data is what everybody would expect, like the FCC broadband maps and U.S. Census data. But there is also a wide range of data available for things like health care data, housing, the location of anchor institutions, and education.

When Brian first brought the data together, it quickly became apparent that the sheer magnitude of the data could be overwhelming, and even a good researcher has a problem making sense of multiple disparate datasets. Brian’s first step to make it easier to understand data was to map everything. It turns out that the human mind can more quickly grasp a map of data points than tables of facts. But even mapping is overwhelming when there are dozens of attributes being mapped.

It turns out that the missing tool to make sense of the huge pile of data is AI. AI can be used to find patterns in complex data sets that a researcher would probably never find on their own. Perhaps the best way to explain how this works is with an example.

Let’s say that a hospital wants to do a better job on improving outcomes for diabetes patients in the region it serves. Research and hospital experience show that enrolling diabetes patients in home monitoring while staying in touch through telemedicine can greatly improve patient outcomes – and hospitals know that proactive care saves money for patients and the hospital. Hospitals already know the patients they are connected to, but how do they find the other people in the region who could benefit from proactive care?

The Marco software with the AI assistance can answer this question in a way that I don’t think a human researcher can easily do. The system can cross-check all of the factors related to given question. It would start with a map of areas that have a higher prevalence of diabetes. It would overlay this with factors related to broadband and telehealth. For example, what areas have good or poor broadband technologies? What is the level of home broadband subscriptions and computer ownership? Where is cellular technology adequate to handle the monitoring needs? How do households incomes and poverty levels impact the ability of homes to afford a broadband connection?

The AI system can answer incredibly detailed questions in a way that I’ve not seen done by other research. For example, you could use the software to identify the neighborhoods that are within twenty miles of a hospital or clinic, where the prevalence of diabetes is higher than average, where people have broadband or good cellular coverage, and where incomes are high enough that many people can afford broadband. After answering this kind of question, it’s easy to quickly modify the parameters of the questions to fine-tune the results until it provides what the hospital system wants to know. There are endless questions that could be posed.

This is amazing tool for policy makers and those who are trying to tackle broadband access or digital inclusion issues. I highly recommend anybody interested in this tool to contact Broadband Catalysts.