The Future of GIS/Geospatial is AI

GIS Professional are Key Influencers

The technology world (and media) is abuzz with AI, ChatGPT, and other specialized tools being released at an unprecedented rate. For many, it is overwhelming and frankly scary. We must see both the positive (embrace) and negative (avoid/counter) results of these new capabilities. This is not new. When the internet first materialized, many people and organizations put their heads in the sand and thought it wasn’t going to be anything but a marketing tool or worse. Folks postulated the end of everything because of its misuse. There were and continue to be fundamental changes because of the internet. The same will be true with AI. Some will ignore it and list all the possible problematic results while others will embrace and influence it. I believe the GIS community MUST be influencers. This will be a big shift. The GIS community in general is slow to change. Esri, the leader in GIS, built its company on controlling change. We let our vendors figure out what our role will be as we wait for them to release something we can use. Or, more importantly, we hope the government will regulate it and make our jobs/roles safe. Remember the internet? We lagged so far behind that Google had to jump in and build a mapping platform!

If we do the same thing with AI, we doom ourselves to oblivion. Why? AI needs content. It needs data. It needs us.

Mapping AI

The quality, value, and accuracy (use whatever term you want) of any result created by an AI tool are dependent on the content, data, and information it ingests. These AI engines scrape websites, pages, and anything they can to collect data. As more data is ingested, the results get better. Well, they get better if the data is accurate, relevant, and usable.

Let’s imagine a mapping AI query. Where is the most scenic hike near me that has a waterfall, a slope of < 3%, and dogs are allowed? Oh, and it has to be open and have parking. The data for this query exists but it exists in many places. AI can scrape all this info, ingest it and answer the simple question that a person might have about a hike. Where is that data? In GIS, geospatial, and spatial databases.

What about a more complex query? Show me the areas in Northern California where human encroachment is putting the Spotted Owl’s nesting habitat in danger. That would require geospatial analysis to answer that question. As an analyst, you might look at all sorts of data. Lighting at night, disturbed hunting grounds, noise pollution, etc. But what if the GIS analysts that are already thinking about this problem shared the results of all “layers” of issues? Then AI could/will ingest it and the environmental Ph.D. student working on solving this problem asks the question, and the answer and maps pop up!

I know the first thing that pops into my head is — what if they use the wrong layer to make a decision? What if they don’t understand the data behind the data, etc? I agree. That is why we need to start building the data we use with AI in mind. That means being deliberate about metadata. It means getting together as a community to design what is needed and create it.

Don’t wait for Esri to do this.

While we missed the early years of the internet, we CANNOT miss the AI revolution. Geospatial is fundamental to life. The data, techniques, analysis, and understanding are in our hands.

Our Biggest Challenges

We often hear about how geospatial is used to “solve the world’s biggest challenges.” Every few years it is proclaimed that the Geospatial Revolution is just beginning.

The truth is, AI gives us the platform to actually realize this vision.

Climate change is a big challenge that we often talk about. But there are so many others. Aging infrastructure, poverty, water allocation, ocean health, livable cities/towns/communities, pollution, natural disasters, economic disparities, health, etc. Without fast access to accurate and thoughtful geospatial data (and derivative data), these problems will be answered by models that are wrong. If GIS professionals jump in, will the results be flawless? No. But the current model is not working. I started in GIS 30+ years ago. Infrastructure quality is still bad. Climate change is accelerating. Species are going extinct faster than we can count. Drinking water is undrinkable and farmers are illegally breaching levees to control water flow. And we are spending more on war than at any time in my lifetime.

Embrace and Guide the Future of Geospatial

AI is the future. The genie cannot be put back in a bottle. AI engines will power apps, applications, solutions, assets, decisions, and more! Let’s ensure that geospatial data and analysis are accessible and correct.

Let us as a community:

• Create a standard for what metadata is critical.

• Build the datasets that we know must power this new world.

• Create analysis that influences positive actions.

• Make critical data easily available and shared.

• Build a geospatial AI engine.

• Build AI-driven solutions that use geospatial data.

• Advocate for authoritative data priority with broader AI engines.

The business model of how companies, organizations, and individuals work will probably need to change. GIS is not a can in the center of an organization. Companies should not control other organizations so they can make more money. We can change how we work together. Let’s redefine partnering to mean working together for a bigger cause and for bigger successes.

To stay relevant and to truly enable the GIS community to become a leader in the change, we must be active participants in the development of the future of AI. We need to take the reins and create the solutions the world needs.

What do you think?