Balancing the AI and Human Elements of Geospatial Applications

Developers of solutions for geospatial applications have integrated elements of AI for decades. The latest, more powerful (and popularized) wave of AI makes it more difficult to determine an optimal mix. We asked industry thought leaders and experts to weigh in.

Advanced computing to automate processes and improve efficiency in workflows is not new to geospatial applications. The names may have changed, but the core proposition is the same: computing assists and enhances many tasks that could otherwise require repetitive and time-consuming manual execution.

I was asked to write about how the latest wave of such advances in computing is, and potentially will be, impacting the world of geospatial applications for practitioners and professionals. AI has been implemented and leveraged in the geospatial sector for decades. However, there have been significant advances, that are coincident with the popularized term “AI”. Early implementations leveraged machine learning and deep learning. More recently, advances adding neural network approaches have hit the mainstream, and certainly for the geospatial sector.

For example, an element of laser scanning for reality capture, namely point cloud classification (PCC), is very processing intensive. And if attempted manually, it would render the use of such mass data capture too costly and time-consuming to be practical at scale. Two decades ago, the “old” AI applied elements of machine learning to PCC, with great success. In the present day though, lidar can capture 2 million points per second, and be on a mobile platform (drone or vehicle) creating a deluge of data. The “old” AI would not be able to keep up. The “new” AI, leveraging decades of advances, neural network approaches, etc. (e.g., for PCC), can.

There are applications of this new wave of AI in geospatial solutions, and at a crucial time. There are skills shortages across various geospatial sectors. Plus, there is a global infrastructure gap: high demand for new, updated, smarter, and greener infrastructure. Legacy tools and methods could never close this gap. To meet this challenge, more automation, smarter processes, and upskilling of workers is an imperative.

AI: Amazement and Anxiety

When chatbots and generative AI tools, like the generative AI art tools we are seeing so much of, became accessible to everyone, there were mixed emotions. First, there is amazement at what it can do. But then, someone might start wondering: “If AI can do this, how long before it can take my job?”

Geospatial practitioners and professionals are typically more sanguine when it comes to the buzz about AI. We’ve been on a continuum of of automation tools developed for our applications since the beginning of the digital age. To remain competitive, geo folks will typically evolve with the tech. And it is not an insignificant fact that, especially for the field side of geospatial, there has been a safety dividend.

This new wave of AI has been popularized (and hyped) as it is quite visible and accessible to the general public. Particularly, marquee AI: generative tools for art, information searches, and the written word. The substantial benefits of this new wave for geospatial applications include those from both generative and analytical AI. However, these elements are often esoteric, so much so that some geo users might not even realize this is in play, unless it is stated as a sales hook.

Not that the reactions of the non-geo folks are not worthy of examination, we’re going to focus this article on the geospatial sector.

Prompts

We asked the geospatial industry to comment on a few key elements of the subject. All but two of the largest geospatial solutions firms asked, responded. We also asked several geo-thought-leaders, those who have written or presented on the subject, or who we’ve had relevant discussions with in recent years.

The first prompt was to relate their thoughts and experiences with AI for communications (as bot-writing has become more commonplace) and/or specific geospatial applications. We asked for examples from their solutions and products.

The second prompt focuses on a trend of promoting AI as a way to reduce staff. While we hear this more in other industries, and rarely in the geospatial sector, it is a subject on the mind of many who work in the industry, when thinking about their futures. The only time I’ve come across this in the geospatial industry has been from some poorly thought-out marketing materials (e.g. “With this AI app for your phone, you do not need surveyors anymore”). And a few over-zealous (and often junior) sales staff (e.g. “You can put all of your past project’s data into AI, and it will do new ones faster and better than you can”). Tact is a quality lacking in some folks.

The responses we received handily address our prompts, but also provide a wider view of the subject.

 

Claire Rutkowski, Chief Information Officer, Power Engineers

On the topic of communications and geospatial applications:

“There are lots of types of AI, from machine learning, computer vision, predictive analytics, and so on to the AI that gets headlines these days – generative AI based on large language models.

“When it comes to marketing copy, case studies, articles, video scripts, etc., I do think generative AI is tremendously helpful in throwing up research ideas and avenues for further exploration.  However, I tried an experiment a couple of months ago in which I started with the same article abstract, gave it to AI, and wrote an article myself, then handed both off to my Marketing person. The AI-generated article was clearly AI-generated. It lacked tone, depth, and empathy. It was boring. Really boring. It did give me some ideas for further avenues of research to explore though, so in the end I updated my article with further thoughts generated by AI (although obviously vetted, researched, and put in my own words). So, AI was a useful tool, but it couldn’t do my job for me.

“When it comes to training manuals, I think the ‘boring’ aspect of AI-generated language is perhaps not as crucial, but accuracy is paramount, and right now you would definitely still need human validation to ensure the instructions are precise, correct, and current.”

On the topic of AI’s potential to reduce workforces:

“I do not think AI can replace your workforce, nor do I think any geo firm should promote that as a key benefit. As I discussed in the keynote, Goldman Sachs (and indeed Autodesk and Bentley) sees AI as a co-pilot, relieving the strain of lower-level lower-value tasks to free up operators and engineers to focus on higher-value activities.

“AI will reduce the number of hours required but given existing resource constraints in the industry and record level backlog, I think it will simply help us to keep up, not eliminate jobs. And as far as promoting AI as reducing your workforce, that would be a mistake. A vendor selling AI-enabled software and using ‘reduce your workforce’ as a selling point will create a lot of resistance from their potential customers because few will want to buy a solution that will eventually be their replacement.”

 

Ronda Schrenk, CEO, United States Geospatial Intelligence Foundation (USGIF)

On the topic of communications:

“AI can be an immensely helpful writing partner. It turbocharges brainstorming, does lightning-fast drafts, and can instantly mine a trove of data to identify the most telling details. 

“But that trove is limited to existing information, which in turn limits how creative AI can be in situations calling for imagination such as marketing. AI also remains subject to hallucination. And it sometimes has a tin ear. So at least for now, we need to ensure that AI-generated text is imaginative, truthful, and rings true. This is where the human touch is indispensable: it’s essential to check AI-generated facts and sources, and to make sure our written communications convey the author’s authentic voice in a way that resonates.”

On the topic of AI’s potential to reduce workforces:

“Putting people out of a job is never anything to brag about. But helping your team expand their skill set and reduce time spent on tedious tasks, freeing them up for more creative and strategic endeavors, these are the greatest strengths of integrating AI into the workplace. Skilled employees have the know-how, and AI can work at scale with amazing speed; together, they bring complementary advantages to the mission and can work together as a team. The way to position your people for success in using AI is to help them do certain things better, faster, and more comprehensively – leveraging technology to bolster human talent.”

 

Jason Hallett, VP and General Manager, Integration Services, Topcon Positioning Systems

Hallett took an interesting approach to answering our questions. He posed the questions to ChatGPT and then followed up with his thoughts. While they agreed in general, Hallett provided depth, on the topic of professional responsibilities, that the AI response lacked.

On the topic of geospatial applications, from ChatGPT:

~While technology such as GPS, drones, and Geographic Information Systems (GIS) have enhanced the efficiency and accuracy of land surveying, humans remain indispensable for their expertise, problem-solving abilities, and ethical considerations in the field.~

On the topic of geospatial applications, from Hallett:

“I agree with the ChatGPT response, but I think there’s more to it for land surveyors. It is a surveyor’s obligation to discover as much evidence as possible and present it with careful and honest consideration, especially when conflicting evidence occurs. The text below, from Cal. Code Regs. Tit. 16, § 404.2 – Responsible Charge – Professional Land Surveying, provides some insight as to why the human element is not only critical, it’s required because someone (not ‘something’) must be held responsible.

“For example: Land surveying decisions. The term ‘responsible charge’ relates to land surveying decisions within the purview of the Professional Land Surveyors’ Act. Land surveying decisions that must be made by and are the responsibility of the land surveyor or legally authorized civil engineer in responsible charge are those decisions concerning permanent or temporary work that could create a hazard to life, health, property, or public welfare, and may include, but are not limited to:

(a)Selecting the methods, procedures, and tolerances of fieldwork.

(b) Determining calculation and adjustment methods.

(c) Determining and specifying the information to be shown on maps or documents furnished in connection with land surveying services, including the format of the information and the format of the maps or documents.

(d) The decisions related to the preparation of maps, plats, land surveying reports, descriptions, and other land surveying documents furnished in connection with the land surveying services.

(e) Reviewing the sufficiency and accuracy of the work product.”

On the topic of AI’s potential to reduce workforces, from ChatGPT:

~Instead of promoting “reducing your workforce” as the primary benefit of AI, surveying firms would be wiser to emphasize other potential benefits such as:

• Improved accuracy and efficiency: AI technologies can enhance the accuracy and efficiency of surveying processes, leading to more precise measurements, reduced errors, and faster project completion times.
• Enhanced capabilities and innovation: AI enables surveying firms to access advanced data analysis, modeling, and visualization tools that can unlock new insights, support informed decision-making, and drive innovation in the industry.
• Better client outcomes: By leveraging AI, surveying firms can deliver superior outcomes for their clients, including more comprehensive surveys, better-informed land management decisions, and improved project outcomes.
• Opportunities for upskilling and growth: Rather than focusing on workforce reduction, surveying firms can position AI implementation as an opportunity for employees to upskill, learn new technologies, and take on more strategic roles within the organization.

By framing AI implementation in terms of these positive benefits, surveying firms can build trust with clients, maintain a positive reputation, and foster a supportive and engaged workforce.~

On the topic of AI’s potential to reduce workforces, from Hallett:

“AI is a tool, it is not perfect, and it has incredible potential to increase productivity when it is developed, used, and checked for errors responsibly. That said, while processing data can be done with exceptional speed, now… so can the delivery of incorrect results that we humans might trust too quickly. The part I like the most from the ChatGPT response is that the opportunities for upskilling and growth are immense today. Humans will spend their time on important decisions and strategic plans, versus mundane data processing, and will be able to develop new technologies at a faster pace, that should be able to better prevent hazards to life, health, property, or public welfare… “

 

Craig Hill, Vice President of Marketing & Services at Leica Geosystems

On the topic of communications and geospatial applications:

“Artificial Intelligence (AI) acts as a tool that enhances human efficiency, augments our abilities, and streamlines our tasks. Yet, it is limited to generating outputs based on human-created inputs and continues to require human creativity and problem-solving for refinement. At this point, creations derived from AI necessitate careful and thorough human review.”

On the topic of AI’s potential to reduce workforces:

“The surveying profession and industry faces a talent scarcity: Fewer young talents enter the industry while seasoned surveyors near retirement age. That, along with consistent cost pressure, requires businesses to leverage new technologies, such as AI, that allow them to do more with less. Although generative AI is relatively new, various forms of AI have been in use for a while, such as machine learning in self-learning total stations. More recent AI developments have enabled applications in surveying as well: Surveyors use AI tools, for example, to generate descriptions for catastrophe boundary plans, thereby saving significant amounts of time.

“In many instances, AI does not replace humans but helps increase productivity by automating tasks. Consider the time savings in the realm of mobile mapping, for example, where automated feature extraction significantly enhances efficiency by reducing labor-intensive manual extraction processes. If harnessed optimally, AI will increasingly take over repetitive and time-consuming tasks, freeing up human resources for tasks that require specifically human abilities or judgment.

“For surveying or the geospatial industries at large, AI advancements will significantly improve data analytics, enabling faster and more accurate insights from vast datasets. In that sense, it will not replace people but, in fact, empower more people to work with data that hitherto required specialists to handle. For example, AiMaps from IDS GeoRadar, also part of Hexagon: Interpreting GPR data can be really complex, but AiMaps uses artificial intelligence to make GPR technology accessible to non-experts with an intuitive display that provides clear, uncluttered data for a swift interpretation of hidden underground utilities.”

 

Dustin Parkman, VP, Industry Solutions, Bentley Systems

On the topic of geospatial applications:

“AI has been an important part of our vision at Bentley, and we are already demonstrating the many benefits that it can offer from both operational and engineering technology perspectives. Fields of AI, such as computer vision, have long been prevalent in our products, with users able to analyze photos, videos, and point clouds to detect cracks in bridge piers or pavement during operations. Users can also compare images from the construction site to BIM models to automate the progress tracking and quality control processes. 

“We can also use this data to do predictive analysis for preventative maintenance. Using AI, teams can anticipate equipment failures before they happen, allowing for proactive repairs and minimized downtime.

“As generative AI has become more mainstream, we can see the potential it has to alleviate resource constraints in the engineering workforce. By using AI to automate time-consuming and repetitive tasks, engineers will have the capacity and latitude to take on bigger problems and drive infrastructure improvements for the greater good.”

On the topic of AI’s potential to reduce workforces:

“While it is highly likely that AI will revolutionize the way we work, it is important to understand that AI will not replace people. At Bentley, we believe that AI will act as an assistant – or copilot – that augments and enhances what infrastructure engineers and practitioners can achieve.

“AI holds the potential to revolutionize the infrastructure engineering community by significantly enhancing productivity. The current boom in infrastructure design, construction, and rehabilitation has placed a considerable burden on the existing workforce. Traditional design and engineering workflows, often rooted in 2D deliverables, are time-consuming and prone to errors. AI can address these challenges head-on, bridging the productivity gap and minimizing the need for manual, non-value-added processes.

“By automating routine tasks, AI allows engineers to focus on innovative solutions that add value, rather than merely producing work. It can streamline design processes, optimize resource allocation, and enhance decision-making through predictive analytics. Furthermore, AI can facilitate real-time monitoring and maintenance of infrastructure, reducing downtime, improving safety, and pinpointing when and where critical maintenance is required.

“For future generations of engineers, AI will be an integral capability, enabling them to tackle complex infrastructure challenges more efficiently. By transforming the way we design, construct, and maintain our infrastructure, AI not only boosts productivity but also paves the way for more sustainable and resilient infrastructure systems. Thus, the integration of AI in infrastructure engineering is not just a productivity enhancer—it is a game-changer. 

“It is important to note that the goal of integrating AI into infrastructure engineering is not to replace engineers, but rather to augment their capabilities. AI is a capability that can handle repetitive tasks and analyze large volumes of data more efficiently than humans. It allows engineers to focus on the aspects of their work that require human ingenuity, creativity, and problem-solving skills. By eliminating the need for manual, time-consuming tasks, AI empowers engineers to spend more time on innovative design and strategic planning. Therefore, we do not see AI as a threat to engineers, but rather as a powerful ally that can help them achieve their full potential and drive the industry forward. AI is here to make engineers’ jobs more meaningful, not to take them away.”

 

Larry Fox, VP of Marketing and Business Development at Bad Elf

On the topic of communications:

“AI can easily access a wealth of knowledge far beyond human capacity. My use of AI in a written capacity is that of an assistant. Since many of these language models are somewhat tuned to provide answers that we will like, that’s not always the best content to be redistributed. I like to ask the AI a few times to provide a few paragraphs and use the material I find appropriate as part of what I construct myself. My term for this is the ‘I didn’t think about it that way’ AI opinion. I refuse to use AI-generated text and regurgitate it in any medium – sometimes it’s a bit pithy, other times mundane and repetitive.

“The purist in me sees using rote AI-generated text as no different than me handing you a block of source code. It performs a function but has no personality (or at least a real personality). Mind you, I can ask it to write in the style of Mark Twain or Porky Pig, but that only serves for enjoyment. My corollary to this is if AI is writing everything then what’s the point in reading it? The reader can get the same, or a similar result, if the writer just shared the AI prompt.”

On the topic of AI’s potential to reduce workforces:

“Now here’s a place where I have a different opinion. AI is a powerful tool that when trained and used properly can outperform me in the areas of big-data analysis, pattern recognition, feature extraction, etc. Humans just aren’t efficient at some of these processes—with the caveat that some are exceptional. However, for large-volume work, imagine the lidar scanner rolling over 20 miles of street; much better to pass that to the AI to extract features than a team of humans.

“It’s really an efficiency problem. Shouldn’t I use the best tool for the job? People in this scenario are those creating and defining the training models. They are also the ones assessing the viability, accuracy, and repeatability of the work products. I liken the move to using AI as not moving from a screwdriver to a power screwdriver but a screwdriver to 1000 simultaneous power screwdrivers. I’m a realist as well. AI will reduce the workforce in places where humans only add marginal value or can be substituted. This is a natural progression caused by technology – how many switchboard operators do you know?”

 

Ray Weatherbee, CEO, Stonex USA

On the topic of geospatial applications:

“My viewpoint on AI in our line of business is similar to when machine control and robotics first arrived for our contractors and surveyors. Whenever the situation involves reducing, the workforce with more efficient automation the workforce will always reject this, and the business owners embrace it. It was always difficult telling a motor grader operator that by automating his machine he would become more productive. If not expressed correctly the operator takes it as an insult. When the surveyor is told that a robotic total station would allow him to become a one-man operation, and the instrument man or pole man is no longer needed it can easily be construed as an insult and people now without a job.”

On the topic of AI’s potential to reduce workforces:

“If all of these new advances are portrayed correctly as a new tool that provides quickness and advances to better accuracy. Now the other individuals have more time to complete other tasks, so everyone continues to have a job because the business is performing better and at a faster pace. One step ahead of the competition which is what it’s all about in order to achieve success.

“I foresee AI entering our market with the same strategy as in the past. It’s all on how it is presented and without simply stating that it will reduce the workforce. Nobody wants to be in that situation. It’s all about turning the potentially negative into a positive. Those that can handle this strategy will succeed.

“I guess we all could look at the automobile manufacturing industry years ago and see how they handled these integrations and learn from their mistakes. I’m sure Henry Ford had to overcome some intense situations while integrating more and more automation in his manufacturing strategies.”

 

Dave George, Global Account Manager, AEC Section, Esri

On the topic of communications:

“Generative AI is evolving at a blistering pace and with that the ability to write pretty good material.  I say pretty good, as what generative AI is using is a compilation of what is and what was.  Granted this is a massive amount of data and more than any human could come up with, but the human mind also can dream up lots of different things based on their observed and not just learned experiences.

“Breaking this down to specific areas, like case studies and articles, these are usually specific situations, and firsthand experience is going to be the best with respect to the story.  AI would not have this experience and would be drawing on any “like” experience from around the internet.  This would be wrong in this instance.  Training materials and manuals are also specific and need to be updated with the latest information about the product referenced.  AI in this instance would not know what the latest and greatest features are and how to take advantage of them in the work process of the product the manual is being made for. 

“For other written communication, Generative AI can support a person in setting a foundation, making sure things are grammatically correct, and building the story, but the individual should only take what they are given as a guide and then review, and edit it to their personality and preferences.  The bottom line is for all these areas, the human element should be preserved for the majority of the text and context of any written medium.”

 On the topic of AI’s potential to reduce workforces:

“There are a lot of areas where I could see AI reducing the current workforce. However, reducing the workforce should not be part of the story here, but a modification of the workforce and work process. The type of jobs may be affected, but the number of jobs in many cases is not affected and sometimes it is even increased. 

“For example. within design and engineering, a lot of factors that go into a design are based on rules.  These rules along with examples of similar projects can all be incorporated into machine learning and the AI functions could very rapidly produce a design, or multiple designs that conform to all the rules.  Aesthetics is to the beholder, but AI could produce multiple options to support a client’s needs. 

“Those with the affected jobs are within their right to be unhappy with the situation, but an overall business always has to evolve to support changes in economies, and technology.  In the case of manufacturing, robots came in and severely reduced the human workforce in some sectors of the business, but increased in others, and created completely new jobs as well.  This, in my opinion, will be the same with AI as it gets integrated into different business work processes. “

 

Jack Dangermond, President, Esri

Jack added some notes to conversations with George, and Andrew Turner, Director & CTO, R&D Center DC, Esri, on these topics. Turner provided a recent example of the application of Esri’s emerging generative AI technology: the  DC “DC Compass”, which provides public access to nearly 2,000 open data sets via a simple AI-driven chatbot.

On geospatial applications and workforces:

“I personally feel that, while a lot of the emphasis in the press has been around reducing jobs or eliminating jobs, my sense of this technology is that it will enrich and accelerate the work people are doing.

“At Esri, we are applying it in two major ways. Improving and accelerating in-house work, like tech support by using LLMs [large language models] with use cases of our customer’s calls. This has improved how we manage these calls.

“The second area is in applying Geo AI models to data, such as imagery, to extract, features, patterns, and in some cases relationships in geographic data.”

Esri has embraced and is a pioneer of Geo AI (or, GeoAI). There’s a collection of articles and blog posts that provide a great introduction to GeoAI.

 

Cautious Advocacy

The respondents were selected for something they have in common: they have all worked, hands-on, in their respective sectors of geospatial. They can recognize, in real-world terms, the direct benefits of AI, the potential, and the value of the human element.

My take on the prompts has been formed from the same influences. I may get asked to watch for trends in geospatial and write about them, but I am also a full-time geospatial practitioner (surveying, GIS reality capture). I’ve been in geospatial for more decades than I’d like to admit, went through the transition from analog to digital, and many tech leaps since.

The term AI might be quite buzzy right now, but folks forget the many steps along the way.  For instance, long before there were internet search engines, there were digital search services like LexisNexis (e.g., for legal and news research). After the internet became open to the public, web search engines soon followed.

As processing power increased, on all sizes of devices, so did the sophistication of applications and the ability for the programs to “learn”. Remember “fuzzy logic” in devices and appliances, and digital assistants? (Ok, “Clippy and “Bob” don’t count). Machine learning and deep learning entered our devices, applications, and lexicon.

With every tech step, every (enduring) innovation, every new black box solution, many in the geospatial sector eagerly welcomed these changes. Changes were not viewed as a threat to their jobs, but instead were a way to reduce errors, reduce rework, increase the productivity of staff, remain competitive, and enable expanding services and growing their businesses.

I’ve been accused of sometimes being a bit too vocal in my advocacy of new tech, and AI. In addition to the AI ghosts-in-the-machine that geospatial solutions developers are rapidly integrating into the products we use each day, there are standalone AI tools I have found invaluable.

As a geo-writer, AI search tools provide depth that traditional search engines cannot. I’ll use several, and then use another AI tool to compare and amalgamate them. Citations often require an additional, more manual approach to verify.  Test drafts are handy, though I can never use them for finished products (and I’ll explain that below). Plus, my clients absolutely do not want that. An example of the enduring desire for a human touch is exemplified by a situation that the content managers for two popular tech publications related. They both had to turn off their content submission portals as they were receiving as many as a hundred AI-written drafts per day. They were easy to spot, flawed in many ways, and mostly way off the mark.

As excited as I and many in the geospatial sector are about the seemingly limitless potential from AI, and benefits already being realized, there are some caveats. You’ll see caveats in the insights above, from the industry experts, and I’d like to offer a few more.

AI mines what it can find out there in the digital world. That can be a plus, but also a liability. The geospatial sector may be large and broad, but it is in reality, an amalgam of esoteric elements. If you give AI a prompt about a geo subject, you may often find that it knows less about it than you do. If it provides some insights you were not aware of, great, but you will surely still need to dig deeper. The reason for this is that there are huge repositories of technical data that it can’t see; papers, publications, and reference materials that are not yet digitally accessible.

Even if/when everything related to geospatial is finally online, it is mixed out there with everything else. Imagine geodesy papers mined along with flat-earth “papers”. Ok, that was for laughs, but it underscores a concern about AI-generated information; what if bias is injected by selective curation of source data?

Can AI field test a product or solution, can it judge the nuances of an interview, or feedback from a stakeholder meeting? A human is, or should be, keeping the complexities of “purpose” in mind at all times. One complaint about AI is that it might not be able to, beyond rudimentary goals.

However, those considerations are mostly taken into account by those who implement AI for the geospatial sector. Geo solution developers are adept at finding the right balance of AI and human elements.

Yes, some elements represent current jobs that AI could greatly impact. This is nothing new, and while adaption of new tech is not without pain, the long-term outlook need not be viewed as dire. To keep things in perspective, consider that a century and a half ago, the majority of the population of this country was directly involved in farming. Now, with the automation since, this is less than 2%. Motorized vehicles replaced the horse-based economy. Typing pools in offices were replaced by keyboards on everyone’s desks (and mobile devices). The list could go on and on. All of this while the population of the country grew eightfold. And did all of these shifts permanently displace human elements? No, there are more people currently employed than at any time in the nation’s history.

Could there be very specific skills displacement in our sector? This may be inevitable in certain cases; however, we are seeing individuals and firms actively upskilling, a move that will benefit both. It is often said that AI might not take your job, but someone skilled at leveraging AI could. To stay ahead, we may need to embrace AI as a new co-worker, and grow our skills for “coaching robots”.

The impact of an increasing footprint of AI in geospatial will likely not be as contentious as for other sectors. On the contrary, AI is poised to enable our practitioners, professionals, and businesses to solve many pressing world problems.

 

Footnote: At the upcoming GoGeomatics Expo 2024, to be held October 28-30 in Calgary Canada, a conference track is dedicated to Geospatial AI. We proposed “Balancing the AI and Human Elements of Geospatial Applications” as a prompt for the keynote address by Bryn Fosburgh, Senior VP, Trimble. We look forward to his insights.