Driving the Future of Public Services with Data & Insights

Tyler Podcast Episode 81, Transcript

Our Tyler Technologies podcast explores a wide range of complex, timely, and important issues facing communities and the public sector. Expect approachable tech talk mixed with insights from subject matter experts and a bit of fun. Host and Corporate Marketing Manager Beth Amann – and other guest hosts – highlights the people, places, and technology making a difference. Give the podcast a listen today and subscribe.

Episode Summary

On this episode of the Tyler Tech podcast, Kyle Hall, Director of Product Management for Tyler’s Data & Insights Division, shares his expertise in the ever-evolving landscape of data management software. Kyle offers insight as both a long-time Tyler employee and former public sector servant. From the importance of a strong data foundation to the evolution of the resident experience, Kyle explores how advancements in technology have driven monumental shifts in public services. He also dives into the future potential of AI and the ways it can further drive efficiencies in the public sector.

Guest: Kyle Hall, Director of Product Management, Data & Insights Division, Tyler Technologies

Host: Beth Amann, Manager, Corporate Marketing, Tyler Technologies

Transcript

Kyle Hall: I think what's really changed is that seeing things like ChatGPT, Midjourney. I mean, there's this dizzying array of tools that started to crop up really all around us in this sort of moment, extreme hype that we're in. So, there is a tremendous amount of opportunity, and I think the biggest thing that’s changed is people's mental models have changed. The idea of, like, oh, maybe this is possible. Maybe I could have this system that creates a conversational interface around all of this different data. Maybe I could do that pretty quickly.

Beth Amann: From Tyler Technologies, it's the Tyler Tech Podcast, where we talk about the issues facing communities today and highlight the people, places, and technology making a difference. I'm Beth Amann. I'm the Corporate Marketing Manager here at Tyler, and I appreciate you joining me for another episode of the Tyler Tech Podcast.

Today, we are joined by Kyle Hall, the Director of Product Management for Tyler's Data & Insights Division to discuss the more technical side of data management software and get into some future trends. Kyle, welcome to the podcast.

Kyle Hall: Thank you very much for having me looking forward to the conversation.

Beth Amann: Yes. Well, our listeners who have been with us for a while will know that the Data & Insights Division personnel have been very much included in our podcast recently. We talked with Franklin Williams, the President, and Saf Rabah, our Vice President of data solutions, and so we're excited to have you here to get a little bit more into the nitty gritty of the technical side of things. Before you were working with what was Socrata and then Tyler Technologies. You and I have gotten to work together for a good while now. I know that you were with the city of Los Angeles and worked in a number of capacities building open data projects and dashboards and visualizations and a lot of analysis related to city financials, and performance data. So, you've been with Tyler now for a good while, but you spent so much time in government. And so, I'm really interested in hearing from your point of view what has changed in how government approaches data management since you were last working in government?

Kyle Hall: Yeah. Absolutely. Well, a lot has definitely changed over the last, last decade. I think first and foremost, you know, when I was working in government, cloud management cloud systems was kind of the new thing coming.

But still the majority of the work we were doing was on premise. We spent a lot of time thinking about the hardware in our data center. And how we could manage and equipment manage costs there. And I think that sort of wave of transition to the cloud has not only come, it is, I think, sort of past controversy at this point. The vast majority of the governments are working with are adopting more of a cloud first mindset, even in very high compliance spaces, like public safety, like work management.

The technology has just improved the security as a group, and really a lot of the policy and understanding is really a lot more mature than it was about, you know, when I was working in the government, A lot of the difficulty in incorporating some of these new systems and technologies, it's not just about the technology. It's about how that technology fits in with procurement policy, how it fits in with security and IT policy, how, whether the staff and expertise exists to manage those systems within a government. And really that knowledge, that cultural shift, that policy shift is extremely widespread at this point.

And now we're sitting in sort of a different kind of inflection point because, you know, as there's been this shift to the cloud, that makes data a lot more accessible. And so similarly, a lot of the things that were maybe considered cutting edge or more risky projects several years ago are now much more routine, I'd say. So, we're seeing a lot of governments that are moving forward with transparency projects based on live data.

The controversy around that is much lower than it used to be. We're seeing a lot of governments really move forward with trying to explore AI and process automation, and some of these wraparound services that can, be effectively used you have new data highly accessible and in a well-managed space. And, you know, you, you just see a lot more maturity and a lot more understanding of the opportunities, as well as the risks and challenges that come along with a more cloud native data forward approach to learning a government?

Beth Amann: It's interesting to think about cloud as being something that was so unfamiliar because it is such a huge part of our everyday lives as consumers and obviously for you and me and our everyday work. I think it's interesting that you talk about the comfort that's there now that these are no longer cutting edge or scary innovations, but you did also mention cybersecurity, that these are not that scary anymore because there's also so much more security associated with having solutions in the cloud versus in on premises.

It sounds like there's so much exciting stuff still to come though, and it sounds like that governments have a lot to choose from and are maybe feeling more comfortable now with these innovative technologies.

And so, thinking about from when you are working in government to when you are now working with government, what are the capabilities that governments are most excited about implementing and leveraging?

Kyle Hall: Yeah. Absolutely. Well, a lot of government process started in paper.

Right? And since those very early times, the problems associated with paper are pretty well understood. Like, things can get lost. It can take a long time to fill out forms.

There can be reconciliation issues between multiple systems. So, if you have multiple systems that are recording aspects of information relative to one person, or one entity that can be something like fragmentation problems. And so, these are these are long running problems that have been happening for hundreds of years in government. So, I think the things that people are most excited about is sort of asking that perennial question, is this the technology that's going to allow me to solve some of these perennial problems together?

And then a lot of cases, the answer is the technology very much can't actually. So, a very simple example is, we do a lot of work with folks in the health and human services side. And for a lot of individuals, there's a very complex array of services that they benefit from that they can take advantage of. Generally, with a pretty high level of security and compliance.

So that's health data, some of that's criminal justice data, some of that sort of social service data, generally held in different systems that don't have a long history of talking to each other. But, you know, one of the really exciting things about these highly secure cloud native data management capabilities that now exist is actually the prospect of bringing that data together is now practically achievable in a way that has been historically impossible. So, you know, any new technology expands the horizon of what can't be done, and really pushes forward sort of the art of the possible.

Then it's just a question of procurement, of implementation of policy and of culture. Right? So, in a lot of cases, what we're seeing there have been extremely excited about looking to say, hey, it is actually possible for us to build a more citizen centric view of the world and to make citizen services more cohesive to make sure the different agencies are better able to communicate and share information with one another. So that remains I think the goal was the thing that people are most excited about, and it's really a question of can that be implemented and can that be achieved.

And that's really some combination of technology and best practice and cultural shift to say, to get people more comfortable with sharing this kind of information. There's one of my favorite projects that we work on is with Fulton County. And, you know, this is actually one of the major initiatives they going on and sharing information between social service providers between hospitals between the county sheriff, really to identify certain individuals who may have interactions with the criminal justice system, but who also are receiving social services through other means and making sure that those individuals are maybe routed to diversionary care or get put into some kind of social support instead of jail wishing that many cases lead to better outcomes for the individual and a lot of cost savings for the jurisdiction.

So, you know, when I look forward, a lot of the things that people are really excited about is, really solving some of these perennial problems about moving forward the ability to make things a little bit more cohesive, a little bit more centralized. And then, of course, AI also kind of shows up in that realm of Hey. I wonder what's possible. I wonder if that can help us with some things as well.

Beth Amann: Yeah. I love that you bring up Fulton County, and we will get to AI in a minute, but I think one of the big misconceptions for residents is when you think of this idea of government, you think, okay, it's one. It's one entity. Like, it's the government's problem. They're going to take care of it for me.

And as we know, that is not accurate, you mentioned, okay, different agencies within Fulton County who are working towards one common goal to serve a resident. We've talked on this podcast about how I can get my license from one organization, but I vote through a different agency, and then I have to send my kids to a different department for public school education and how they're fragmented in a lot of ways. And even you just saying like a piece of paper can get lost. Imagine a piece of paper traveling through all of those different departments.

There's this big misconception for everyday residents that government is one thing and government is many has vast capabilities and a lot of what happens with data management software solutions is that it's an attempt to connect those dots.

Kyle Hall: Yeah. Absolutely. And not even just government, right? You know in that Fulton County example, a lot of those agencies are maybe nonprofits. Maybe they're private or semi-private hospitals. So, it's really the, you know, you are totally right.

There is this sort of magical view that people of like, oh, there's some magical machine somewhere in the background in government that knows everything and manages all this information. And that that's simply does not exist in some ways. It would be kind of amazing if it did, but always would be probably less than ideal if it did.

Beth Amann: There's good and bad for every option.

Kyle Hall: Exactly.

But the idea that you can bring this information together and also bringing people outside of government in a well-managed and secure way. I mean, that's a pretty incredible innovation. Right? That's really a huge shift in terms of what's possible around policy delivery.

Is ultimately, you know, we live in a pluralistic society. One of the true hallmarks of American society is not just that the government goes out it alone, but that there are this array of nonprofits, social service providers, private entities, companies, citizen organizations, all of whom participate in in the construction of our society and that delivery of services. So, the idea that you can really build programs and build information systems that actually kind of match that complexity without costing ten years to make and hundreds of millions of dollars to put together is really pretty incredible.

It's it's an amazing shift.

Beth Amann: Yeah. What was that phrase you said? It was practically possible what was previously impossible? Is that the phrase you used?

Kyle Hall: Yeah. Something like that.

Beth Amann: I think it's great. And really points out where government is right now in terms of technical capabilities that there is so much opportunity that was not possible before.

Beth Amann: We'll be right back to our conversation.

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Beth Amann: So, you mentioned the great buzzword. You mentioned AI. There's a lot of talk in this industry right now. I think every conversation I've had since becoming one of the hosts on this podcast has somehow included AI, and there's a lot of work that we think of as traditional government work that's been rooted in data science, and not AI or generative AI, but there's obviously a ton of opportunity there. So, can you talk about the opportunities you see for governments to build on or expand their data science capabilities with AI?

Kyle Hall: Yeah. Absolutely. Well, I think the first thing that you said is that AI is part of a continuum. Right? There's an AI is not different than data science. And data science is not different than statistics exactly.

You can think about data science as really fast statistics at a certain level, and AI is really fast data science. This would be a very simple way to think about it. But a lot of the core requirements to do any kind of analysis are very common. Right?

You need data, reasonable quality that data to be accessible, you need to handle your privacy and security concerns. And you need to make sure that that data remains up to date. So, a lot of core infrastructure problems are really the same regardless of the type of analysis that you're doing. I think what's really changed is that seeing things like ChatGPT, Midjourney.

I mean, there's this dizzying array of tools that started to crop up really all around us in this sort of moment of extreme hype that we're in. More justified maybe than in previous years. So, there is a tremendous amount of opportunity, and I think the biggest thing is changed is people's mental models have changed. The idea of, like, oh, maybe this is possible.

Maybe I could have this system that creates a conversational interface around all of this different data. Maybe I could do that pretty quickly. So, we're still in this kind of very early moment, this sort of very exploratory moment when it comes to generative AI.

And really understanding what does that actually mean for us, what are the best suited opportunities? And then you can think about it a lot like when we started shifting from on premises to cloud boosted systems, There was a million things that people thought might, you know, be kind of a pillar app. And in a lot of cases, it was email.

It was, like, kind of the first thing that moved over, that really changed people's lives. And similarly in AI, in this world of generative AI, those pillar apps are things that are getting worked on right now. Those are things that are going to be coming over the next you know, the coming months and years. I think the pace of change is going to be phenomenal when we look over the next maybe three to five years. There's so much investment coming into this world of AI. And so many opportunities that are getting unlocked. Just to for some very simple ones, you know, we do a lot of work around government transparency.

And a lot of that transparency work is rooted in the idea that we're going to go find the data in new systems. We're going to scrub it and apply our privacy rules, things like that. And then we're going to make that information public. The challenge you often run into in those kind of traditional transparency program, just it can be pretty difficult for instance to interpret that data. So, one of the experiments that we're doing in how right now and one of the projects that we're working on is basically training models to we're actually trying two different approaches, one to look at data across many different governments in a, in a common domain. So, for example, looking at assessment data across many different governments and training a model that knows how to interpret and kind of communicate around that data.

One of the most common types of transparency programs. If you're a homeowner and you want to look up information about your parcel, about your property, you have to go somewhere online to look that up. Well, that's a great case for a chat bot or kind of a conversational AI kind of model.

The other side of that we're looking at is could we train a model on all of the data for a single jurisdiction so that it can maybe route citizens to appropriate government services and tell them what is or is not available in that particular jurisdiction. There's still some challenges in terms of taking that live.

Hallucination is a pretty well-known problem. So most conversational AIs at this point still have an error rate that's probably a little bit on the high side for our level of comfort. Obviously, you don't want to end up in a situation where a citizen is misled, or a conversation maybe goes down path that you really don't want a government website going down. So, there's a lot of guardrails that are getting put in place there.

There's a lot of work that's happening to drive that. So, I think that's probably the thing that'll come first is working with public data in particular and really communicating with citizens and helping to guide them to either the services or answers to questions. If I were to guess, I would say I think that's probably the thing that's going to come most quickly interested. That's a really common aspect of what governments are doing and is really for a meaningful change in how citizens interact with government. But the opportunity is way, way bigger than that.

A lot of it has to do with not just how we communicate with citizens, but also how governments run their own operations. Going back to that, comment about, hey, how do we miss data? Well, you can create really effective algorithms that can match data. Hey, what happens if, you know, can we maybe automate filling out forms? can we maybe automate some of our process through some smarter technology?

So there's a tremendous amount of opportunity in terms of government efficiency, pace of process, And then an area that's a personal passion, obviously, working at the Data & Insights Division, is there's a tremendous amount of ability within AI to basically run statistics and use a new model that's created through very complicated math to run different complicated math and help you find things about your data and about your operation. So, This is already being used in a lot of cases in a low-level way for security systems. And so there's a lot of active monitoring systems that look you know, all of the activity happening throughout a jurisdiction and then trying to use AI and an anomaly detection to say, hey, kind of strange that this individual whose normal pattern of use is this is looking at this information at two in the morning from an IP address in Russia.

Maybe we should do something about that.

Beth Amann: Just a little strange, you know.

Kyle Hall: Yeah. Right. But that can be extended into all other aspects of government operations.

So, in payment processing, to do to identify fraud or anomalies in that data. You get procurement data. There's a lot of ways that you can build security and protection using ai in that world. Then even just for policy makers, you know, the ability to quickly ask questions and find outliers, identify trends.

There really is an infinite world of opportunity. I think some of those things are going to happen faster than others know, anything that's working with public data, you have less of a security and a privacy, a sort of data security concern. So, my guess is a lot of those things are going to happen faster, but there's a tremendous amount of opportunity and a tremendous amount of space for, really government operations to be transformed through the use of these AI technologies.

Yeah. And we are excited to be a part of it. And, you know, obviously, as Tyler, we have access to a vast array of data, all the clients that are using our tens of thousands of installed systems across the world or across the United States. So, we're really looking at how we can take advantage of all of that data and build some incredibly cool insights for our clients for those who are using Tyler. So sometimes to understand how they stack up relative to others, to maybe understand global trends or national trends and how those might be impacting a particular jurisdiction. I think the universe of opportunity is vast.

Beth Amann: I feel like you just offered so many points of inspiration for our listeners, like you went from assessors to offices to individual citizen experiences all over the place that any of our public sector listeners can really just say, I have an idea that came out of this. You had said something really helpful about how the speed and the pace of technology is really going to increase. And that is one of the coolest things right that there's so much computing power that wasn't available previously that is allowing these solutions to just like rapidly roll out. You said that the pillar apps are being created right now, and that's so true.

There is just I feel like we could talk for hours about every different option, even just my mind is spinning with everything you just shared, the idea of being able to compare parcels, not only in your local county, but across different counties around the country or across your state and using that for comparables. The ability to have a government website be more easily navigated through a chatbot, pulling information from that government website I just think that there's something for every one of our public sector listeners to be able to say, oh, I could start implementing that or I could start thinking about that right now.

So, we've talked about the kind of, like, past ten years. We can look forward to another ten years though and say, where do you see government data analysis and management ten years from now, especially as we're thinking about the pace in which solutions are showing up rolling out and being implemented?

Kyle Hall: Yeah. Absolutely. Well, I think as you said, the there's this sort of interesting compounding effect that, that is happening inside right now just, you know, if you think about, like, when the database was introduced, you know, it took maybe twenty years for that to really reach a point of maturity and broad adoption. You know, the cloud technology is to maybe the ten, twelve years. That cycle is shrinking. It's really getting shorter and shorter. So that pace from my technologies introduced to the sort of first killer apps are introduced to widespread adoption to sort of pervasiveness.

That cycle is shrinking more quickly than ever. And I think as I mentioned, The most important thing is I think we're going to start to see a lot of divergence among - because in order to seek advantage of AI, in order to take advantage of these next generation technologies, you have to have your foundation in order, and your foundation is the quality and accessibility of the data that you have. And those governments that have made those investments are going to find it very easy to take advantage of everything that's to come. You have your data in a well-managed place.

You have your security rules implemented in an accessible way. The cost to implement, right, a new AI technology can be relatively low. It's one of the cool things about how these systems getting built, but the costs are also coming down very quickly. I mean, to ChatCPT for membership for an organization is, you know, twenty bucks a month.

There are obviously more things to do than just pay the twenty bucks to take advantage of it, but the costs have gotten really low. But for those governments who haven't made those foundational investments, that's going to start to have a compounding effect. It's going to be not just that you don't have that core system data, but all of the other things you might want to do with it are going to get harder and harder and more expensive, more expensive, longer at longer in the end. So I really do see we start to see a lot of different where those governments that are making those investments that are really trying to stay ahead of the game and really tackle maybe some longstanding issues around data quality, data access, data security, really have a huge opportunity to leapfrog, you know, the current state of citizen experience, whereas those who haven't made those investments are going to find it more and more expensive to keep up.

You know, but when I look ahead ten years, there there's always a background in government, which is citizen expectation.

It's not maybe something that we talked about a lot, but it's certainly something that that public sector employees are deeply aware of, you know, when Google became widely available it became a citizen expectation that they used Google stuff about their government and find information very readily. And that meant that technologies like PDFs and things of that nature became a lot less attractive, right, because you can't Google inside a PDF. Similarly, I think that that change in citizen expectation is going to be just absolutely incredible over the next twenty years. I think any government of five years now is still relying on any kind of paper process is going to find a combination of rising citizen expectations of generational change. It's going to lead to a lot of problems. I think really we're going to see that full shift to not just digital native, but digital only government. I think we're going to see really transformative change in terms of how citizens interact with governments.

I think even the idea of a single government website is that point of access may fade out over the next ten years. You could totally imagine a world where states or the federal government is offering single interfaces that can access the information of many governments and route citizens in more central ways. So, once we are at this sort of precipice where we can see maybe not exactly where we're going, but all of the ways in which the world might change. You know, this is a eally incredible moment in terms of, like, a new technology that has nearly unlimited potential.

We're all just, you know, together working together heads around it. I'm interested in means and what the opportunities are and where we should go next. So really over the next ten years, I think the big thing is, yeah, that kind of divergence between those that are maybe right into the wave and those that aren't. And then just that radical change into this and expectation that's going to put a lot more pressure on those in the public sector to make information more accessible, make process more accessible and really fully make that shift away from the paper process and paper mindset to something that is more self-service, more digitally native, more accessible to citizens.

Beth Amann: think the call out for citizen expectations shaping what government services are is so important. The march of technology is going to continue. People do not want to fill out paper forms. I, for example, was sent to PDF and asked to fill it out, but I need to download it, print it, and then upload it back, and I'm avoiding that task because that seems more difficult than I want it to be instead of just inputting it into a digital system.

So, If I am irritated by that now, think about how people who are coming into the workforce ten, fifteen years from now are going to feel about that. And I love the call that you had about having a solid data foundation, I think that that's something we really have tried to empower our clients with here at Tyler, making sure that they have good data governance policy that they've been able to really work in in the culture of their government to make sure that there's an understanding of why data quality matters because you don't want to train an AI model on bad data. Hallucinations are one thing, but having the wrong information within that AI model is going to be a disaster for everyone who's involved.

And it's something that I think our public sector listeners can focus on now Instead of thinking, okay. Well, we don't have the budget right now to employ some type of AI solution. You can work on data quality. You can work on having good data governance policies in place and making sure that your data management permissions are set up correctly and data sharing permissions are set up correctly.

So, there is a little bit of, like, you can do it now type information for our listeners.

Kyle Hall: Yeah. Absolutely. I think the the best way to, you know, get ready for the future is to make sure your house is in order and you're ready for, you know, ready for the guests to come if you will.

Beth Amann: The AI guests are coming.

Kyle Hall: Exactly.

Beth Amann: Oh my gosh. Well, Kyle, there's so much that we could talk about, but I do wanna thank you for taking the time to join us today on the Tyler Tech podcast.

Kyle Hall: Of course. Thank you so much for having me. It's a pleasure to chat.

Beth Amann: We've spoken a lot about data and AI on this podcast recently, and I don't see that stopping anytime soon. Governments are poised to take advantage of innovative technology to create more efficiencies in their systems and better support their communities, but it starts with the data you have currently. Tyler creates solutions made exclusively for the public sector and has experts with government experience ready to support you on this journey. I hope you are excited about what the future holds and will reach out to us at podcast at tylertech dot com to be connected with an expert, like Kyle, if you'd like to learn more. For Tyler Technologies, I'm Beth Amann. Thanks for joining the Tyler Tech podcast.

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