Jun 01 2023

4 Ways to Use Deep Learning to Improve Citizen Services

State and local agencies can direct specific responses through artificial intelligence and machine learning tools.

Imagine a world where citizens could quickly and easily report issues to city hall without having to identify the correct department or phone number. If a road sign were damaged, a citizen could upload a photo of it to an app built to automatically categorize the issue and route it to the appropriate contact. They could report a damaged fire hydrant or another piece of city property by simply noting it in an app designed to automatically send the report to the correct town office.

You don’t have to imagine. The capability exists; it’s called deep learning.

Deep learning, a neural network consisting of more than three layers, takes machine learning (ML) and artificial intelligence (AI) to new heights. It mimics the way the human brain acquires knowledge (such as learning to drive a car), makes decisions and filters those decisions to the appropriate places.

Deep learning is exceptional for enhancing citizen experiences. Local authorities can use deep learning to prevent traffic congestion and accidents by predicting road conditions with incredible accuracy. Police departments can use it to keep communities safer because deep learning can detect and classify images and help police identify criminals through photos captured by CCTV, traffic cameras and other connected devices.

But how do state and local agencies begin a path toward deep learning? Let’s look at four key success factors.

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1. Lean into More Efficient Databases

One of the most critical components in advanced ML initiatives is the quality of the agency’s database management system.

Deep learning requires massive amounts of data. Although AI can process large data sets faster than a human, databases must keep pace with the complex processing needed to derive actionable insights without human intervention.

To take advantage of deep learning and meet the needs of advanced AI algorithms, forward-thinking agencies must upgrade to more powerful and efficient databases with unlimited throughput, scalable processing power and zero latency.

2. Leverage Cloud-Hosted Databases

To accommodate the explosion of information generated and collected by agencies, and gain intelligence from it, state and local government must continue to invest in cloud-hosted database services.

Compared with on-premises data centers, cloud-based solutions are less constrained by operational or technical requirements, making them more scalable and able to store and process ever-increasing amounts of data. When managed well, they can improve performance across agencies and reduce costs.

MORE FROM STATETECH: How data sharing boosts public benefits enrollment.

3. Don’t Rule Out On-Premises

Despite the enthusiasm for cloud services, budget constraints and the potentially high upfront costs of cloud migration may force some agencies to pause technology investments. And that’s OK. Some database workloads perform better in data centers, and moving to the cloud may break what doesn’t need to be fixed.

Plus, some sensitive information might be best kept on-prem. For instance, agencies collecting sensitive information (such as data pertaining to possible criminal investigations) may prefer to keep such information close to home for security purposes.

For these reasons, as well as inflationary pressures driving up pay-as-you-go cloud models, on-premises solutions will still play a key role in 2023.

4. Ensure Observability into Hybrid Environments

Whether an agency chooses to use cloud-hosted or on-premises database and storage services, concerns about cost, performance and efficiency will still be paramount.

To ensure databases are fully optimized to achieve the potential of deep learning, IT pros need single-pane-of-glass visibility into their technology environment, whether it’s on-premises, hybrid or multicloud. With observability, teams can discover, map and understand their data estates, making it easier to ensure data is highly available and applications and operations work efficiently.

Providing better citizen services is about improving public services and making life easier for local constituents. Deep learning can help agencies fulfill both objectives: It can provide agencies with a way to transform operations and the intelligence needed to exceed citizens’ expectations.

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