The modern world is highly diversified on dozens of levels. Millions of different people live in hundreds of countries, work in dozens of industries, and enjoy thousands of activities. The society is divided by race, gender, age, wealth, etc. But there are two contrasting universes that define our everyday lives the most: a governmental one and a business one. On their verge, AI public services exist.

In the gov space, one has to fill endless papers, submit them after hours in lines, find tangled schedules, call offices, and more. Public services today are remarkably similar to those of the mid-20th century. Compare them to private offers: one-click accommodation bookings, personalized delivery services, mobile payments everywhere…

The thing is that governments around the world are afraid. They live in comfort zones and don’t want to evolve because this process involves significant risks. Another fact is that national digital transformation is inevitable. Citizens turn into clients who want to get the best services. Today, we’re to talk about artificial intelligence and its GovTech influence.

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To clarify things, let’s define the idea of public service. In general, it includes various duties handled by governmental/national representatives and delivered to citizens. Healthcare services, education, policing, administrative works – all of these fields are public.

Spending of governments on public sector

And what’s the problem with this industry? Surprisingly, it’s not about stagnancy. Cabinets struggle to keep the same disruption pace as businesses, but they work on it. Forget about a myth that public services can’t or don’t want to change. Instead, think about more significant challenges, such as the need for large investments and risk management strategies. Executives have to study everything carefully before making any changes.

In 2017, Europe governments spent up to 10% of GDP on public services. Sadly, R&D departments received almost nothing. The leading sections were as follows:

  • Public debt transactions.
  • Executive and legislative organs.
  • General services.
  • Basic research.

Today, the situation is similar. But we see some optimistic signs.

Trade-offs that should be broken

In the UK, the Office for National Statistics reveals intriguing info. From 2017, average input exceeds output on a quarter-by-quarter basis. This leads to a slight decline in productivity when we look at small periods. The average consumption of fixed capital is growing, too. This situation is quite evident as governments try to invest more in better services plus research.

Under these circumstances, each cabinet should prioritize goals. Ministers and officers face trade-offs because they can’t reach everything at once. Examples are price vs. performance, speed vs. quality, delight vs. convenience, and so on. Trade-offs set limits. And disruptive innovations can break these limits to reach both high speed, top quality, and affordable costs.

Keeping this in mind, let’s look at a more global trend. The same British agency we’ve mentioned above reports that the worldwide productivity level is gradually growing. From 2010, it increases each year. While local trends show certain volatility, annual statistics reveal clear progress!

Productivity of British public sector

Ways to transform

Here are a few examples of disruption strategies with case studies from private sectors. They should help to understand how public services can evolve:

  • Innovation is introduced by a new player. Being a relatively unknown company, Netflix started sending DVDs by mail. This was an innovation to the video market.
  • Innovation targets underserved users. Southwest Airlines started working with business clients from Texas who previously had no choice but to drive by car.
  • Innovation offers worse performance initially. First digital cameras were inferior to film analogs totally. But then the disruption evolution helped them to grow.
  • Innovation comes at a lower cost. Spotify is free (Premium is $10 per month). Just imagine how much should you spend on buying all the songs from its library.
  • Innovation may be linked to the tech growing independently. Blockchain allows dozens of companies to introduce new products for banking, retail, and government.

Get it right: modern entrepreneurs face lots of risks. They try to maximize revenue, keep optimized processes, and gain/retain the customers’ loyalty. They may fail and lose it all. Nonetheless, at the national level, stakes are much higher. Leaders that integrate digital disruption have to mitigate more peculiar risks like value destruction, trust deprivation, strikes, revolutions, and even doubt in the concept of governance. That’s why transformation is so slow here.

Various modern technologies can enable benefits to make the public sector evolution faster and safer. But we propose to focus on one particular GovTech trend – AI. It definitely can break the mentioned trade-offs and help nations to become digital.

To read about other GovTech ideas and concepts, check out our recent guide!

Artificial intelligence (AI) in government

The reason why artificial intelligent machines can reshape our society is in their almost unlimited potential. In general, there are two types of AI:

  1. General. A theoretical level of AI development that results in a machine similar or even better than human intelligence.
  2. Narrow. Existing software that can’t progress outside its boundaries set for specific tasks, e.g. speech recognition, NLP, analysis, etc.

The topic of the AI revolution was fully covered in the gigantic must-read study by Tim Urban from Wait But Why. He explains why we’re still far away from general AI examples. While it’s a difficult task to create a really intelligent machine, experts around the world develop successful narrow AI tools for different tasks, including public services. We will talk about the use cases a bit later. Now, let’s think about how machines change GovTech on different levels.

AI functional levels

Capgemini lists nine types of artificial intelligence united in three large stages. More globally, they also fall into one of two reviewed categories: general or narrow AI. However, these types can benefit governments in their own ways:

  • Monitor – gather data from different sensors/bases.
  • Analyze – process data and define its patterns.
  • Act – handle specific processes like form filling.
  • Interact – respond to citizens, accept requests.
  • Remember – store data in the protected databases.
  • Anticipate – predict behavior or specific trends.
  • Feel – understand human emotions.
  • Moralize – make decisions based on human morale.
  • Create – set their own tasks and start new processes.

For governments, the first six types united into two categories (automatons and assistants) are the most valuable. They can handle basic processes, interact with customers, and help with Big Data crucial for nations. Creative AI also can help in social work, for instance.

AI stages by intelligence

AI usage for public

Finally, it’s time to see how AI is disrupting public services. In a nutshell, these tools are focused on advanced digital ecosystems convenient for both gov employees and end-users. Particularly, AI helps to address the citizens’ issues, gather public opinions, automate daily tasks like requests for documents or payments, detect fraud, etc. In this case, AI systems can be implemented for internal or external use.

Further, we list a few public sectors with the highest potential for AI disruption.

1. Government efficiency

The first case is the most obvious. By integrating AI systems into cabinets, governments can save tons of money and time. Machines do tedious tasks better than humans because they don’t make errors, have higher efficiency, and lower relative costs. It’s important not to replace clerks with AI apps but reorient human employees on more creative jobs.

In the US Department of Labor, workers historically analyze hundreds of thousands of surveys. They do it on a daily basis using tangled coding systems. From 2014, the Department integrates AI systems to handle this task. Reportedly, one machine can process as many surveys during a day as one employee processes within a month!

2. Security

Here, AI works in both cases: as protection of governmental databases full of sensitive data and as an artificial policeman that boosts the national defense. AI apps can utilize language processing and computer vision to detect crimes/frauds and react to them in real-time. Different countries, such as Thailand, are already using AI systems to analyze data related to suspicious behavior. It may progress to full national preventive and protective systems.

To grasp the idea, explore software security risk management in more detail.

3. Healthcare

Probably, this industry is one of the most recognizable public services. Using AI public services, governments can deliver a better quality of healthcare faster and with lower expenses. Tools based on machine learning capabilities are able to check symptoms and suggest diagnoses, predict outbreaks, help to develop better preventive measures, set personalized treatment, etc.

There are dozens of examples of how AI helps doctors. For instance, in Northwestern Medicine in Chicago, local experts and Google specialists started a deep learning AI program to identify lung cancer. The system has analyzed hundreds of scans and predicted if a patient has a disease or no. In some cases, AI was even more precise than doctors.

4. Education

On par with healthcare, nations often guarantee quality education for citizens. In this field, AI can work for more personalized classes and generally digitalized education. Even simple AI apps are widely used for remote courses and individual schedules, which is useful for diverse communities. Also, these tools can act as virtual teachers as well as analysts because they track the progress of each student and make suggestions for further classes.

5. Interactions with citizens

Apart from top-rated services, governments use AI to contact with citizens. On the one hand, machines gather valuable feedback that helps to understand people. On the other hand, smart assistants and bots represent a next-gen interaction channel convenient for millennials and Gen Z members who don’t use phones and even move away from emails.

In Latvia, the administration utilizes a 24/7 chatbot called UNA. It answers the most popular questions of entrepreneurs, such as documentary requirements and processes. For more than a year, UNA has responded to 22,000 questions from 4,000 clients. It’s available through the official website as well as in Facebook Messenger.

AI regulation and other challenges

There are debates around AI implementation because we still don’t clearly understand how to work with smart machines. For the best results, developers should ensure data quality and availability, regular updates, and equality. It’s also important to find skilled workers, including programmers, managers, researchers, etc.

Top obstacles for AI in GovTech

Moreover, the public sector comes with extra challenges, such as follows:

  • Accountability. The main question related to official AI apps is «Who is responsible for the possible outcomes?». Machines can make their own decisions with often unpredicted results. That’s why an entirely new legal framework is required. Experts must develop it before the wide adoption of AI for public services.
  • Biases. Here comes the second issue. If humans create AI systems, they insert specific rules and morale into them. For governments, these rules may lead to certain inequality in providing services. This challenge is even more complicated because it’s barely possible to create a fully unbiased system.
  • Employment. Some countries have laws that protect civil servants. In this case, AI disruption can threaten human employees who don’t want to lose their positions. Still, businesses try to solve this problem for several years. The most obvious solution is to find other types of work for human employees instead of firing them.

Don’t forget about the obstacles we mentioned earlier. Governments do want to evolve and deliver better services. But they face high risks that require proper planning so it may look that they don’t try to transform. Usually, they try. But it takes a lot of time and resources.

Moving to disruption

Overall, the strategy of AI implementation is pretty similar for all industries. Feel free to check the general algorithm if you’re interested in these tools. Nevertheless, don’t hesitate to study governmental processes in more detail. They may affect this scheme on different levels, such as slower research, inability to innovate due to tech reasons, etc.

Here are three main stages with subtasks required for evolution in AI public services:

  1. Focus.
    • Understand jobs to be done.
    • Reveal current trade-offs.
    • Think about how to break trade-offs.
    • Discover specific AI use cases.
  2. Shape.
    • Develop the needed resources.
    • Set the infrastructure.
    • Implement software and hardware.
    • Change laws if needed.
  3. Grow.
    • Innovate by installing AI solutions.
    • Sunset legacy apps.
    • Transform the industry.

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Smart government use cases

In conclusion, let’s take a brief look at the successful national AI public services’ cases. Some of them are based on the local level (cities, regions), while others cover whole countries:

  • Atlanta. Researchers from universities worked closely with the city fire rescue agency to introduce a tool with predictive analytics features. Firebird can identify which buildings are likely to catch fire. It uses historical data and evaluates buildings by size, structure, location, neighborhood, etc.
  • Estonia. This country is mostly known for its e-residency initiative. However, various citizen-focused projects are successful, too. Here, people can access multiple public services online thanks to the system of digital identity. It’s possible because of automated recognition solutions based on AI, partially.
  • New York City. The local body responsible for social services has created a portal called ACCESS HRA in partnership with IBM. It allows people to manage their cases related to food support, benefits, insurance. IBM delivered AI systems based on machine learning, machine vision, and NLP.
  • Pittsburgh. The city partnered with Rapid Flow Technologies to create SURTRAC. This software controls and optimizes traffic automatically. It focuses on lower stops and reduced wait/travel times. SURTRAC is powered by machine vision that analyzes how cars are moving, where they stop, and so on.
  • Singapore. Trying to become the smartest nation, Singapore delivers various nation-wide projects. Here, the strategy of smart urban mobility intersects with self-driving vehicles. In the national healthcare industry, AI-based robots and assistants boost the quality of services and improve the patient experience.
  • The USA. The center that works with immigrants has launched an AI-powered chatbot called Emma in 2015. The tool responds to the users’ questions about citizenship and immigration, thanks to language processing and generation models. It also can train on new inquiries from customers.
Smart countries by their AI strategies

DICEUS for GovTech

Let’s finish with a straightforward question. What is the one common thing that unites several AI public services? In the majority of cases, governments had to cooperate with private companies to develop efficient solutions. The thing is it’s barely possible to revolutionize public services without a fresh look and professional development approach.

That’s why we’re here for your service. DICEUS is a company with rich experience in different areas, from healthcare to banking. Thanks to extensive geographical and domain coverage, our experts know how to work in both the public and private sectors. The recent trends of governments that evolve according to business patterns show that this experience can help greatly.If you have any questions, don’t hesitate to contact us and get a personalized consultation!