It’s hard to believe that just 30 years ago, the small Baltic state of Estonia was lacking many of the services modern governments take for granted. Nowadays, the country has not only bounced back from decades of Soviet administration but become a model for the way digital transformation can boost efficiency, security, transparency and inclusivity in the public sector. What’s more, innovation is booming: Estonia boasts six times more start-ups per capita than elsewhere in the European Union.
Artificial intelligence use cases for government include:
99% of public services in Estonia are available as e-services, and Estonia continues to invest heavily in technology and artificial intelligence for the public sector. Let’s take a look at some of the most interesting artificial intelligence government applications currently being explored in Estonia.
Artificial intelligence for government can streamline communication
Named “Kratt” after a creature from old Estonian folklore, the 2019 Estonian AI strategy aims to boost the uptake of AI by both the public and the private sector. The strategy will invest at least 10 million euros over a three-year period.
The Estonian government has laid out a vision for how it intends to use AI to benefit both the public and private sectors. As part of the strategy, the government will take a leading role in promoting and accelerating the use of AI-based applications. #KrattAI will focus on four main pillars, boosting the uptake of AI in government, the economy, research and development and the legal sector.
In order to develop the strategy, the government looked at how citizens interact with public services and the challenges they can face. It found that people are often uncertain of which government agencies they need to contact. What’s more, they tend to be unaware of many opportunities offered by the government. Communication between public service agencies and citizens was more often than not time-consuming and ineffective.
In order to make public services easier to use and to better structure communication, #KrattAI aims to create a system in which citizens will be able to get all the information they need in one session, using one device, via a virtual assistant. The strategy foresees the development of open-source chatbots, an authentication system that will enable the use of private sector digital channels (such as WhatsApp or Facebook Messenger), speech synthesis applications and a consent management platform.
Reducing tax fraud with artificial intelligence for government
Taxes enable governments to finance public sector initiatives and create national environments that are conducive to economic growth. Unfortunately, tax fraud remains a major issue in Europe. According to official statistics, European Union member states lose up to 190 billion euros a year to tax avoidance and evasion. Estonia is no exception: the Estonian Tax and Customs Board (ETCB) calculated that in 2019, the nation had lost 134,1 million euros of tax revenue in non-reported or under-reported income.
Unfortunately, the processes currently employed by many national tax agencies, such as document processing and reporting, are time-consuming, repetitive and slow. Artificial intelligence can help agencies detect fraud more efficiently with fewer false positives, enabling public servants to dedicate their time to high-value tasks while building a trust-based relationship with taxpayers. The ETCB is currently seeking to create an AI-based “human-in-the-loop” system that will not only enable more efficient tax fraud detection but also increase accuracy over time.
This will enable more accurate identification of potential fraud and streamline operations of both analysts and auditors.
According to the OECD, AI will eventually free up nearly one-third of government agents’ time. Indeed, one of the major benefits of AI is its ability to enable tasks to be performed more efficiently by fewer people. This is of particular interest to law and tax enforcement authorities, which are often faced with high volumes of appeals to process and limited human resources.
AI can help create personalized learning paths for students
Education is another field in which resources are limited, but needs are consequential. Each pupil is different, yet teaching in public school systems the world over tends to be geared to the needs of the “average” student, rather than customized to individual learning requirements.
The Estonian Education and Youth Authority has begun to explore the use of AI to create personalized learning infrastructure. The infrastructure aims to support the creation of customized learning paths without placing an extra burden on the teaching staff. To do this, learning analytics are used to interpret students’ learning behaviour, i.e the way they learn, what inspires them and what holds them back. The infrastructure will provide students with personalized suggestions to improve the way they learn, and teachers with diagnostics about students that will enable them to intervene as soon as help is needed, rather than when a student starts to struggle.
Artificial intelligence government applications include emergency response
If there’s one thing that has been brought to light by the 2020/2021 health crisis, it’s a worldwide lack of disaster preparedness. The need for a timely, coordinated response isn’t just imperative when it comes to pandemics. It also applies to large-scale weather events, natural catastrophes, geopolitical tensions and terrorist attacks alongside personal accidents and emergencies, whether at a local, national or global scale.
When disaster strikes, the ability to respond immediately, precisely and effectively is vital. At this point in time, the emergency notification process tends to be extensive and complex. When a person calls the emergency services to report an incident, a lot of valuable risk assessment time is lost on trying to understand exactly what the situation is. Callers in panic are not always able to provide objective, relevant information, while call quality and background noise can affect dispatchers’ ability to accurately evaluate a situation.
According to recent Microsoft research into the California wildfires, AI is one of the most effective ways to minimize the fallout from major incidents. The study states that “More adoption of AI could enable emergency management agencies to rally more precise responses to events more quickly, potentially saving lives and reducing property damage, or to cut costs on preventative capital improvement projects.
AI can help dispatchers identify the nature of an incident, how serious it is and flag a need to request additional information. This enables emergency center staff to ensure that the right kind of help is sent as soon as possible. The Estonian Emergency Response Center, which handles around a million calls per year, is developing a solution that uses AI to make risk assessment decisions faster and automate contact center operations.
Analyzing calls using text-to-speech and sentiment analysis enables the Estonian government to respond better to emergencies. But at the same time, it helps public agencies understand query patterns and take pre-emptive action to explain and handle issues.
Using AI-based road traffic accident risk prediction to reduce accidents
Similarly, a road accident prediction project is providing valuable information on how to reduce and prevent traffic incidents. The figures are sobering: in 2018, 67 people died and 1,832 were injured on the Estonian roads. The number of serious road accidents with victims has fluctuated between 1,300 and 1,500 since 2010.
When we think of AI and road traffic, it’s often in relation to self-driving vehicles. But AI has several applications when it comes to improving road safety. Towns across the world are implementing AI solutions to monitor and optimize traffic as part of “smart city” initiatives. AI can also help predict, prevent and reduce road accidents by analyzing the root causes of traffic accidents and what makes them more or less severe. Thus, cities can develop transport systems that enable sustainable mobility and shape safe attitudes and behaviour on the part of drivers. Over in Estonia, the Estonian Road Administration is developing an accident prediction model that analyzes the risk, severity, and causes of traffic accidents. The solution will draw on multiple sources, such as traffic offenses, traffic accidents, weather conditions, locations of police vehicles, traffic count data and road register data.
According to the Estonian Government Chief Data Officer, Ott Velsberg, “We need to rethink how to make the government as lean, as proactive and as personalized as possible“. Estonia’s heavy AI investments are putting the country on the right path: AI for government can help the public sector design better policies, improve decision-making, and boost communication and engagement with residents. What’s more, it can improve the efficiency and all-round user-friendliness of services.
But AI can go beyond improving services and reducing bureaucracy. It also helps governments respond better to emergency situations, prevent them from happening in the first place and come to the aid of their citizens when they need it the most.
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