Artificial intelligence (AI) is entering people's daily lives at a rapid pace, especially with the already well-known chatbots (Bard, ChatGPT, etc.), and this raises the question of its use in the state. The ability of AI algorithms to analyze a large amount of data makes them perfect candidates for facilitating a large number of tasks of the state administration, BGNES reported.
Countries such as Italy, the US, and Australia have already implemented certain models of AI in various parts of their administration. With AI gaining popularity, Bulgaria also intends to integrate it into its state institutions. The Ministry of Electronic Government (MEG) is currently developing 3 AI integration strategies: in the education system, healthcare, and social economy.
The introduction of AI in the Ministry of Education envisages the integration of "High-Tech Equipped and Connected Classrooms" (HICs) in schools. These "smart classrooms" will serve to more quickly introduce educational innovations in learning and teaching in the field of natural sciences. The participation of AI in the improvement of the learning process among Bulgarian students is logical, considering the digital VOSKS.
The Ministry of Health has submitted a project for a "National Digital Platform for Medical Diagnostics". This project would utilize the high capacity of AI to handle large amounts of data.
The Ministry of Labor and Social Policy, for its part, is planning the introduction of a "Platform with adaptive-analytical software, with the possibility of self-learning, processing, and analysis of social and solidarity economy data".
Bulgaria plans to adopt new technologies more similarly to most countries, facilitating data processing. These strategies were shared by the Minister of e-Government, Alexander Iolovski, answering a parliamentary question. Bulgaria has a large number of examples of this type of innovation to draw experience from.
The Italian Ministry of Labor and Social Policies has launched its "chatbot" to provide information on the guaranteed minimum income program. The ministry found the chatbot a success and later expanded the scope of the service to communicate with citizens.
In a country that has long struggled with high rates of tax evasion, the new tool has given the country's tax fraud unit a rare advantage in the fight against it. They could automate the analysis of proprietary databases to match citizens' income statements with their other assets, such as bank accounts, asset management companies, insurance policies, and pleasure properties.
The algorithmic approach cross-checks databases to flag potential fraud for people on the team to follow up on. This approach protects citizens' data until evidence emerges to warrant a closer examination. People are always assessing which cases require further investigation - a "man in the loop" approach required by legislation. This contributed to a significant improvement in Italy's tax evasion rate, breaking the vicious cycle between lost tax revenue and declining government services.
Another example that could be directly compared to the Bulgarian strategies is the Australian "Rapid, Emergency, Disease and Syndrome Diagnosis in the Field of Public Health" (PHREDSS). PHREDSS monitors patients' symptoms in hospitals every day. Unusual patterns could indicate an outbreak of disease or a problem of public health concern in the population. PHREDSS is also useful for monitoring the impact of seasonal and known disease outbreaks, such as seasonal influenza or gastroenteritis. Doctors receive regular reports from PHREDSS, leaving them more time to deal with the actual treatment of patients, rather than hours of reading and synthesizing data.
AI "assistants" will increasingly enter the states, especially after the adoption of the EU AI regulation law. Regulation of new technology will allow a framework for innovation, with data processing only being part of the "bonuses".
A place for innovation would be in traffic analysis. Especially with the high rate of road accidents in the country. The US Department of Energy has developed the Transportation State Estimation Capability (TranSEC). It uses machine learning to analyze traffic flow, even from incomplete or sparse traffic data, to provide real-time street-level estimates of vehicle movement. Such tools would help law enforcement officers locate high-risk areas. This would hasten the response time and warming of the road arteries.
Adaptation to the new environment is inevitable, as the new tools will become increasingly ambitious in their capabilities. Strategies for introducing new technologies will become increasingly imperative. This will bring with it the need for new qualifications and risks for professions affected by AI. /BGNES
