Data-centric solutions in the public sector may improve the quality of social services

Algorithms for the collection and processing of large data flows may resolve social problems in the regions. However, a high-level transparency shall not violate personal (private) boundaries. This was concluded by the participants of the session Data in Service of the State and Society: Trajectories of the Future held on June 8 at the St. Petersburg International Economic Forum (SPIEF 2019).

"70% of people in the country are dissatisfied with the quality of social services. This is therefore a new opportunity for us to render quality and timely assistance owing to interdepartmental interaction and big data communication," General Director of the Agency for Strategic Initiatives (ASI) Svetlana Chupsheva said.

Regional and federal authorities will organize a model based on big data-driven algorithms so that people in need of social services can receive targeted assistance without undue delay.

"Big data and communication within one system provide the ability to reduce the time limits manyfold and provide services of absolutely new quality," the head of the ASI added.

Several regions have already commenced to cope with social problems using digital solutions.

"We would like data-centric solutions to be used in the public sector more seriously," the Head of the Sakha Republic (Yakutia) Aysen Nikolayev stated. "Within the terms of the ASI's contest of digital solutions, we had important projects related to the region specifics: considerable dispersion and remoteness of localities from each other, as well as the need to provide healthcare to the population. To optimally provide people with medicines and medical services, as well as to analyze the reach of healthcare, such solutions were offered. I consider this very important."

Yakutia also places its stake on the modernization of the public administration system.

"In our region, we have already introduced big data positions for regional managers (CDO – Chief Data Officer); we also have Ñhief Information Officer (CIO) for information technologies and Chief Digital Transformation Officer (CDTO) responsible for process transformation in the entire region. There is no retreat: we have to address the problem. Such regions as ours may benefit from digitalization, use of data base management, as well as adoption of artificial intelligence in public and municipal administration even more than heavily populated regions," Aysen Nikolayev noted.

According to the Special Representative of the Russian President on Technological Development, Director of the ASI's Young Professionals direction Dmitriy Peskov, the current infrastructure is poorly adapted for big data processing.

"The data we use these days is primarily accumulated by banks, telcos, search engines, and, occasionally, state authorities because they have historically had such data and have easy access to customers. Why not work with them. However, the percentage is tiny, much less than 1% of the data available to us. The current infrastructure – whether organizational, technological, or physical – is in principle not able to process or accumulate the data surrounding us. During the day, a human can generate tens of terabytes of raw data – appearance, gait, decisions made. However, when it comes to raw data collection, the modern infrastructure proves to be incapable of this," Dmitriy Peskov said.

Another issue is lack of clear boundaries protecting against the invasion of artificial intelligence on privacy.

"The legislation has deficiencies as it fails to define data – big data or open data – and how to depersonify it to remove personal information. So where are the boundaries – what data may or may not be collected for ethical reasons? There is no clear borderline between the tasks that may be relegated to algorithms and artificial intelligence and those that can only be performed by humans," Svetlana Chupsheva emphasized.