Milestone in Türkiye’s Artificial Intelligence Strategy: Data Management and Security in the Public Sector
The challenges facing the Ministry of Industry and Technology include not only technological but also institutional and ethical dimensions. The General Directorate of National Technology and Artificial Intelligence not only develops artificial intelligence policies through data centers and cloud infrastructure; It establishes a comprehensive framework for reliability, openness and auditability in public services. This transformation not only increases technical capacity, but also makes the use of artificial intelligence in accordance with data governance, good governance and ethical principles a central goal.
Strategic Transformation in Artificial Intelligence Infrastructure: Data Center and Cloud Computing
Strengthening data centers and cloud computing infrastructure across the country forms the cornerstone for accelerating artificial intelligence projects. With policy recommendations and coordination processes, technical standards, security requirements and control mechanisms are clarified. In particular, limits and permissions for data flow that protect data security and national interests are clearly determined. In this context, quality control, data classification and access management throughout the data lifecycle are vital.
Ethical and Safe Artificial Intelligence: Transparency and Accountability in Public Services
The use of artificial intelligence in accordance with ethical principles is not only a technological choice, but is seen as the basic building block of public security. Trustworthy AI is supported by bias-reducing datasets, transparent model documentation, and processes that enforce user notification. Human-centered design integrates with security architecture, offering transparency and auditability in decision processes. Additionally, thanks to R&D supports and international collaborations, global best practices are integrated into Türkiye’s capacity.
Public AI Applications and Data Management: Standards, Quality and Compliance
As the center that manages the state’s artificial intelligence applications, the General Directorate of Public Artificial Intelligence plays a leading role in updating the legislation and implementing national policies and strategies. In this context, data governance principles, procedures and standards are determined. In line with the digital state vision, standards are applied for every stage of the data life cycle. It is planned to establish a common data infrastructure for public institutions, and the quality criteria of the data used in artificial intelligence applications are defined and inspected. Thus, the reliability and accuracy of decision support systems in public services are strengthened.
Strengthening Data Security and Access Control
Data security is not just a technical measure; it is also a critical requirement for public safety and citizen trust. While access management policies are clarified, a minimum necessary approach is adopted with the principle of minimizing personal and corporate data. In this way, shadow tables and unauthorized access risks are reduced and audit trails are strengthened. In addition, the reliability of the infrastructure is increased with standardized certification and authorization processes.
International Cooperation and R&D Investments
International collaborations strengthen the aim of harmonization with high quality standards. Supporting R&D activities increases the global competitiveness of the domestic ecosystem. Through data sharing and joint projects, both the public and private sectors can quickly adopt best practices. In addition, a solid basis for the data economy is created through national data field studies and data quality criteria are updated periodically.
Unified Standards and Implementation Roadmap
Within the scope of the new structuring, technical standards and criteria are determined; certification and authorization processes become clearer. These steps create a harmonious ecosystem for data centers and cloud infrastructure. In addition, thanks to the coordination focused on public projects, projects are implemented on time and within budget. This roadmap aims to establish an ecosystem that results in data quality and secure AI applications.
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