The introduction of AI in public institutions is no longer a futuristic experiment. From automated civil complaint response and welfare beneficiary selection to crime prediction and even traffic and urban management, AI is rapidly expanding, driven by its promise of administrative efficiency. However, AI in the public sector differs from corporate services. Fairness, accountability, and public trust must take precedence over efficiency. When this balance is disrupted, technology becomes the seed of social conflict, not innovation.

Key Trends Related to AI Adoption in Public Institutions

The recent trends in AI adoption in the public sector can be summarized into three categories.

First, there is the spread of automation-focused AI that replaces repetitive administrative tasks.

Second, the introduction of a data-based decision-making system to assist policy decisions.

Third, there is an increase in interactive AI administrative windows that interact directly with citizens.

The problem is that all of these trends are often discussed in a technology-centric manner, with designing for social impact often following suit.

The Impact of AI in Public Institutions on Society

AI in public institutions has direct consequences for citizens' lives. As AI intervenes in decisions like welfare eligibility, administrative dispositions, and support recipient selection, even a single error can impact individuals' livelihoods and rights. In particular, because public institution decisions involve "coercion" rather than "choice," AI's judgments operate not as mere recommendations but as de facto administrative power.

Social issues that are easy to miss

The following issues are frequently overlooked when implementing AI in public institutions.

• Institutionalization of algorithmic discrimination: AI learns from past data. If discrimination inherent in existing systems is reflected in the data, AI will reproduce it with increasing sophistication.
• Lack of clarity about responsibility: When problems arise due to AI decisions, it is often unclear who is responsible: the developer, a government official, or an organization.
• Unexplainable Administrative Decisions: Citizens have the right to demand explanations for administrative decisions. However, if AI's decision-making process cannot be explained, the legitimacy of the administration is undermined.
• Digital Accessibility Gap: For seniors, people with disabilities, and digitally vulnerable populations, AI-based administrative services could be another barrier rather than a convenience.
• Potential expansion into a surveillance society: If data collected for efficiency reasons is turned into surveillance and control, public AI will breed fear, not trust.

Response strategies and institutional design directions

AI in public institutions should be approached as a governance project, not a technology project, and requires the following strategies:

First, we need to institutionalize a social impact assessment before introducing AI.

Second, the ultimate responsibility structure for all AI decisions must be clearly established.

Third, the possibility of explanation at a level that citizens can understand must be guaranteed at the UX and institutional levels.

Fourth, the choice not to adopt AI should also be respected as a policy option.

Commonalities in Public AI Discussions Worth Noting

Rather than emphasizing the technology's potential, discussions about mature public AI first define areas where it should not be used. Furthermore, they clearly position AI as an "assistant," not a "decision-maker." Successful cases share a common characteristic: investing more time and resources in trust-building processes than in the systems themselves.

Insight Summary

AI in public institutions is both a tool for increasing efficiency and a force for restructuring social structures. It's not the technology itself that creates problems; it's its introduction without control and accountability that becomes problematic. The key to the success of public AI lies not in smarter algorithms, but in more mature social consensus and design.