Cannot explain the results.
AI becomes difficult to trust in audit, reporting, and complaint-handling situations.
Strange results occur only in specific situations.
Bias builds up quietly. By the time it’s discovered, the problem has already occurred.
Unable to track what changed.
Even if the results change after a model update, there’s no way to find the cause.
AI Reliability
We put recognized
AI safety principles into practice.
Even if AI makes the judgment, the responsibility for the final decision lies with people.
Governance Committee
Assign person in charge
Mandatory approval process
>It is designed so that the same conditions always produce the same result.
Model Card
Data documentation
Log-based reproducibility verification
Provides the basis for judgment and influencing factors along with the results.
Output score + supporting text
Pre-disclosure of evaluation criteria
Design it so that a person can intervene and stop it when a problem occurs.
Real-time monitoring
Reporting Channel
Discontinue use if abnormalities occur.
All changes can be recorded in history and tracked with an approval process.
Change Approval Process
Document retention
Periodic revalidation
Agents are managed according to agent-specific criteria.
Delegation scope control
Orchestration tracking
Decision Path Audit
AI Ethics
Ethics is not a declaration,
it is a managed system.
Based on the ethics checklist developed with the government agency KISDI,
we manage the entire process from design to operation.
01
Human rights protection
We respect users as individuals and do not discriminate for any reason.
02
Privacy protection
We minimize personal data collection and destroy it properly upon request.
03
Respect for Diversity
Recognize the possibility of bias in AI models and take control measures to ensure fairness.
04
Infringement prohibited
Diverse experts label data, with training and verification minimizing bias.
05
publicness
We support users’ rational decision-making and continuously review social impacts.
06
Solidarity
We reflect stakeholder input and partner with external and government bodies.
07
Data management
We manage data systematically and destroy it properly once its purpose is fulfilled.
08
Accountability
We designate ethics officers with clear accountability and improvement procedures.
09
Safety
If an error occurs, we will notify you immediately and take prompt follow-up action.
10
Transparency
We disclose AI's scope and limitations upfront and respond fully to explanation requests.