1. The Question
To what extent should a system explain its decisions?
Explainability produces trust.
Yet full disclosure is neither realistic nor desirable.
In immigration administration, certain forms of non-disclosure are unavoidable—
due to national security, diplomatic considerations, and the prevention of system abuse.
The question, therefore, is not simple.
How much should be explained?
What must remain undisclosed?
This is a problem of institutional boundary design.
2. Redefining Explainability
As defined in Chapter 8:
Trust is the condition in which individuals can understand, anticipate, and rely on institutional decisions.
From this follows the role of explainability:
Explainability is the ability to present the structure of a decision in a way that is understandable.
It is not equivalent to transparency.
Explainability requires that individuals can grasp:
- What factors were considered
- What perspectives were applied
- Why the decision was reached
Understanding—not full disclosure—is the objective.
3. Why Full Transparency Fails
Complete transparency appears ideal,
but it can destabilize a system.
There are three primary risks:
- Exposure of strategic vulnerabilities
- Gaming of the system through formal compliance
- Loss of adaptive discretion due to rigid rule-following
For this reason:
Full transparency does not necessarily produce trust.
It can undermine the system itself.
4. Conditions for Legitimate Non-Disclosure
Non-disclosure is not inherently justified.
It must meet specific conditions.
In this model, non-disclosure is acceptable only if:
(1) It does not undermine explainability
The logic of the decision must remain understandable.
(2) It does not conceal arbitrariness
Non-disclosure must not function as a cover for irrational decisions.
(3) It preserves verifiability
Internal review or third-party oversight must remain possible.
In other words:
Non-disclosure is not an alternative to trust.
It is a controlled exception within a trust structure.
5. The “Explainable Black Box”
This boundary is operationalized through the concept of the:
“Explainable Black Box.”
Not everything can be disclosed.
But nothing can be left entirely unexplained.
A system must ensure that:
- The existence of evaluation criteria is visible
- The direction of decision-making logic is indicated
- Case-specific reasoning is provided
Through this approach:
Understanding can be achieved without full visibility.
6. The Boundary of Discretion
As discussed in Chapter 9, discretion is unavoidable.
The problem lies in its lack of structure.
Here, explainability plays a defining role:
Explainability establishes the boundary of legitimate discretion.
- Discretion that can be explained is structured
- Discretion that cannot be explained is indistinguishable from arbitrariness
Therefore:
Explainability is the condition that allows discretion to exist without producing distrust.
7. Institutional Implications
This design aligns with key principles of administrative law.
In particular:
- Review of the decision-making process
- Obligations to provide reasons
- The legitimacy of authority (presumption of validity)
These principles suggest that:
Authority becomes trustworthy only when its reasoning is accessible.
Without explanation, authority appears as imposition.
With explanation, it becomes a basis for reliance.
8. Implications for Social Integration
Immigration decisions are not merely procedural outcomes.
They shape individuals’ lives, expectations, and sense of belonging.
When decisions are understandable,
individuals retain the capacity to accept outcomes—
even unfavorable ones.
When decisions are not understandable,
distrust extends beyond the system to society itself.
Therefore:
Explainability is a precondition for social integration.
9. Conclusion: Designing the Boundary
The central conclusion of this chapter is clear:
The issue is not transparency versus secrecy.
The issue is how to design the boundary of explainability.
A system must avoid both extremes:
- Total transparency
- Total opacity
What is required is:
A designed boundary that preserves trust while maintaining system integrity.
*This post is positioned as a chapter that makes up the table of contents in the Balanced Coexistence Model.