DAIXIS™
Governance for scientific interpretation.
AI systems generate outputs.
Organizations make decisions.
Between those two steps, interpretation assigns meaning.
The decision was never the problem.
The interpretation was.
Embedded Files
The Unowned Layer
In real-world decision workflows, outputs are simplified, labeled, and communicated until they become actionable.
During this process, language changes.
Certainty shifts.
Assumptions are introduced.
The underlying data do not change.
But the conclusions do.
This is the Unowned Layer:
The space between output and decision where interpretation occurs without formal control.
How It Works
DAIXIS evaluates how interpretation changes as information moves from output to decision.
It identifies where meaning shifts beyond what the evidence supports.
Evidence vs Narrative Alignment
Does the conclusion reflect the underlying data, or the story built around it?
Causal Language Expansion
Are associations being presented as causes?
Mechanistic Certainty
Is biological or technical explanation overstated?
Assumption Stacking
Are layered assumptions driving conclusions?
Translational Risk
Does the final message extend beyond what can be defended?
Interpretation is not evaluated for correctness alone.
It is evaluated for how it changes meaning.
Core Principle
Core Principle
DAIXIS does not determine truth.
It identifies when interpretation extends beyond what the evidence can support.
Why It Matters
Why It Matters
Failures in AI-assisted workflows rarely come from the data.
They come from how the data are understood.
Decisions are made based on interpretation,
not generation.
Without governance, interpretation becomes the most influential
and least controlled step in the process.
Interpretation turns uncertainty into decisions.
DAIXIS prevents decisions from moving beyond their evidence.
DAIXIS is applied through DumstorfAI consulting engagements in real-world scientific and Medical Affairs environments.
For organizations working with AI-assisted scientific decisions:
info@dumstorf.ai
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