Concern 289 · Working draft · editorial review in progress
Model registry & lineage gaps
Model-registry and lineage gaps leave an organization unable to trace which model was released and how it was produced.
Understanding the concern
A model registry records versions and related information. Lineage connects a released artifact to its training run, data, code, and evaluation. Without that chain, a team may struggle to reproduce a result, identify an affected deployment, or choose a safe replacement.
A registry is useful only if its records match what is actually running. A friendly alias such as production can point to different versions over time. Important investigations need the exact artifact and configuration, not just the label users saw.
An example
A medicine cabinet contains labeled containers, but no batch records connect them to the manufacturing and testing process.
Illustrative unless identified as a documented case.
Words in plain English
- Model
- The learned part of an AI system. It uses patterns found during training to produce an answer or prediction.
- Training
- The process of using examples to shape how an AI model behaves. Learning patterns from material does not establish that the material is true or fair.
Evidence and its limits
MLflow documents version and alias workflows; NIST supports artifact provenance. The analogy does not equate model release with medical certification.
MLflow documentation · Official technical documentation
Model Registry Workflows ↗ (opens in a new tab)Describes registration, versions, aliases and deployment workflows; an alias is mutable and a registry must match actual deployment.
NIST · SP 800-218A · 2024 · Official guidance
Secure Software Development Practices for Generative AI and Dual-Use Foundation Models ↗ (opens in a new tab)Adds AI-specific lifecycle practices to secure software development; guidance does not certify a particular system.
Broader frameworks and background
These resources provide context. They do not establish every claim in this concern.
- NIST AI RMF (opens in a new tab)
framework
A question to discuss
Can we trace a live result to the exact model artifact and evidence supporting its release?
Keep track of different views, what needs checking, and any next step in your own discussion notes.
Open discussion notes →Principles for the conversation
Before you finish · reflect together
Virtues and principles to consider
Virtues are qualities we practice in how we treat people and make choices. They are not scores for judging someone. Use these ideas to explore what a thoughtful response could look like.
Stewardship
Stewardship means caring for resources and systems that others depend on, including people who will use them later. It looks beyond the benefit of a quick launch.
Plan for maintenance, energy use, data protection, and eventual shutdown. Ask who will look after the tool when the original team moves on and how future users can avoid inheriting hidden costs.
Ask together: What are we responsible for caring for over time?
Prudence
Prudence means using careful judgment before and during action. It balances worthwhile opportunities with the need to avoid harm that could have been anticipated.
Start with a limited trial, set stopping points, and prefer choices that can be undone when uncertainty is high. Review what happens rather than assuming the original plan remains sound.
Ask together: What is a careful next step, and when should we stop or change course?
Cooperation
Cooperation means working with others toward a shared purpose while respecting their contribution. It is not simply asking people to accept a decision already made.
Share information, roles, and credit. Include the people who do the daily work when choosing or testing a tool. Make disagreements discussable so that cooperation does not become pressure to agree.
Ask together: What can we do together that none of us can do well alone?
Editorial ratings
These are editorial judgments from the register, not measured probabilities or predictions about your situation.
About the register and scoring →More ways to explore
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