Responsibility Attribution

Responsibility attribution is an AI UX pattern that labels which human, agent, or model version caused each action or edit. Teams can answer “who did this?” without digging through raw logs.

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Interactive demo

Run · Customer update → History

Run history

Who did what on this customer update

Selected step

Ops Assistant: Drafted update from CRM and support logs

Overview

The design problem

How might we design responsibility attribution so people can trust and act on AI output?

Use this pattern

When this pattern fits

  • Essential for multi-agent systems, enterprise automation, and shared collaborative environments where clear accountability across agents and humans is required for audits, incidents, and trust.

Avoid this pattern

When to skip or lighten it

  • Solo sandboxes where a single user is always the actor.
  • Anonymous public demos where identity is intentionally absent.
  • High-volume telemetry where per-event attribution UI would overwhelm (summarize instead).

States

State model coming soon

Key UX elements

Key UX elements coming soon

Anti-patterns to avoid

  • Commits or edits marked only as “AI” with no model or agent id.

  • Human users taking blame for silent agent side effects.

  • Attribution that disappears after merge or publish.

  • Ambiguous co-author tags that mix reviewer and generator.

How products use it

ProductImplementation
GitCo-authored-by trailers for human and tool contributors.
GitHubCommit and PR attribution including Copilot-assisted changes.
Stripe RadarEvent logs that separate system and human decisions.
KubernetesAudit logs naming user, service account, and verb.

Implementation

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Pattern Definition:

Frequently asked questions

What is responsibility attribution in AI UX?

It is UI and metadata that records which person or agent produced an action, so accountability stays clear when AI and humans collaborate.

Where should attribution appear?

On diffs, activity feeds, receipts, and exported artifacts. Hover cards can show agent version and approving human.

How does it differ from an audit trail?

Attribution is the actor label on each change. An audit trail is the full chronological record. Attribution is the readable tip of that record.

Should AI be listed as author?

Yes, with agent identity and the supervising human when approval was required. Do not pretend the human typed machine output.

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