Data Accountability, Privacy & Protection

Data Accountability, Privacy & Protection connects policies to decision rights and enforceable safeguards. Owners, stewards and custodians have distinct obligations; permitted purpose, lifecycle use, classification, retention and contextual permissions govern both source and derived AI assets.

Connect AI data use to ownership, permissions, privacy and protection. Make responsibilities visible where information moves between people, systems and agents.

Why this matters

Permission to collect or read information does not automatically permit training, retrieval, logging, memory or action. Derived stores can preserve sensitive information after the source has changed or been deleted.

Questions to bring to the work

• Who can approve this purpose, access exception or change to a critical definition?
• Do permissions, correction and deletion obligations reach every relevant derived store?

Explore this chapter

Turn policy intent into usable standards and specify who may interpret the rule, approve a purpose or grant an exception.

Separate ownership of business meaning and acceptable use from stewardship coordination and custody of storage, access and protection.

Use RACI to clarify consequential data decisions such as purpose changes, definitions, agent access, quality exceptions and deletion.

Test permitted purpose and lifecycle obligations separately for training, evaluation, retrieval, inference, logging and memory, including derived-store deletion.

Apply classification and protection to prompts, context, embeddings, memory, outputs and logs as well as original databases and documents.

Evaluate access against task, purpose, jurisdiction and delegated authority, with owned, time-bound exceptions and usable escalation.

What useful evidence looks like

• Decision-specific ownership or RACI assignments, permitted-purpose records and lifecycle boundaries.
• Access, retention, deletion and exception tests across source data, indexes, prompts, logs and memory.

Move from understanding to practice

Framework source

Editorial adaptation from the supplied AIDIVE Version 1 master documents.

• AIDIVE Data Dimension Version-1.docx · D.3 Data Accountability, Privacy & Protection; AIDIVE Data - Practices & Playbook Version-1.docx · AR-D07, AR-D08, AR-D09

Data

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