AI data retention
The rules governing which AI inputs, outputs, logs and derived records remain in a system, for what purpose, and for how long. Not using data for training does not mean that it is not stored.
- Separate controls
- Training use, storage duration, access, deletion
- EU principle
- GDPR Article 5(1)(e): storage limitation
OpenAI's API documentation separates its default no-training policy from abuse-monitoring retention and feature-specific application state. Commercial and consumer products may have different terms.
A product needs a copy ledger covering application storage, logs, providers, indexes, exports and backups. Verify deletion and restoration behavior rather than treating a removed chat bubble as proof.
Connected
- Zero data retentionA provider arrangement limiting storage of eligible AI request content, subject to approval, feature coverage and documented exceptions. It does not remove records retained by the customer's own application.
- AI training-data consentWhether and how a company asks users before using their data to train or improve AI models; shaped by the FTC's 2024 warning on retroactive terms changes and GDPR's right to object.
- Agent evaluationRepeatable testing of an AI agent's complete task, tool use, permissions and final system state against explicit acceptance criteria. A successful demo is not a production reliability estimate.
Linked from
Field notes that cover AI data retention
More concepts & methods
- machine learningscientific study of algorithms and statistical models that computer systems use to perform tasks without explicit instructions
- deep learningspecialized form of machine learning that uses artificial neural networks to identify patterns in data
- genetic algorithmcompetitive algorithm for searching a problem space
- Altitude, depth and rangeFelix Rieseberg’s framework for ambition with AI models: speed repeats work faster, altitude targets outcomes, depth uses expert instruments and range combines disciplines.
- Outcome-based promptingAsking an AI agent to pursue a specified change for a user or system, with evidence and boundaries, instead of merely producing a named deliverable.
- AI outside judgeAn acceptance check outside an agent’s self-assessment, such as a deterministic test, held-out evaluation, measurement or separately briefed reviewer.