OpenAI · OpenAI Safety Standards · View original document ↗

Bias evaluation to avoid stereotypes in content

Medium severity High confidence Explicitdocumentlanguage Common · 144 of 352 platforms
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Recent governance activity OpenAI recorded 16 documented changes in the last 30 days.
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This analysis describes what OpenAI's agreement states, permits, or reserves. It does not constitute a legal determination about enforceability. Regulatory applicability and practical outcomes may vary by jurisdiction, enforcement context, and individual circumstances. Read our methodology

ConductAtlas Analysis

Why it matters (compliance & governance perspective)

A commitment to rigorous bias evaluation signals that content outputs are actively reviewed against a standard of stereotype avoidance, not merely passively filtered.

Consumer impact (what this means for users)

Users of OpenAI's systems can expect that content has been evaluated to avoid reinforcing biases or stereotypes.

How other platforms handle this

Tinder Medium

If you believe Your Content was removed in error, you may submit an appeal. More information is available here.

Mailchimp Medium

We review account behavior and content that Members create, send, and publish in Mailchimp, including Campaigns and Websites.

Glassdoor Medium

We allow Content that names individuals in the highest positions in a company who have broad influence over the work environment, as long as the Content describes the individual's behavior or performance at work.

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▸ View Original Clause Language DOCUMENT RECORD
"
Rigorously evaluating content to avoid reinforcing biases or stereotypes.

— Excerpt from OpenAI's OpenAI Safety Standards

Applicable regulations

California AB 2013 AI Training Data Transparency
US-CA
DMCA
United States Federal
DSA
European Union

Provision details

Document information
Document
OpenAI Safety Standards
Entity
OpenAI
Document last updated
May 12, 2026
Tracking information
First tracked
July 9, 2026
Last verified
July 9, 2026
Record ID
CA-P-064264
Document ID
CA-D-00822
Evidence Provenance
Source URL
Wayback Machine
Content hash (SHA-256)
29a3d40e8275f104584cc6bdb20b0b6a52711666f2f59ee81227d1760ed522ea
Analysis generated
July 9, 2026 04:12 UTC
Methodology
Evidence
✓ Snapshot stored   ✓ Hash verified
Citation Record
Entity: OpenAI
Document: OpenAI Safety Standards
Record ID: CA-P-064264
Captured: 2026-07-09 04:12:50 UTC
SHA-256: 29a3d40e8275f104…
URL: https://conductatlas.com/platform/openai/openai-safety-standards/provision/CA-P-064264/bias-evaluation-to-avoid-stereotypes-in-content/
Accessed: July 12, 2026
Permanent archival reference. Stable identifier suitable for legal filings, compliance documentation, and research citation.
Classification
Severity
Medium
Categories

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Frequently Asked Questions

What does OpenAI's Bias evaluation to avoid stereotypes in content clause do?

A commitment to rigorous bias evaluation signals that content outputs are actively reviewed against a standard of stereotype avoidance, not merely passively filtered.

How does this clause affect you?

Users of OpenAI's systems can expect that content has been evaluated to avoid reinforcing biases or stereotypes.

How many platforms have this type of clause?

ConductAtlas has identified this type of provision across 144 platforms. See the full comparison.

Is ConductAtlas affiliated with OpenAI?

No. ConductAtlas is an independent monitoring service. We are not affiliated with, endorsed by, or sponsored by OpenAI.