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A living record of our commitments to responsible AI. From founding charter to framework v3.0 — every milestone, audit, and policy decision documented in the open.
Founding commitment to responsible AI. Established core principles for transparency, fairness, and accountability across all lab operations.
Baseline measurements across 3 models. Evaluated demographic parity, equalized odds, and calibration metrics to establish benchmarks.
5 independent experts appointed. Includes ethicists, civil rights advocates, and technical safety researchers from leading institutions.
Standardized red-team evaluation launched. Covers adversarial prompting, jailbreak resistance, and harmful content generation testing.
First public disclosure of practices. Detailed model capabilities, limitations, training data sources, and known failure modes.
Independent third-party review. Comprehensive assessment of governance practices, bias mitigation efforts, and safety protocols.
Enhanced consent and provenance tracking. Implemented full data lineage documentation and opt-out mechanisms for data subjects.
Public incident reporting launched. Created structured channels for external stakeholders to flag concerns and track resolutions.
Comprehensive update aligned with EU AI Act. Integrated risk classification, conformity assessments, and mandatory documentation requirements.
Core governance document outlining principles, risk assessments, and decision-making frameworks for all AI development and deployment activities.
Requirements for model cards, technical documentation, capability disclosures, and limitation reporting for every model released.
Testing and monitoring standards for identifying, measuring, and reducing bias across protected demographic groups in model outputs.
Red-team and adversarial testing procedures including jailbreak testing, harmful content evaluation, and capability boundary assessment.
Sourcing, consent, and privacy standards governing data collection, storage, usage rights, and individual opt-out mechanisms.
Classification and response process for AI-related incidents including severity tiers, escalation paths, and public disclosure timelines.