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Anthropic continue upholding these principles
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These are Anthropic's formal voluntary commitments made in coordination with the White House in 2023, representing a key industry governance milestone alongside similar pledges from OpenAI, Google, and others.
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Summary
This page outlines Anthropic's voluntary commitments to responsible AI development, including safety research, transparency, and policy engagement. It reflects pledges made as part of broader industry efforts coordinated with governments to ensure AI is developed safely and beneficially. The commitments cover areas such as red-teaming, safety research sharing, and societal harm mitigation.
Key Points
- •Anthropic commits to investing in safety research including interpretability, alignment, and evaluations before deploying frontier models.
- •Pledges include sharing safety information with governments, industry peers, and civil society to support responsible AI development.
- •Commitments include red-teaming and rigorous testing of AI systems to identify risks before and after deployment.
- •Anthropic promises to develop technical mechanisms to help users identify AI-generated content and prevent misuse.
- •These voluntary commitments were part of a broader White House-coordinated initiative with major AI companies in 2023.
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| Page | Type | Quality |
|---|---|---|
| AI Policy Effectiveness | Analysis | 64.0 |
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# Anthropic’s Transparency Hub
A look at Anthropic's key processes, programs, and practices for responsible AI development.
[01Model Report](https://www.anthropic.com/transparency/model-report) [02System Trust and Reporting](https://www.anthropic.com/transparency/system-trust-reporting) [03Voluntary Commitments](https://www.anthropic.com/transparency/voluntary-commitments)
## Executive Summary
Last updated January 29, 2026
Below is information about how we are meeting and working towards our [voluntary commitments](https://www.anthropic.com/transparency/voluntary-commitments#list-of-voluntary-commitments). Our experience with multiple voluntary frameworks has revealed consistent themes, as well as considerable overlap in their core requirements around safety, security, and responsible development. We are providing an overview organized by key areas of focus. We [welcome feedback](mailto:transparency@anthropic.com) from the AI community and policymakers to inform our future work.
## Risk Assessment and Mitigation
### Responsible Scaling Policy
In September 2023, we published the first version of our [Responsible Scaling Policy](https://www.anthropic.com/news/announcing-our-updated-responsible-scaling-policy) (RSP), our framework for managing potential catastrophic risks from models.
The policy is centered around implementing safeguards which are proportional to the identified risks. As AI models become more powerful, they require stronger protections. When models reach certain capability thresholds, we will implement additional safeguards around security and deployment.
The RSP is designed to evolve as our understanding of AI risks improves, while maintaining this fundamental commitment to safety. It serves both as our internal guidebook and as a model for industry-wide safety standards.
[Related Commitments](https://www.anthropic.com/transparency/voluntary-commitments#list-of-voluntary-commitments): G7 Hiroshima Process International Code of Conduct; AI Seoul Summit's Frontier AI Safety Commitments; Seoul AI Business Pledge
### Risk Identification
Anthropic works to identify a wide spectrum of potential risks from AI systems:
- For catastrophic risks addressed in our [Responsible Scaling Policy](https://www.anthropic.com/news/announcing-our-updated-responsible-scaling-policy) (RSP), we have identified Capability Thresholds, which correspond to different levels of required security and deployment measures. We have adopted capability thresholds for CBRN weapons and autonomous AI research and development.
- We also study and assess risks in other domains, including cybersecurity; autonomous capabilities; societal impacts like [representation](https://www.anthropic.com/research/towards-measuring-the-representation-of-subjective-global-opinions-in-language-models) and [discrimination](https://arxiv.org/abs/2312.03689); and [
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