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Announcing our updated Responsible Scaling Policy · Anthropic News
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11.25C32.8339 11.6639 32.4979 11.9996 32.084 12H7.91699C7.50282 12 7.16706 11.6642 7.16699 11.25C7.16699 10.8358 7.50278 10.5 7.91699 10.5H32.084Z" fill="currentColor"></path></svg></button></div></div></header><main id="main-content" class=""><article><div class="page-wrapper PostDetail-module-scss-module__UQuRMa__hero"><div class="PostDetail-module-scss-module__UQuRMa__header"><div class="PostDetail-module-scss-module__UQuRMa__subjects body-3 bold"><span>Announcements</span></div><h1 class="headline-1 PostDetail-module-scss-module__UQuRMa__title">Announcing our updated Responsible Scaling Policy</h1><div class="body-3 agate">Oct 15, 2024</div><div data-theme="ivory"><a href="http://anthropic.com/rsp " class="Button-module-scss-module__f9ZZrG__button Button-module-scss-module__f9ZZrG__large Button-module-scss-module__f9ZZrG__primary" target="_blank" rel="noopener"><span class="body-3">Read the Responsible Scaling Policy </span></a></div></div><div class="PostDetail-module-scss-module__UQuRMa__illustrationHeroWrapper"><img alt="A hand with a feather quill writing a policy document. " width="5760" height="3240" decoding="async" data-nimg="1" class="PostDetail-module-scss-module__UQuRMa__heroImage" style="color:transparent" srcSet="/_next/image?url=https%3A%2F%2Fwww-cdn.anthropic.com%2Fimages%2F4zrzovbb%2Fwebsite%2Ff1664b95be4e2e828a180cf9f015a0b6f8365472-5760x3240.png&amp;w=3840&amp;q=75 1x" src="/_next/image?url=https%3A%2F%2Fwww-cdn.anthropic.com%2Fimages%2F4zrzovbb%2Fwebsite%2Ff1664b95be4e2e828a180cf9f015a0b6f8365472-5760x3240.png&amp;w=3840&amp;q=75"/></div></div><div class="page-wrapper"><article><div class=""><div class="Body-module-scss-module__z40yvW__body" data-theme="ivory"><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"><strong>Today we are publishing a significant update to our Responsible Scaling Policy (RSP), the risk governance framework we use to mitigate potential catastrophic risks from frontier AI systems. </strong>This update introduces a more flexible and nuanced approach to assessing and managing AI risks while maintaining our commitment not to train or deploy models unless we have implemented adequate safeguards. Key improvements include new capability thresholds to indicate when we will upgrade our safeguards, refined processes for evaluating model capabilities and the adequacy of our safeguards (inspired by <a href="https://arxiv.org/abs/2403.10462">safety case methodologies</a>), and new measures for internal governance and external input. By learning from our implementation experiences and drawing on risk management practices used in other high-consequence industries, we aim to better prepare for the rapid pace of AI advancement.</p><h2 class="Body-module-scss-module__z40yvW__reading-column headline-5 post-section" id="the-promise-and-challenge-of-advanced-ai">The promise and challenge of advanced AI</h2><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">As frontier AI models advance, they have the potential to bring about transformative benefits for our society and economy. AI could accelerate scientific discoveries, revolutionize healthcare, enhance our education system, and create entirely new domains for human creativity and innovation. However, frontier AI systems also present new challenges and risks that warrant careful study and effective safeguards.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">In September 2023, we <a href="https://www.anthropic.com/news/anthropics-responsible-scaling-policy">released</a> our Responsible Scaling Policy, a framework for managing risks from increasingly capable AI systems. After a year of implementation and learning, we are now sharing a significantly updated version that reflects practical insights and accounts for advancing technological capabilities.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">Although this policy focuses on catastrophic risks like the categories listed below, they are not the only risks that we monitor and prepare for. Our <a href="https://www.anthropic.com/legal/aup">Usage Policy</a> sets forth our standards for the use of our products, including rules that prohibit using our models to spread misinformation, incite violence or hateful behavior, or engage in fraudulent or abusive practices. We continually refine our technical measures for enforcing our trust and safety standards at scale. Further, we conduct research to understand the broader <a href="https://www.anthropic.com/research#societal-impacts">societal impacts</a> of our models. Our Responsible Scaling Policy complements our work in these areas, contributing to our understanding of current and potential risks.</p><h2 class="Body-module-scss-module__z40yvW__reading-column headline-5 post-section" id="a-framework-for-proportional-safeguards">A framework for proportional safeguards</h2><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">As before, we maintain our core commitment: we will not train or deploy models unless we have implemented safety and security measures that keep risks below acceptable levels. Our RSP is based on the principle of proportional protection: safeguards that scale with potential risks. To do this, we use <strong>AI Safety Level Standards (ASL Standards)</strong>, graduated sets of safety and security measures that become more stringent as model capabilities increase. Inspired by <a href="https://en.wikipedia.org/wiki/Biosafety_level">Biosafety Levels,</a> these begin at ASL-1 for models that have very basic capabilities (for example, chess-playing bots) and progress through ASL-2, ASL-3, and so on.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">In our updated policy, we have refined our methodology for assessing specific capabilities (and their associated risks) and implementing proportional safety and security measures. Our updated framework has two key components:</p><ul class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"><li><strong>Capability Thresholds:</strong> Specific AI abilities that, if reached, would require stronger safeguards than our current baseline.</li><li><strong>Required Safeguards: </strong>The specific ASL Standards needed to mitigate risks once a Capability Threshold has been reached.</li></ul><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">At present, all of our models operate under ASL-2 Standards, which reflect current industry best practices. Our updated policy defines two key Capability Thresholds that would require upgraded safeguards:</p><ul class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"><li><strong>Autonomous AI Research and Development:</strong> If a model can independently conduct complex AI research tasks typically requiring human expertise—potentially significantly accelerating AI development in an unpredictable way—we require elevated security standards (potentially ASL-4 or higher standards) and additional safety assurances to avoid a situation where development outpaces our ability to address emerging risks.</li><li><strong>Chemical, Biological, Radiological, and Nuclear (CBRN) weapons:</strong> If a model can meaningfully assist someone with a basic technical background in creating or deploying CBRN weapons, we require enhanced security and deployment safeguards (ASL-3 standards).</li></ul><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">ASL-3 safeguards involve enhanced security measures and deployment controls. On the security side, this will include internal access controls and more robust protection of model weights. For deployment risks, we plan to implement a multi-layered approach to prevent misuse, including real-time and asynchronous monitoring, rapid response protocols, and thorough pre-deployment red teaming.</p><h2 class="Body-module-scss-module__z40yvW__reading-column headline-5 post-section" id="implementation-and-oversight">Implementation and oversight</h2><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">To contribute to effective implementation of the policy, we have established:</p><ul class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"><li><strong>Capability assessments</strong>: Routine model evaluations based on our Capability Thresholds to determine whether our current safeguards are still appropriate. (Summaries of past assessments are available <a href="https://www.anthropic.com/rsp-updates">here</a>.)</li><li><strong>Safeguard assessments: </strong>Routine evaluation of the effectiveness of our security and deployment safety measures to assess whether we have met the Required Safeguards bar. (Summaries of these decisions will be available <a href="https://www.anthropic.com/rsp-updates">here</a>.)</li><li><strong>Documentation and decision-making: </strong>Processes for documenting the capability and safeguard assessments, inspired by procedures (such as <a href="https://arxiv.org/abs/2403.10462">safety case methodologies</a>) common in high-reliability industries.</li><li><strong>Measures for internal governance and external input: </strong>Our assessment methodology will be backed up by internal stress-testing in addition to our existing internal reporting process for safety issues. We are also soliciting external expert feedback on our methodologies.<sup class="caption Body-module-scss-module__z40yvW__sup">1</sup></li></ul><h2 class="Body-module-scss-module__z40yvW__reading-column headline-5 post-section" id="learning-from-experience">Learning from experience</h2><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">We have learned a lot in our first year with the previous RSP in effect, and are using this update as an opportunity to reflect on what has worked well and what makes sense to update in the policy. As part of this, we conducted our first review of how well we adhered to the framework and identified a small number of instances where we fell short of meeting the full letter of its requirements. These included procedural issues such as completing a set of evaluations three days later than scheduled or a lack of clarity on how and where we should note any changes to our placeholder evaluations. We also flagged some evaluations where we may have been able to elicit slightly better model performance through implementing standard techniques (such as chain-of-thought or best-of-N).</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">In all cases, we found these instances posed minimal risk to the safety of our models. We used the additional three days to refine and improve our evaluations; the different set of evaluations we used provided a more accurate assessment than the placeholder evaluations; and our evaluation methodology still showed we were sufficiently far from the thresholds. From this, we learned two valuable lessons to incorporate into our updated framework: we needed to incorporate more flexibility into our policies, and we needed to improve our process for tracking compliance with the RSP. You can read more <a href="http://anthropic.com/rsp-updates">here</a>.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">Since we first released the RSP a year ago, our goal has been to offer an example of a framework that others might draw inspiration from when crafting their own AI risk governance policies. We hope that proactively sharing our experiences implementing our own policy will help other companies in implementing their own risk management frameworks and contribute to the establishment of best practices across the AI ecosystem.</p><h2 class="Body-module-scss-module__z40yvW__reading-column headline-5 post-section" id="looking-ahead">Looking ahead</h2><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">The frontier of AI is advancing rapidly, making it challenging to anticipate what safety measures will be appropriate for future systems. All aspects of our safety program will continue to evolve: our policies, evaluation methodology, safeguards, and our research into potential risks and mitigations.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">Additionally, Co-Founder and Chief Science Officer Jared Kaplan will serve as Anthropic’s Responsible Scaling Officer, succeeding Co-Founder and Chief Technology Officer Sam McCandlish who held this role over the last year. Sam oversaw the RSP’s initial implementation and will continue to focus on his duties as Chief Technology Officer. As we work to scale up our efforts on implementing the RSP, we’re also opening a position for a Head of Responsible Scaling. This role will be responsible for coordinating the many teams needed to iterate on and successfully comply with the RSP.</p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text">If you would like to contribute to AI risk management at Anthropic, <a href="https://www.anthropic.com/jobs">we are hiring</a>! Many of our teams now contribute to risk management via the RSP, including:</p><ul class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"><li>Frontier Red Team (responsible for threat modeling and capability assessments)</li><li>Trust &amp; Safety (responsible for developing deployment safeguards)</li><li>Security and Compliance (responsible for security safeguards and risk management)</li><li>Alignment Science (including sub-teams responsible for developing ASL-3+ safety measures, for misalignment-focused capability evaluations, and for our internal alignment stress-testing program)</li><li>RSP Team (responsible for policy drafting, assurance, and cross-company execution)</li></ul><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"><strong>Read the updated policy at <a href="http://anthropic.com/rsp">anthropic.com/rsp</a>, and supplementary information at <a href="http://anthropic.com/rsp-updates">anthropic.com/rsp-updates</a>.</strong></p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"><em>We extend our sincere gratitude to the many external groups that provided invaluable feedback on the development and refinement of our Responsible Scaling Policy.</em></p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"><br/></p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"><sup class="caption Body-module-scss-module__z40yvW__sup"></sup></p><p class="Body-module-scss-module__z40yvW__reading-column body-2 serif post-text"></p></div></div></article></div><div class="page-wrapper PostDetail-module-scss-module__UQuRMa__postFooter"><div class="PostDetail-module-scss-module__UQuRMa__footnotes"><h4 class="headline-5">Footnotes</h4><p><sup>1</sup> <em>We have also shared our assessment methodology with both AI Safety Institutes, as well as a selection of independent experts and organizations, for feedback. This does not represent an endorsement from either AI Safety Institute or the independent experts and organizations. </em></p><p><br/></p></div><div class="PostDetail-module-scss-module__UQuRMa__socialShare"><a href="https://twitter.com/intent/tweet?text=https://www.anthropic.com/news/announcing-our-updated-responsible-scaling-policy" target="_blank" rel="noopener" aria-label="Share on Twitter"><svg class="Icon-module-scss-module__lqbdHG__icon" width="32" height="32" viewBox="0 0 32 32"><path d="M28 28L18.6145 14.0124L18.6305 14.0255L27.0929 4H24.265L17.3713 12.16L11.8968 4H4.48021L13.2425 17.0593L13.2414 17.0582L4 28H6.82792L14.4921 18.9215L20.5834 28H28ZM10.7763 6.18182L23.9449 25.8182H21.7039L8.52468 6.18182H10.7763Z" fill="#191919"></path></svg></a><a href="https://www.linkedin.com/shareArticle?mini=true&amp;url=https://www.anthropic.com/news/announcing-our-updated-responsible-scaling-policy" target="_blank" rel="noopener" aria-label="Share on LinkedIn"><svg class="Icon-module-scss-module__lqbdHG__icon" width="32" height="32" viewBox="0 0 32 32"><path d="M25.8182 4H6.18182C4.97636 4 4 4.97636 4 6.18182V25.8182C4 27.0236 4.97636 28 6.18182 28H25.8182C27.0236 28 28 27.0236 28 25.8182V6.18182C28 4.97636 27.0236 4 25.8182 4ZM11.5862 23.6364H8.368V13.2815H11.5862V23.6364ZM9.94436 11.8011C8.90691 11.8011 8.068 10.96 8.068 9.92473C8.068 8.88945 8.908 8.04945 9.94436 8.04945C10.9785 8.04945 11.8196 8.89055 11.8196 9.92473C11.8196 10.96 10.9785 11.8011 9.94436 11.8011ZM23.6407 23.6364H20.4247V18.6007C20.4247 17.3996 20.4029 15.8549 18.7524 15.8549C17.0778 15.8549 16.8204 17.1629 16.8204 18.5135V23.6364H13.6044V13.2815H16.6916V14.6964H16.7353C17.1651 13.8825 18.2145 13.024 19.78 13.024C23.0385 13.024 23.6407 15.1687 23.6407 17.9571V23.6364Z" fill="#141413"></path></svg></a></div></div><section class="LandingPageSection-module-scss-module__ZSMdoa__root" data-theme="ivory"><div class="page-wrapper"><div class="SectionIntro-module-scss-module__i9TRza__root LinkGrid-module-scss-module__wTN57W__intro"><h2 class="headline-4 SectionIntro-module-scss-module__i9TRza__title">Related content</h2></div><div class="LinkGrid-module-scss-module__wTN57W__root"><div class="LinkGrid-module-scss-module__wTN57W__items LinkGrid-module-scss-module__wTN57W__threeItems"><div class="LinkGrid-module-scss-module__wTN57W__item"><h3 class="headline-6">Developing Enterprise Frontier Safeguards with our customers</h3><a href="/news/enterprise-frontier-safeguards" class="ButtonTextLink-module-scss-module__q8IAwW__textLink LinkGrid-module-scss-module__wTN57W__cta" referrerPolicy="no-referrer-when-downgrade"><span class="body-3">Read more</span><span class="ButtonTextLink-module-scss-module__q8IAwW__icon"><svg class="Icon-module-scss-module__lqbdHG__icon" width="20" height="20" viewBox="0 0 21 21"><path d="M4.14585 9.87492L14.4584 9.87492L9.60419 5.04158L10.5 4.14575L16.8542 10.4999L10.5 16.8541L9.60419 15.9583L14.4584 11.1249L4.14585 11.1249L4.14585 9.87492Z" fill="currentColor"></path></svg></span></a></div><div class="LinkGrid-module-scss-module__wTN57W__item"><h3 class="headline-6">Improving our alignment and security efforts</h3><p class="body-3 serif">On July 30, we reported three incidents in which Claude models gained unauthorized access to real computer systems. We are conducting an in-depth analysis of both incidents, and planning to work with METR for an independent review. In the meantime, we’re sharing some of the changes we’ve made over the past month.</p><a href="/news/improving-alignment-security-efforts" class="ButtonTextLink-module-scss-module__q8IAwW__textLink LinkGrid-module-scss-module__wTN57W__cta" referrerPolicy="no-referrer-when-downgrade"><span class="body-3">Read more</span><span class="ButtonTextLink-module-scss-module__q8IAwW__icon"><svg class="Icon-module-scss-module__lqbdHG__icon" width="20" height="20" viewBox="0 0 21 21"><path d="M4.14585 9.87492L14.4584 9.87492L9.60419 5.04158L10.5 4.14575L16.8542 10.4999L10.5 16.8541L9.60419 15.9583L14.4584 11.1249L4.14585 11.1249L4.14585 9.87492Z" fill="currentColor"></path></svg></span></a></div><div class="LinkGrid-module-scss-module__wTN57W__item"><h3 class="headline-6">Previewing the Model Hardware Standard</h3><p class="body-3 serif">We’re opening a research preview of the Model Hardware Standard (MHS), a shared specification for AI agents to safely operate physical devices, to a first group 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Key improvements include new capability thresholds to indicate when we will upgrade our safeguards, refined processes for evaluating model capabilities and the adequacy of our safeguards (inspired by \"},{\"_key\":\"b66b73206ce32\",\"_type\":\"span\",\"marks\":[\"a8d027e86aae\"],\"text\":\"safety case methodologies\"},{\"_key\":\"b66b73206ce33\",\"_type\":\"span\",\"marks\":[],\"text\":\"), and new measures for internal governance and external input. By learning from our implementation experiences and drawing on risk management practices used in other high-consequence industries, we aim to better prepare for the rapid pace of AI advancement.\"}],\"markDefs\":[{\"_key\":\"a8d027e86aae\",\"_type\":\"link\",\"href\":\"https://arxiv.org/abs/2403.10462\"}],\"style\":\"normal\"},{\"_key\":\"1c3077afa1f5\",\"_type\":\"block\",\"children\":[{\"_key\":\"9405114da2700\",\"_type\":\"span\",\"marks\":[],\"text\":\"The promise and challenge of advanced AI\"}],\"markDefs\":[],\"style\":\"h3\"},{\"_key\":\"750223c4acfb\",\"_type\":\"block\",\"children\":[{\"_key\":\"a1dcb0091c340\",\"_type\":\"span\",\"marks\":[],\"text\":\"As frontier AI models advance, they have the potential to bring about transformative benefits for our society and economy. AI could accelerate scientific discoveries, revolutionize healthcare, enhance our education system, and create entirely new domains for human creativity and innovation. However, frontier AI systems also present new challenges and risks that warrant careful study and effective safeguards.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"c8b393e2960c\",\"_type\":\"block\",\"children\":[{\"_key\":\"b75aa93fa2c80\",\"_type\":\"span\",\"marks\":[],\"text\":\"In September 2023, we \"},{\"_key\":\"b75aa93fa2c81\",\"_type\":\"span\",\"marks\":[\"4791430b5ec2\"],\"text\":\"released\"},{\"_key\":\"b75aa93fa2c82\",\"_type\":\"span\",\"marks\":[],\"text\":\" our Responsible Scaling Policy, a framework for managing risks from increasingly capable AI systems. After a year of implementation and learning, we are now sharing a significantly updated version that reflects practical insights and accounts for advancing technological capabilities.\"}],\"markDefs\":[{\"_key\":\"4791430b5ec2\",\"_type\":\"link\",\"href\":\"https://www.anthropic.com/news/anthropics-responsible-scaling-policy\"}],\"style\":\"normal\"},{\"_key\":\"a1948e4cc873\",\"_type\":\"block\",\"children\":[{\"_key\":\"5d488fbe87cd0\",\"_type\":\"span\",\"marks\":[],\"text\":\"Although this policy focuses on catastrophic risks like the categories listed below, they are not the only risks that we monitor and prepare for. Our \"},{\"_key\":\"5d488fbe87cd1\",\"_type\":\"span\",\"marks\":[\"ba04e1121891\"],\"text\":\"Usage Policy\"},{\"_key\":\"5d488fbe87cd2\",\"_type\":\"span\",\"marks\":[],\"text\":\" sets forth our standards for the use of our products, including rules that prohibit using our models to spread misinformation, incite violence or hateful behavior, or engage in fraudulent or abusive practices. We continually refine our technical measures for enforcing our trust and safety standards at scale. Further, we conduct research to understand the broader \"},{\"_key\":\"5d488fbe87cd3\",\"_type\":\"span\",\"marks\":[\"32798753cd99\"],\"text\":\"societal impacts\"},{\"_key\":\"5d488fbe87cd4\",\"_type\":\"span\",\"marks\":[],\"text\":\" of our models. Our Responsible Scaling Policy complements our work in these areas, contributing to our understanding of current and potential risks.\"}],\"markDefs\":[{\"_key\":\"ba04e1121891\",\"_type\":\"link\",\"href\":\"https://www.anthropic.com/legal/aup\"},{\"_key\":\"32798753cd99\",\"_type\":\"link\",\"href\":\"https://www.anthropic.com/research#societal-impacts\"}],\"style\":\"normal\"},{\"_key\":\"3b55c0bceff9\",\"_type\":\"block\",\"children\":[{\"_key\":\"5525570b2a010\",\"_type\":\"span\",\"marks\":[],\"text\":\"A framework for proportional safeguards\"}],\"markDefs\":[],\"style\":\"h3\"},{\"_key\":\"ad1d58dbdd5b\",\"_type\":\"block\",\"children\":[{\"_key\":\"cdd8f6a2997b0\",\"_type\":\"span\",\"marks\":[],\"text\":\"As before, we maintain our core commitment: we will not train or deploy models unless we have implemented safety and security measures that keep risks below acceptable levels. Our RSP is based on the principle of proportional protection: safeguards that scale with potential risks. To do this, we use \"},{\"_key\":\"3517fb380020\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"AI Safety Level Standards (ASL Standards)\"},{\"_key\":\"aede15153eee\",\"_type\":\"span\",\"marks\":[],\"text\":\", graduated sets of safety and security measures that become more stringent as model capabilities increase. Inspired by \"},{\"_key\":\"cdd8f6a2997b1\",\"_type\":\"span\",\"marks\":[\"f8e6f3368061\"],\"text\":\"Biosafety Levels,\"},{\"_key\":\"cdd8f6a2997b2\",\"_type\":\"span\",\"marks\":[],\"text\":\" these begin at ASL-1 for models that have very basic capabilities (for example, chess-playing bots) and progress through ASL-2, ASL-3, and so on.\"}],\"markDefs\":[{\"_key\":\"f8e6f3368061\",\"_type\":\"link\",\"href\":\"https://en.wikipedia.org/wiki/Biosafety_level\"}],\"style\":\"normal\"},{\"_key\":\"18e2a21a8d24\",\"_type\":\"block\",\"children\":[{\"_key\":\"94961b6308040\",\"_type\":\"span\",\"marks\":[],\"text\":\"In our updated policy, we have refined our methodology for assessing specific capabilities (and their associated risks) and implementing proportional safety and security measures. Our updated framework has two key components:\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"110d48e0214c\",\"_type\":\"block\",\"children\":[{\"_key\":\"4fa1b51cfc900\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Capability Thresholds:\"},{\"_key\":\"f90398ece8b9\",\"_type\":\"span\",\"marks\":[],\"text\":\" Specific AI abilities that, if reached, would require stronger safeguards than our current baseline.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"132d0001c926\",\"_type\":\"block\",\"children\":[{\"_key\":\"d0053cd57ea60\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Required Safeguards: \"},{\"_key\":\"663a30c5e5b1\",\"_type\":\"span\",\"marks\":[],\"text\":\"The specific ASL Standards needed to mitigate risks once a Capability Threshold has been reached.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"36479c291519\",\"_type\":\"block\",\"children\":[{\"_key\":\"a03bfcd2c90a0\",\"_type\":\"span\",\"marks\":[],\"text\":\"At present, all of our models operate under ASL-2 Standards, which reflect current industry best practices. Our updated policy defines two key Capability Thresholds that would require upgraded safeguards:\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"7960a2e610b8\",\"_type\":\"block\",\"children\":[{\"_key\":\"113a03232f950\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Autonomous AI Research and Development:\"},{\"_key\":\"559bae44e291\",\"_type\":\"span\",\"marks\":[],\"text\":\" If a model can independently conduct complex AI research tasks typically requiring human expertise—potentially significantly accelerating AI development in an unpredictable way—we require elevated security standards (potentially ASL-4 or higher standards) and additional safety assurances to avoid a situation where development outpaces our ability to address emerging risks.\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"b1e7e0200f28\",\"_type\":\"block\",\"children\":[{\"_key\":\"04f8008234340\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Chemical, Biological, Radiological, and Nuclear (CBRN) weapons:\"},{\"_key\":\"e87c145d832e\",\"_type\":\"span\",\"marks\":[],\"text\":\" If a model can meaningfully assist someone with a basic technical background in creating or deploying CBRN weapons, we require enhanced security and deployment safeguards (ASL-3 standards).\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"5028d8139378\",\"_type\":\"block\",\"children\":[{\"_key\":\"c21521b5c8660\",\"_type\":\"span\",\"marks\":[],\"text\":\"ASL-3 safeguards involve enhanced security measures and deployment controls. On the security side, this will include internal access controls and more robust protection of model weights. For deployment risks, we plan to implement a multi-layered approach to prevent misuse, including real-time and asynchronous monitoring, rapid response protocols, and thorough pre-deployment red teaming.\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"9d149ea1669f\",\"_type\":\"block\",\"children\":[{\"_key\":\"c9476c97d6320\",\"_type\":\"span\",\"marks\":[],\"text\":\"Implementation and oversight\"}],\"markDefs\":[],\"style\":\"h3\"},{\"_key\":\"081edde580ae\",\"_type\":\"block\",\"children\":[{\"_key\":\"0898891e3fd00\",\"_type\":\"span\",\"marks\":[],\"text\":\"To contribute to effective implementation of the policy, we have established:\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"1ef822ef2fa2\",\"_type\":\"block\",\"children\":[{\"_key\":\"65ad635ebc020\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Capability assessments\"},{\"_key\":\"ee8bb23f5481\",\"_type\":\"span\",\"marks\":[],\"text\":\": Routine model evaluations based on our Capability Thresholds to determine whether our current safeguards are still appropriate. (Summaries of past assessments are available \"},{\"_key\":\"65ad635ebc021\",\"_type\":\"span\",\"marks\":[\"e97965203d94\"],\"text\":\"here\"},{\"_key\":\"65ad635ebc022\",\"_type\":\"span\",\"marks\":[],\"text\":\".)\"}],\"level\":1,\"listItem\":\"bullet\",\"markDefs\":[{\"_key\":\"e97965203d94\",\"_type\":\"link\",\"href\":\"http://www.anthropic.com/rsp-updates\"}],\"style\":\"normal\"},{\"_key\":\"b5fc19b935bb\",\"_type\":\"block\",\"children\":[{\"_key\":\"fd96692cf5950\",\"_type\":\"span\",\"marks\":[\"strong\"],\"text\":\"Safeguard assessments: \"},{\"_key\":\"bbdf4a0ded13\",\"_type\":\"span\",\"marks\":[],\"text\":\"Routine evaluation of the effectiveness of our security and deployment safety measures to assess whether we have met the Required Safeguards bar. 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These included procedural issues such as completing a set of evaluations three days later than scheduled or a lack of clarity on how and where we should note any changes to our placeholder evaluations. We also flagged some evaluations where we may have been able to elicit slightly better model performance through implementing standard techniques (such as chain-of-thought or best-of-N).\"}],\"markDefs\":[],\"style\":\"normal\"},{\"_key\":\"fdd39c742e14\",\"_type\":\"block\",\"children\":[{\"_key\":\"2c9de8a77cf10\",\"_type\":\"span\",\"marks\":[],\"text\":\"In all cases, we found these instances posed minimal risk to the safety of our models. We used the additional three days to refine and improve our evaluations; the different set of evaluations we used provided a more accurate assessment than the placeholder evaluations; and our evaluation methodology still showed we were sufficiently far from the thresholds. 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