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articles/ai-foundry/model-inference/overview.md

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Microsoft helps guard against abuse and unintended harm by taking the following actions:
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- Incorporating Microsoft's [principles for responsible AI use](https://www.microsoft.com/ai/responsible-ai)
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- Adopting a [code of conduct](/legal/cognitive-services/openai/code-of-conduct?context=/azure/ai-services/openai/context/context) for use of the service
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- Adopting a [code of conduct](legal/ai-code-of-conduct?context=/azure/ai-services/openai/context/context) for use of the service
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- Building [content filters](/azure/ai-services/content-safety/overview) to support customers
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- Providing responsible AI [information and guidance](/legal/cognitive-services/openai/transparency-note?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext&tabs=image) that customers should consider when using Azure OpenAI.
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articles/ai-services/agents/overview.md

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## Responsible AI
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At Microsoft, we're committed to the advancement of AI driven by principles that put people first. Generative models such as the ones available in Azure OpenAI have significant potential benefits, but without careful design and thoughtful mitigations, such models have the potential to generate incorrect or even harmful content. Microsoft has made significant investments to help guard against abuse and unintended harm, which includes incorporating Microsoft’s <a href="https://www.microsoft.com/ai/responsible-ai?activetab=pivot1:primaryr6" target="_blank">principles for responsible AI use</a>, adopting a [Code of Conduct](https://aka.ms/AI-CoC) for use of the service, building [content filters](/azure/ai-services/content-safety/overview) to support customers, and providing responsible AI [information and guidance](/legal/cognitive-services/openai/transparency-note?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext&tabs=image) that customers should consider when using Azure AI Agent Service.
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At Microsoft, we're committed to the advancement of AI driven by principles that put people first. Generative models such as the ones available in Azure OpenAI have significant potential benefits, but without careful design and thoughtful mitigations, such models have the potential to generate incorrect or even harmful content. Microsoft has made significant investments to help guard against abuse and unintended harm, which includes incorporating Microsoft’s <a href="https://www.microsoft.com/ai/responsible-ai?activetab=pivot1:primaryr6" target="_blank">principles for responsible AI use</a>, adopting a [Code of Conduct](/legal/ai-code-of-conduct?context=/azure/ai-services/agents/context/context) for use of the service, building [content filters](/azure/ai-services/content-safety/overview) to support customers, and providing responsible AI [information and guidance](/legal/cognitive-services/openai/transparency-note?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext&tabs=image) that customers should consider when using Azure AI Agent Service.
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## Get started with Azure AI Agent Service
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articles/ai-services/computer-vision/concept-liveness-abuse-monitoring.md

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# Abuse monitoring in Face liveness detection
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Azure AI Face liveness detection lets you detect and mitigate instances of recurring content and/or behaviors that indicate a violation of the [Code of Conduct](https://aka.ms/AI-CoC) or other applicable product terms. This guide shows you how to work with these features to ensure your application is compliant with Azure policy.
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Azure AI Face liveness detection lets you detect and mitigate instances of recurring content and/or behaviors that indicate a violation of the [Code of Conduct](/legal/ai-code-of-conduct?context=/azure/ai-services/computer-vision/context/context) or other applicable product terms. This guide shows you how to work with these features to ensure your application is compliant with Azure policy.
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Details on how data is handled can be found on the [Data, Privacy, and Security](/legal/cognitive-services/face/data-privacy-security?context=/azure/ai-services/computer-vision/context/context) page.
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articles/ai-services/computer-vision/toc.yml

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- name: Best practices for enrolling users
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href: enrollment-overview.md
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- name: Code of conduct
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href: https://aka.ms/AI-CoC
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href: /legal/ai-code-of-conduct?context=/azure/ai-services/computer-vision/context/context
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- name: Data privacy and security
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href: /legal/cognitive-services/face/data-privacy-security?context=/azure/ai-services/computer-vision/context/context
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- name: Limited Access features

articles/ai-services/openai/concepts/abuse-monitoring.md

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There are several components to abuse monitoring:
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- **Content Classification**: Classifier models detect harmful text and/or images in user prompts (inputs) and completions (outputs). The system looks for categories of harms as defined in the [Content Requirements](https://aka.ms/AI-CoC), and assigns severity levels as described in more detail on the [Content Filtering](/azure/ai-services/openai/concepts/content-filter) page. The content classification signals contribute to pattern detection as described below.
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- **Content Classification**: Classifier models detect harmful text and/or images in user prompts (inputs) and completions (outputs). The system looks for categories of harms as defined in the [Content Requirements](/legal/ai-code-of-conduct?context=/azure/ai-services/openai/context/context), and assigns severity levels as described in more detail on the [Content Filtering](/azure/ai-services/openai/concepts/content-filter) page. The content classification signals contribute to pattern detection as described below.
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- **Abuse Pattern Capture**: Azure OpenAI Service’s abuse monitoring system looks at customer usage patterns and employs algorithms and heuristics to detect and score indicators of potential abuse. Detected patterns consider, for example, the frequency and severity at which harmful content is detected (as indicated in content classifier signals) in a customer’s prompts and completions, as well as the intentionality of the behavior. The trends and urgency of the detected pattern will also affect scoring of potential abuse severity.
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For example, a higher volume of harmful content classified as higher severity, or recurring conduct indicating intentionality (such as recurring jailbreak attempts) are both more likely to receive a high score indicating potential abuse.
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- **Review and Decision**: Prompts and completions that are flagged through content classification and/or identified as part of a potentially abusive pattern of use are subjected to another review process to help confirm the system’s analysis and inform actioning decisions for abuse monitoring. Such review is conducted through two methods: automated review and human review.

articles/ai-services/openai/includes/content-filter-configurability.md

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Content filtering configurations are created within a Resource in Azure AI Foundry portal, and can be associated with Deployments. [Learn more about configurability here](../how-to/content-filters.md).
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Customers are responsible for ensuring that applications integrating Azure OpenAI comply with the [Code of Conduct](https://aka.ms/AI-CoC).
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Customers are responsible for ensuring that applications integrating Azure OpenAI comply with the [Code of Conduct](/legal/ai-code-of-conduct?context=/azure/ai-services/openai/context/context).

articles/ai-services/openai/index.yml

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- text: Limited access
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- text: Code of conduct
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url: https://aka.ms/AI-CoC
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url: /legal/ai-code-of-conduct?context=/azure/ai-services/openai/context/context
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- text: Data, privacy, and security
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url: /legal/cognitive-services/openai/data-privacy?context=/azure/ai-services/openai/context/context
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- text: Customer Copyright Commitment

articles/ai-services/openai/overview.md

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## Responsible AI
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At Microsoft, we're committed to the advancement of AI driven by principles that put people first. Generative models such as the ones available in Azure OpenAI have significant potential benefits, but without careful design and thoughtful mitigations, such models have the potential to generate incorrect or even harmful content. Microsoft has made significant investments to help guard against abuse and unintended harm, which includes incorporating Microsoft’s <a href="https://www.microsoft.com/ai/responsible-ai?activetab=pivot1:primaryr6" target="_blank">principles for responsible AI use</a>, adopting a [Code of Conduct](https://aka.ms/AI-CoC) for use of the service, building [content filters](/azure/ai-services/content-safety/overview) to support customers, and providing responsible AI [information and guidance](/legal/cognitive-services/openai/transparency-note?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext&tabs=image) that customers should consider when using Azure OpenAI.
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At Microsoft, we're committed to the advancement of AI driven by principles that put people first. Generative models such as the ones available in Azure OpenAI have significant potential benefits, but without careful design and thoughtful mitigations, such models have the potential to generate incorrect or even harmful content. Microsoft has made significant investments to help guard against abuse and unintended harm, which includes incorporating Microsoft’s <a href="https://www.microsoft.com/ai/responsible-ai?activetab=pivot1:primaryr6" target="_blank">principles for responsible AI use</a>, adopting a [Code of Conduct](/legal/ai-code-of-conduct?context=/azure/ai-services/openai/context/context) for use of the service, building [content filters](/azure/ai-services/content-safety/overview) to support customers, and providing responsible AI [information and guidance](/legal/cognitive-services/openai/transparency-note?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext&tabs=image) that customers should consider when using Azure OpenAI.
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## Get started with Azure OpenAI Service
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articles/ai-services/openai/toc.yml

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- name: Code of conduct
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href: https://aka.ms/AI-CoC
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href: /legal/ai-code-of-conduct?context=/azure/ai-services/openai/context/context
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- name: Data, privacy, and security
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href: /legal/cognitive-services/openai/data-privacy?context=/azure/ai-services/openai/context/context
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articles/ai-services/speech-service/toc.yml

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- name: Code of conduct
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href: /legal/ai-code-of-conduct?context=/azure/ai-services/speech-service/context/context
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- name: Limited access
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- name: Disclosure for voice and avatar talent

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