Merge pull request #368 from PatrickFarley/consaf-updates

add tony's draft

Author: denrea

articles/ai-services/content-safety/how-to/improve-performance.md

@@ -0,0 +1,86 @@
+---
+title: "Mitigate false results in Azure AI Content Safety"
+titleSuffix: Azure AI services
+description: Learn techniques to improve the performance of Azure AI Content Safety models by handling false positives and false negatives.
+#services: cognitive-services
+author: PatrickFarley
+manager: nitinme
+ms.service: azure-ai-content-safety
+ms.topic: how-to
+ms.date: 09/18/2024
+ms.author: pafarley
+#customer intent: As a user, I want to improve the performance of Azure AI Content Safety so that I can ensure accurate content moderation.
+---
+
+# Mitigate false results in Azure AI Content Safety
+
+This guide provides a step-by-step process for handling false positives and false negatives from Azure AI Content Safety models. 
+
+False positives are when the system incorrectly flags non-harmful content as harmful; false negatives are when harmful content is not flagged as harmful. Address these instances to ensure the integrity and reliability of your content moderation process, including responsible generative AI deployment.
+
+## Prerequisites
+
+* An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services/)
+* Once you have your Azure subscription, <a href="https://aka.ms/acs-create"  title="Create a Content Safety resource"  target="_blank">create a Content Safety resource </a> in the Azure portal to get your key and endpoint. Enter a unique name for your resource, select your subscription, and select a resource group, supported region (see [Region availability](/azure/ai-services/content-safety/overview#region-availability)), and supported pricing tier. Then select **Create**.
+
+## Review and verification
+
+Conduct an initial assessment to confirm that the flagged content is really a false positive or false negative. This can involve: 
+- Checking the context of the flagged content.  
+- Comparing the flagged content against the content safety risk categories and severity definitions:
+    - If you're using content safety in Azure OpenAI, see the [Azure OpenAI content filtering doc](/azure/ai-services/openai/concepts/content-filter).
+    - If you're using the Azure AI Content Safety standalone API, see the [Harm categories doc](/azure/ai-services/content-safety/concepts/harm-categories?tabs=warning) or the [Prompt Shields doc](/azure/ai-services/content-safety/concepts/jailbreak-detection), depending on which API you're using.
+
+## Customize your severity settings
+
+If your assessment confirms that you found a false positive or false negative, you can try customizing your severity settings to mitigate the issue. The settings depend on which platform you're using.
+
+#### [Content Safety standalone API](#tab/standalone-api)
+
+If you're using the Azure AI Content Safety standalone API directly, try experimenting by setting the severity threshold at different levels for [harm categories](/azure/ai-services/content-safety/concepts/harm-categories?tabs=definitions) based on API output. Alternatively, if you prefer the no-code approach, you can try out those settings in [Content Safety Studio](https://contentsafety.cognitive.azure.com/) or Azure AI Studio’s [Content Safety page](https://ai.azure.com/explore/contentsafety). Instructions can be found [here](/azure/ai-studio/quickstarts/content-safety?tabs=moderate-text-content). 
+
+In addition to adjusting the severity levels for false negatives, you can also use blocklists. More information on using blocklists for text moderation can be found in [Use blocklists for text moderation](/azure/ai-services/content-safety/how-to/use-blocklist?tabs=windows%2Crest).
+
+
+#### [Azure OpenAI](#tab/azure-openai-studio)
+
+Read the [Configurability](/en-us/azure/ai-services/openai/concepts/content-filter?tabs=warning%2Cuser-prompt%2Cpython-new#configurability-preview) documentation, as some content filtering configurations may require approval through the process mentioned there.
+
+Follow the steps in the documentation to update configurations to handle false positives or negatives: [How to use content filters (preview) with Azure OpenAI Service](/azure/ai-services/openai/how-to/content-filters). 
+
+In addition to adjusting the severity levels for false negatives, you can also use blocklists. Detailed instruction can be found in [How to use blocklists with Azure OpenAI Service](/azure/ai-services/openai/how-to/use-blocklists).
+
+#### [Azure AI Studio](#tab/azure-ai-studio)
+
+Read the [Configurability](/azure/ai-studio/concepts/content-filtering#configurability-preview) documentation, as some content filtering configurations may require approval through the process mentioned there.
+
+Follow the steps in the documentation to update configurations to handle false positives or negatives: [Azure AI Studio content filtering](/azure/ai-studio/concepts/content-filtering#create-a-content-filter).
+
+In addition to adjusting the severity levels for false negatives, you can also use blocklists. Detailed instruction can be found in [Azure AI Studio content filtering](/azure/ai-studio/concepts/content-filtering#use-a-blocklist-as-a-filter).
+
+---
+
+## Create a custom category based on your own RAI policy
+
+Sometimes you might need to create a custom category to ensure the filtering aligns with your specific Responsible AI policy, as prebuilt categories or content filtering may not be enough. 
+
+Refer to the [Custom categories documentation](/azure/ai-services/content-safety/concepts/custom-categories) to build your own categories with the Azure AI Content Safety API.
+
+## Document issues and send feedback to Azure
+
+If, after you’ve tried all the steps mentioned above, Azure AI Content Safety still can't resolve the false positives or negatives, there is likely a policy definition or model issue that needs further attention.
+
+Document the details of the false positives and/or false negatives by providing the following information to the [Content safety support team](mailto:[email protected]):
+- Description of the flagged content.
+- Context in which the content was posted. 
+- Reason given by Azure AI Content Safety for the flagging (if positive).
+- Explanation of why the content is a false positive or negative.
+- Any adjustments already attempted by adjusting severity settings or using custom categories. 
+- Screenshots or logs of the flagged content and system responses.
+
+This documentation helps in escalating the issue to the appropriate teams for resolution.
+
+## Related content
+
+- [Azure AI Content Safety overview](/azure/ai-services/content-safety/overview)
+- [Harm categories](/azure/ai-services/content-safety/concepts/harm-categories?tabs=warning)

articles/ai-services/content-safety/toc.yml

@@ -63,6 +63,8 @@ items:
     href: how-to/custom-categories-rapid.md
   - name: Use a blocklist
     href: how-to/use-blocklist.md
+  - name: Mitigate false results
+    href: how-to/improve-performance.md
   - name: Encryption of data at rest
     href: how-to/encrypt-data-at-rest.md
   - name: Migrate from public preview to GA