\n \n However, ensuring a high-quality user experience goes beyond simple guardrails like this. You want your application\u2019s responses to be not only accurate, but also embody your brand\u2019s values and prevent harmful or inappropriate output. With AI capabilities expanding so rapidly, it can be challenging just to keep track of the challenges around ensuring high-quality responses, let alone the steps required to protect against bad output (triggered either by malicious usage or inadvertently).\n<\/p>\n \n Microsoft has a portal that covers various aspects of Responsibe AI<\/a>, including the A-Z of responsible AI<\/a> which acts like a glossary of terms like Jailbreak, Impact assessment, and Red-teaming that will help inform your understanding of these concepts. Microsoft Learn also has an overview of what is Responsible AI<\/a> that introduces issues like reliability, safety, inclusiveness, privacy, and security; things you should consider in your implementation of AI features and how to address them. \n<\/p>\n \n These things can be addressed in different layers of your application architecture:\n<\/p>\n \n Many of these concerns are new and specific to AI implementations and will need new solutions that keep up with the changing landscape of AI capabilities and heightened user expectations.\n<\/p>\n \n \n The new Azure Content Safety<\/a> service can be a part of your AI toolkit to ensure your users have high-quality interactions with your app. It is a content moderation platform that can detect offensive or inappropriate content in user interactions, and provide your app with a content risk assessment based on different types of problem (eg. violence, hate, sexual, and self-harm) and severity. This high level of granularity provides your app with the tools to block interactions, trigger moderation, add warnings, or otherwise handle each safety incident appropriately to provide the best experience for your users.\n<\/p>\n \n Azure Content Safety is multi-lingual aware and multi-model \u2013 it works on both text and image inputs \u2013 and can form an important part of your AI safety system.\n<\/p>\n \n The service includes the interactive Content Safety Studio<\/a> and dashboard as well as the API<\/a> that you\u2019ll incorporate into your app architecture.\n<\/p>\n \n \n Refer to the announcement blog post<\/a> and documentation<\/a> for more information, including quickstarts and code samples in C#, Python, Java, and JavaScript.\n<\/p>\n \n We\u2019d love your feedback on this post, including any tips or tricks you\u2019ve learned from playing around with ChatGPT prompts.\n<\/p>\n \n If you have any thoughts or questions, use the feedback forum<\/a> or message us on Twitter @surfaceduodev<\/a>.\n<\/p>\n![\"Model](\"https:\/\/devblogs.microsoft.com\/surface-duo\/wp-content\/uploads\/sites\/53\/2023\/10\/model-refuses-to-write-a-poem.png\")
What is Responsible AI?<\/h2>\n
\n
![\"Announcing](\"https:\/\/devblogs.microsoft.com\/surface-duo\/wp-content\/uploads\/sites\/53\/2023\/10\/thumbnail-image-1-of-blog-post-titled.png\")
Azure Content Safety<\/h2>\n
![\"Content](\"https:\/\/devblogs.microsoft.com\/surface-duo\/wp-content\/uploads\/sites\/53\/2023\/10\/a-screenshot-of-a-computer-description-automatica-2.png\")
Feedback and resources<\/h2>\n