What should you implement to prevent hateful responses from being returned by a generative AI solution?

Question

Options

• Aprompt engineering
• Babuse monitoring
• Ccontent filtering
• Dfine-tuning

• A
  6% (1)
• C
  89% (16)
• D
  6% (1)

Explanation

Azure OpenAI Service includes a content filtering system that works alongside core models, including DALL-E image generation models. This system works by running both the prompt and completion through an ensemble of classification models designed to detect and prevent the output of harmful content. The content filtering system detects and takes action on specific categories of potentially harmful content in both input prompts and output completions. Variations in API configurations and application design might affect completions and thus filtering behavior. The text content filtering models for the hate, sexual, violence, and self-harm categories have been specifically trained and tested on the following languages: English, German, Japanese, Spanish, French, Italian, Portuguese, and Chinese. However, the service can work in many other languages, but the quality might vary. In all cases, you should do your own testing to ensure that it works for your application. In addition to the content filtering system, Azure OpenAI Service performs monitoring to detect content and/or behaviors that suggest use of the service in a manner that might violate applicable https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/content-filter

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