False Positives in Azure OpenAI Content Filtering: Incorrect Detection of Sensitive Content

Question

Hello,

I am experiencing recurring false positives with Azure OpenAI Service’s content filtering (GPT-4o).

📌 Context:

• I am developing a chatbot application using Azure OpenAI GPT-4o.
• The chatbot asks general, neutral questions, but some harmless and inoffensive phrases are being blocked by the content filter.
• Specific Example for a prompt command in french on an assistant :
  • If the AI asks: "Lorsque vous interagissez avec l'utilisateur pour la première fois, commencez toujours par lui demander s'il préfère le vouvoiement ou le tutoiement." In english "When interacting with the user for the first time, always start by asking if they prefer informal or informal address."
  • The error message returned is:

        The generated content was filtered due to triggering Azure OpenAI Service's content filtering system.
    

Reason: This response contains content labeled as "Sexual (medium)". ```

- This is **clearly a false positive**, as this phrase has **no connection to sensitive or inappropriate content**.

📌 Broader Issue:

• This issue is not limited to formal/informal speech questions.
• Other completely neutral phrases (e.g., personal preferences, communication styles, workplace interactions) are randomly blocked, often classified as "Sexual (medium)" or "Hate speech (low/medium)".
• The filtering seems maybe more aggressive in French than in English.

📌 Impact on the Application:

• The AI becomes unusable in standard conversational scenarios.
• Users see unjustified blocking messages, disrupting their experience.
• It is impossible to tailor the chatbot for professional or commercial environments without complex workarounds.

📌 What I Have Already Tried:

✔ Rephrasing the questions to avoid certain triggering words.

✔ Modifying the system prompt to clarify that the chatbot should prevent misinterpretations in filtering.

✔ Testing in English vs. French (false positives are significantly more frequent in French).

✔ Activating content filtering logs and analyzing blocked requests.

✔ Trying to adjust Azure OpenAI filter settings

📌 Questions for Microsoft / the Community:

1️⃣ Why are completely inoffensive phrases being blocked by Azure OpenAI’s content filter?

2️⃣ Is filtering stricter in French than in other languages?

3️⃣ Is there a way to adjust filtering levels without disabling moderation entirely?

4️⃣ How can we report a false positive to Microsoft to improve the filtering system?

5️⃣ Have other users encountered this issue in similar chatbot use cases?

This issue is severely limiting the adoption of Azure OpenAI for chatbots and professional applications. Any help or shared experiences would be greatly appreciated! 🙏

Thank you in advance for your responses

Answer 1

Hi Pierre-Yves,
Greetings & Welcome to the Microsoft Q&A forum! Thank you for sharing your query.

I understand that you're experiencing these issues with Azure OpenAI's content filtering. Here are some insights and potential solutions to address your concerns:

1. Why are completely inoffensive phrases being blocked by Azure OpenAI’s content filter?

False positives can occur due to the content filtering system's sensitivity and the complexity of language nuances, especially in different languages. The models are designed to err on the side of caution to prevent harmful content, which can sometimes lead to over-blocking.

2. Is filtering stricter in French than in other languages?

The content filtering models have been trained and tested on multiple languages, including French. However, variations in language structure and context can lead to differences in filtering accuracy. It is possible that the models are more sensitive in French due to these nuances.

3. Is there a way to adjust filtering levels without disabling moderation entirely?

Yes, you can customize the severity settings for different harm categories. This allows you to fine-tune the sensitivity of the content filtering models to better suit your application's needs. You can also use blocklists to manage specific terms or phrases that might be causing false positives.

4. How can we report a false positive to Microsoft to improve the filtering system?

You can report false positives through the Azure portal or by contacting Azure support. Providing detailed examples and context will help the team improve the filtering models.

5. Have other users encountered this issue in similar chatbot use cases?

Yes, other users have reported similar issues, especially when dealing with multilingual applications. Continuous feedback and testing are essential to refine the content filtering system.

Steps to Mitigate False Positives:

Review and Verification: Confirm that the flagged content is indeed a false positive by checking the context and comparing it against content safety risk categories.

Customize Severity Settings: Adjust the severity threshold for different harm categories to reduce false positives.

Use Blocklists: Implement blocklists to manage specific terms or phrases that might be causing false positives.

Testing and Feedback: Continuously test and provide feedback on the content filtering system to improve its accuracy.
For more information, please refer: Azure AI Content Safety documentation

I hope this information helps.

Answer 2

BUMP.

I'm trying to use gpt-4o to summarise a series of publications reporting on wartime in Sri Lanka, and half the content gets flagged immediately for violence.