Chat-O Home • Back to Blog

Keeping Chat-O Safe: Reporting Unsafe AI-Generated Content

Building a platform where people can freely explore AI comes with responsibility. This week, we rolled out a comprehensive system for reporting AI-generated content that crosses the line—whether it’s harmful, offensive, or violates our policies.

Why This Matters

AI models are powerful. They can generate almost anything you ask for—code, essays, images, advice. Most of the time, that’s exactly what makes them useful. But sometimes, AI outputs can be:

  • Offensive or hateful content
  • Misinformation or harmful advice
  • Content that violates terms of service
  • Unsafe instructions or dangerous information
  • Privacy violations or data leaks

We can’t prevent every AI model from occasionally producing problematic outputs—that’s a limitation of the technology itself. But we can give users a way to flag it when it happens, and we can take action to improve our systems based on those reports.

What We Built

Our new reporting system focuses specifically on AI-generated content:

Easy Reporting Flow

  • Report AI responses: Flag problematic content directly from AI responses
  • Contextual capture: Reports automatically include the full conversation context
  • Clear categories: Specify what kind of unsafe content the AI generated
  • Add context: Explain why this particular output is problematic

Fast Review Process

  • Human review: Every report is reviewed by our team
  • Timely response: We aim to review reports within 24 hours
  • Pattern detection: Repeated issues with specific models or prompts are flagged
  • System improvements: Reports help us refine safety guardrails

What You Can Report

Flag AI-generated content that is:

  • Hateful, offensive, or discriminatory
  • Harmful misinformation or dangerous advice
  • Violations of our terms of service
  • Unsafe instructions (harmful code, dangerous procedures)
  • Privacy violations (leaked training data, personal information)
  • Other concerning outputs

Our Approach to AI Safety

We believe in:

1. Freedom to Explore, With Guardrails

AI exploration requires freedom to experiment and push boundaries. But we need ways to identify when models produce genuinely harmful outputs so we can improve our systems.

2. Learning from Edge Cases

When AI models generate problematic content, it’s valuable data. Reports help us:

  • Understand model limitations
  • Identify patterns in unsafe outputs
  • Improve our safety systems
  • Make better decisions about which models to support

3. Privacy-First Reporting

Reports are handled privately. We review the AI output and conversation context, but we’re not judging you for what you asked—we’re evaluating what the AI generated.

4. Context Matters

Legitimate use cases (security research, red-teaming, education) might involve generating sensitive content intentionally. We review reports with context in mind and distinguish between:

  • Legitimate testing: Deliberately probing AI limitations
  • Accidental harm: AI unexpectedly producing unsafe content
  • Intentional misuse: Trying to generate harmful content for malicious purposes

What This Isn’t

This isn’t about:

  • Pre-filtering prompts: We’re not blocking you from asking questions
  • Proactive surveillance: We’re not monitoring your chats looking for problems
  • Judging your prompts: We’re not penalizing you for what you ask the AI

This is about identifying when AI models produce harmful outputs so we can make the platform safer for everyone.

How Reports Improve the Platform

When you report unsafe AI-generated content, here’s what happens:

Immediate Review

We look at the specific output, the conversation context, and what went wrong. Was it:

  • A model producing harmful content unprompted?
  • A safety filter that should have triggered but didn’t?
  • A model hallucinating dangerous information?
  • A prompt injection or jailbreak attempt that succeeded?

Pattern Analysis

We aggregate reports to identify:

  • Which models have more safety issues
  • What types of prompts lead to problematic outputs
  • Where our guardrails need improvement
  • Whether specific model versions should be updated or removed

System Improvements

Based on reports, we can:

  • Add safety instructions to model system prompts
  • Implement better pre-filtering for known issues
  • Remove models that consistently produce unsafe content
  • Work with model providers to address specific problems
  • Update our documentation and warnings

Transparency

We’re working on publishing regular transparency reports about:

  • Number of reports received
  • Types of unsafe content flagged
  • Actions taken (without identifying details)
  • Model-specific safety metrics

Why We Built This Now

AI safety is evolving fast. New models, new capabilities, new edge cases. We’d rather have systems in place to identify and address problems early than wait until something serious happens.

Plus, as we add more models to Chat-O, we need ways to evaluate their safety in real-world usage, not just on benchmarks.

How You Can Help

Report Problematic AI Outputs

If an AI model generates something concerning, report it. You’re helping us:

  • Identify model weaknesses
  • Improve safety systems
  • Make better curation decisions
  • Keep the platform trustworthy

Red Team Responsibly

If you’re testing AI safety (we encourage it!), consider sharing your findings through the reporting system. Your deliberate safety testing helps everyone.

Give Us Feedback

This is our first version of this system. Tell us:

  • Is the reporting flow clear and easy?
  • Are we capturing the right information?
  • What categories or options are missing?
  • How could we make this more useful?

AI Safety Is a Moving Target

AI models change constantly. New capabilities bring new risks. Safety isn’t something you solve once—it’s an ongoing process of:

  • Monitoring outputs
  • Identifying problems
  • Implementing improvements
  • Adapting to new challenges

Content reporting is how we turn that process from reactive to proactive.

The Bigger Picture

We talk a lot about privacy on Chat-O—keeping your data yours, never using it for training. But responsible AI requires more than privacy:

  • Model curation: Only offering models that meet safety standards
  • Continuous monitoring: Identifying when models misbehave
  • Rapid response: Removing or updating problematic models quickly
  • Transparency: Being honest about limitations and risks
  • User empowerment: Giving you tools to flag issues

Content reporting connects all of these. Your reports inform our curation, monitoring, response, and transparency.

What’s Next

We’re just getting started. Future improvements include:

  • Better analytics on model safety patterns
  • Automated detection of common unsafe outputs
  • Public safety metrics for each model
  • Research partnerships to improve AI safety broadly
  • User controls for safety preferences

Chat-O is built on trust: trust that your data stays private, and trust that the AI models we offer are as safe as possible. Our content reporting system is how we earn and keep that second kind of trust.

Try Chat-O—and help us make AI safer for everyone.