The introduction explains that AI providers sometimes reduce model quality
Web-based reporting platform built with standard web technologies (likely HTML, CSS, JavaScript, backend database for user reports).
2025-08-27
- website
Highlight 1
Provides a simple and clear mechanism for users to report issues with AI model performance.
Highlight 2
Encourages community engagement by creating a centralized space for user feedback.
Highlight 3
Raises accountability for AI providers by signaling quality degradation trends.
Improvement 1
Lack of structured reporting categories (e.g., response accuracy, coherence, hallucination) may limit the usefulness of collected data.
Improvement 2
The platform could benefit from analytics or dashboards to visualize trends over time.
Improvement 3
Limited discoverability—needs stronger awareness campaigns or SEO improvements to attract a wider audience.
Product Functionality
Introduce structured reporting options, analytics dashboards, and trend insights for both users and researchers.
UI & UX
Improve navigation and add clear calls-to-action for submitting reports and viewing data insights.
SEO or Marketing
Optimize the site for search engines with clear meta descriptions, keywords, and blog posts about AI model quality issues. Leverage social media to drive community engagement.
MultiLanguage Support
Offer multi-language support (e.g., Spanish, Chinese, French) to enable global participation and broaden reporting coverage.
- 1
What is DumbDetector.ai?
It is a platform where users can report when AI models start producing lower-quality or nonsensical responses, helping track and highlight performance issues.
- 2
How does the platform work?
Users submit reports of poor AI responses, which are collected and shared to build awareness of when models degrade in quality.
- 3
Why should I use DumbDetector.ai?
By reporting your experiences, you contribute to a community-driven effort to hold AI providers accountable and improve the quality of AI services.