Right to Transparency
You have the right to know exactly how your data is being used and which AI models are being trained on your contributions.
The Transparency Problem
Most AI companies do not disclose the specific data sources used to train their models. When you use social media, write online, or create content, you often have no way of knowing if your contributions end up training AI systems.
What Transparency Means
Data Source Disclosure
AI companies should be required to disclose the categories of data used for training, including whether they scraped public websites, licensed data, or used user-generated content from specific platforms.
Individual Notification
Individuals should be notified when their specific content is used for AI training, with clear information about what data was used and for what purpose.
Data Provenance
AI outputs should include provenance information - citations back to the data sources that contributed to specific responses. This creates accountability and enables compensation.
Current Requirements
- EU AI Act: Requires disclosure of training data for high-risk AI systems
- GDPR: Mandates transparency about automated decision-making
- Colorado Algorithmic Accountability Law: Requires notice and explanation for high-risk AI
What We Advocate For
- Mandatory disclosure of AI training data sources
- Individual notification when personal data is used
- Cryptographic provenance tracking for AI outputs
- Regular audits of AI training practices