This text explores the challenges and concerns surrounding data participation in the age of AI. It discusses the issues of consent and control over personal data, highlighting cases where users have faced backlash against forced data-sharing agreements. The text emphasizes the need for context and understanding in the use of data, and the importance of considering the rights and preferences of data creators and users. It questions the compatibility of copyright laws with AI data usage and suggests policy changes to address these issues. The conclusion calls for a focus on building online platforms and AI models that prioritize human terms and values.
Signal | Change | 10y horizon | Driving force |
---|---|---|---|
Backlash against vendors forcing data access | Less extractive data acquisition | Increased user control over data access | User frustration and demand for privacy |
Fierce user backlash against data-sharing | Increased awareness of data rights | Strengthened data protection regulations | User demand for privacy and autonomy |
Frustration over exercising right to opt out | Improved opt-out mechanisms | Better enforcement of data protection | User demand for privacy and control |
Incompatibility of case law with AI data grab | Shift in legal framework for AI data | Revised copyright laws | Need for alignment of laws and norms |
Uncertainty in translating AI anxiety into laws | Improved articulation of AI concerns | Clearer expression of AI anxieties | Need for effective legal mechanisms |
Questions about copyright status and control | Greater clarity in copyright laws | Enhanced legal protection for creators | Need for updated copyright laws |
Desire for transparency and non-commercial use | Preference signals for data sharing | Improved communication of data consent | User preference and consent |
Lack of mechanisms for contextual data use | Framework for data use contexts | Clear guidelines for data use in AI | Balance between data use and rights |
Mandatory data collection for AI training | Need for consent-driven training | Consent-based AI data training | User desire for control over data |
Lack of control over AI systems | Empowered control over AI systems | Increased user control over AI | User demand for control and autonomy |
Difficulty in disengaging from AI companies | Improved opt-out mechanisms | Enhanced user control over data usage | User desire for control and privacy |
Dark patterns to thwart data opt-outs | Transparent and effective opt-outs | Improved user control over data opt-outs | User demand for privacy and control |