How to enhance user control and privacy protections in AI
Published: 16/10/2026
| OECD
The Organisation for Economic Co-operation and Development (OECD) has published a policy brief concerning how to enhance user control and privacy protections in AI.
The OECD notes that while building AI systems requires large volumes of data that often include personal information, maintaining data protection compliance improves data quality by strengthening user trust. The analysis focuses on two key data-gathering practices: conversational inputs from generative AI interactions, such as chatbots; and large-scale web scraping of public platforms.
The OECD assesses emerging regulatory guidance and industry practices, focusing on transparency and opt-out mechanisms, multi-stage data filtering, and privacy-enhancing technologies (PETs). In addition, the brief evaluates technical complexities around model weights data memorisation, the potential for machine unlearning, and privacy challenges posed by autonomous agentic AI systems.
In its conclusions for policymakers, the OECD recommends cultivating pragmatic collaboration between industry and regulators to uphold individual privacy rights without impeding technological development.
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