New ITI Guide Examines AI’s Application to Privacy Policy
WASHINGTON – As lawmakers worldwide continue to develop policies focused on AI, global tech trade association ITI released Privacy & Generative AI (opens in a new tab) — a new guide that focuses on the need for a clear and consistent application of global personal data and privacy rules to Generative AI models and systems.
ITI’s policy guide emphasizes that privacy approaches need to be risk-based and proportionate. This means tailoring privacy considerations to different stages within an AI value chain, and having a clear understanding of the types of data being processed and the corresponding privacy risks.
Above all, the development, deployment, and use of Generative AI systems requires a balanced, forward-looking assessment of longstanding privacy norms and principles.
“The AI models and systems that power the globe and help billions of consumers daily can’t operate without high quality, relevant data—making privacy policy a focal point of international technology discussions,” said ITI Senior Director of Policy, Trust, Data and Technology Rob McGruer. “A more coherent global approach is needed to move beyond the increasing patchwork of privacy laws emerging around the world. ITI’s Privacy & Generative AI policy guide aims to assist regulators in narrowing down the priority areas where data privacy and AI overlap, and offer sound, industry-backed guidance for clearer, harmonized privacy standards that protect consumers while allowing AI to thrive.”
ITI recommends global policymakers focus on:
- Ensuring clear and consistent AI guidance among global privacy regulators to streamline existing privacy rules across different jurisdictions in practice;
- Promoting regulatory sandboxes to advance flexible approaches;
- Defining clear global guidance that promotes the real-world application of Privacy Enhancing Technologies;
- Prioritizing trusted cross-border data flows;
- Leveraging AI to improve privacy standards; and
- Supporting greater transparency and accountability through the development of clear, industry-led data governance and provenance standards.
Read the full document here (opens in a new tab).