OpenAI argues that denying teens AI access until adulthood would leave them unprepared—just like withholding internet access from previous generations. They detail practical safeguards: age-appropriate defaults, learning-focused tools like Study Mode, parental controls, and partnerships with organizations such as the Family Online Safety Institute to ensure responsible, safe access.

The core tension this article exposes is the gap between a patchwork of state-level AI safety laws and the need for a coherent federal framework that can also scale internationally. Without a unified national standard, frontier AI risks being governed by inconsistent state regulations that confuse consumers, strain regulator resources, and divert developer attention, especially at startups.

This paper shows that not all data points need expensive unlearning—by using influence functions to identify low-impact points, you can cut computational costs by up to 50% while maintaining privacy guarantees. A practical insight for anyone building privacy-preserving AI systems.