Risk-adjusted regulatory approach for AI algorithms

Categorizing AI algorithms into low, medium, and high-risk categories is crucial for effective regulation. By prioritizing oversight on high-risk algorithms that have the potential to harm users, such as in employment where discriminatory applications can occur, regulatory bodies can focus resources on impactful areas while not burdening small operators. Aligning with the European Union's risk-adjusted approach, where regulations target algorithms affecting a million or more users, the U.S. can bridge the gap in regulatory frameworks. This approach ensures that regulatory efforts are targeted towards algorithms with real risk implications for a significant number of users, fostering a balance between innovation and user protection. The emphasis on real high-impact scenarios in various sectors like education, employment, healthcare, and criminal justice further underscores the necessity of addressing areas of genuine concern for societal well-being.