The integration of AI in business raises several risks, particularly in areas like algorithmic pricing where AI can lead to price collusion without clear accountability. Current legal frameworks struggle to address who is responsible when AI systems coordinate to inflate prices. Additionally, AI's persuasive capabilities can be exploited to target vulnerable populations, transforming traditional scams into highly personalized schemes.

Regulation of AI in mental health should focus on reducing harm and promoting access to evidence-based resources. This includes establishing standardized benchmarks for AI responses to sensitive prompts, enhancing crisis routing to provide timely support, enforcing privacy protections, and ensuring that AI systems marketed for mental health meet a duty-of-care standard through rigorous evaluation and monitoring.

The U.S. approach to AI regulation has shifted towards industrial acceleration, emphasizing private-sector leadership and innovation. However, this strategy raises concerns about the lack of safeguards and accountability. Critical questions remain about fairness in algorithmic decision-making and the protection of workers displaced by automation. Balancing innovation with responsible oversight is essential to build trust in American-made AI technologies.