Summary:
- The article outlines five pragmatic approaches to AI regulation, emphasizing the need for transparency, accountability, and human-in-the-loop systems.
- It advocates for a balanced framework that encourages innovation while addressing the risks associated with data privacy, algorithmic bias, and security in AI deployment.