Effective policy requires a distinction between safety engineering and social regulation. While theoretical debates about superintelligence grab headlines, they often function as distractions from the messy, measurable problems happening today. To prevent these existential fears from stalling progress, regulators should anchor their frameworks in existing legal categories.
For example, algorithmic bias should be handled through updated anti-discrimination laws rather than new, abstract AI treaties. If a credit-scoring tool unfairly rejects minority applicants, that is a civil rights violation that we already know how to prosecute. Similarly, economic displacement needs a direct response through labor laws and updated social safety nets, not speculative discussions about sentient machines.
Policymakers can maintain this focus by implementing tiered regulation. High-stakes applications—like medical diagnostics or judicial sentencing—demand strict oversight and mandatory audits immediately. By building these specific rules now, we create a foundation of accountability. We shouldn't wait for a
