Policy development for AI presents unique challenges because the technology evolves faster than regulatory frameworks can adapt. The tension between enabling innovation and managing risk requires policy approaches that are both flexible and robust. Healthcare AI policy specifically highlights this - we need safeguards for patient safety while avoiding regulatory paralysis that prevents beneficial applications. The key policy question isn't whether to regulate AI, but how to design governance structures that can evolve alongside the technology while maintaining public trust and protecting fundamental values.
Reading some of the case studies cited in the survey, it's a pity all those insights can't somehow feed back into more recurring, systematic 'real-world evals' of the systems' usefulness + risks. So much nuances and little benefits/risks that probably get overlooked in evals that are 1-2 steps removed from real-world use.
Policy development for AI presents unique challenges because the technology evolves faster than regulatory frameworks can adapt. The tension between enabling innovation and managing risk requires policy approaches that are both flexible and robust. Healthcare AI policy specifically highlights this - we need safeguards for patient safety while avoiding regulatory paralysis that prevents beneficial applications. The key policy question isn't whether to regulate AI, but how to design governance structures that can evolve alongside the technology while maintaining public trust and protecting fundamental values.
Reading some of the case studies cited in the survey, it's a pity all those insights can't somehow feed back into more recurring, systematic 'real-world evals' of the systems' usefulness + risks. So much nuances and little benefits/risks that probably get overlooked in evals that are 1-2 steps removed from real-world use.