Podcast: The science of polarization

Artificial intelligence (AI) promises a future once confined to science fiction: personalized medicine accounting for your specific condition, accelerated scientific discovery addressing the most difficult challenges, and reimagined public education designed around AI tutors suited to each student's learning style. We see glimpses of this potential on a daily basis. Yet, as AI capabilities surge forward at exponential speed, the laws and regulations meant to guide them remain anchored in the twentieth century (if not the nineteenth or eighteenth!). This isn't just inefficient; it's dangerously reckless.

For too long, our approach to governing new technologies, including AI, has been one of cautious incrementalism—trying to fit revolutionary tools into outdated frameworks. We debate how century-old privacy torts apply to vast AI training datasets, how liability rules designed for factory machines might cover autonomous systems, or how copyright law conceived for human authors handles AI-generated creations. We tinker around the edges, applying digital patches to analog laws.