States like California are becoming the real engines of AI governance as federal regulation stalls.
Publicly built and publicly accountable AI models are emerging as a credible alternative to corporate AI.
AI is already embedded in governance worldwide, reshaping courts, campaigning, and citizen participation.
AI’s influence looks less like a distant threat and more like an infrastructure problem already shaping the way power flows, which is why Nathan Sanders and Bruce Schneier push past the fixation on deepfakes to show how governance itself is being rewritten in real time. Their argument sharpens when Bruce notes that “the way it makes mistakes with overconfidence are deliberate design decisions,” a reminder that private incentives are coding public consequences. The emergence of public, open models like Switzerland’s suggests a path where AI development mirrors democratic values instead of corporate priorities. State-level action, especially in places like California, shows that regulation doesn’t have to wait for federal willpower that isn’t coming. And as campaigns, courts, and citizen engagement absorb AI more deeply, the stakes shift from predicting the future to deciding who gets to control it.
Tune in for a conversation that maps the terrain of AI power before the next wave hits.
What DOGE Gets Wrong about Tech and Government
Members of the DOGE network rarely offer thoughtful accounts that depart from the Musk narrative (government is broken, full of talentless hacks, DOGE is fixing things). So I was interested to see a DOGEr express genuine circumspection. This came from Sahil Lavingia, a startup founder, who was
