Regulating today's AI harms builds the machinery for tomorrow's risks

From the conversation

How do you connect this data regulation to maybe the long term future of building safe transformative AI. Perfect. So you start by saying some AI systems could be risky, right? That is already a controversial plan because most of software, at least since the 90s is not regulated, right? Most of software, the potential harms that come from general software are not considered the purview of government, maybe there are some lawsuits on the margin but largely you buy a software for Microsoft or from Google and if things go badly for you, then things go badly for you. You shouldn't have bought it in the first place. It's a responsibility of the user. We want to get to the point where there's an agreement that when software or AI systems become sufficiently advanced, the hubs are big enough that governments should stop caring about it and privacy is a way to do it, today. Bias is a way to do it, today. And then you start carving out certain domains where AI could be harmful where governments could pay attention and then you ask, "Okay, so how should governments pay attention?" And so you build a machinery, that machinery could look like mandatory audits. It could look like standards and best practices.…