Imagine it is 2028. A start-up in St. Louis trains an AI model that can spot pancreatic cancer six months earlier than the best radiologists, buying patients precious time that medicine has never been able to give them. But the model never leaves the lab. Why? Because a well-intentioned, technology-neutral state statute drafted in 2025 forces every “automated decision system” to undergo a one-size-fits-all bias audit, to be repeated annually, and to be performed only by outside experts who—three years in—still do not exist in sufficient numbers. While regulators scramble, the company’s venture funding dries up, the founders decamp to Singapore, and thousands of Americans are deprived of an innovation that would have saved their lives.

That grim vignette is fictional—so far. But it is the predictable destination of the seven “deadly sins” that already haunt our AI policy debates. Reactive politicians are at risk of passing laws that fly in the face of what qualifies as good policy for emerging technologies.