Too Much Order, Too Soon: The Case Against AI Term Sheets
Washington may be closing in on an AI “term sheet.” The industry, meanwhile, is already writing its own rules.
Recent commentary suggests U.S. artificial intelligence (AI) policy may be coalescing around a federal framework. A widely discussed Tech Policy Press piece argues that a short “term sheet” emerging from negotiations between the White House and industry could reshape American AI policy. An Axios report, meanwhile, highlights how Anthropic imposed constraints on its latest model before release. Taken together, these developments point to two distinct—and too often conflated—mechanisms of governance: political coordination and market discipline. Washington policy debates fixate on the former. The latter already shapes behavior across the industry.
That distinction matters. A political “term sheet” can influence expectations, shape investment decisions, spur compliance planning, and create focal points for firms trying to anticipate the regulatory landscape. It can affect how boards, general counsel, venture investors, enterprise customers, and journalists define “responsible AI.” In that limited sense, the strongest version of the term-sheet argument holds: nonbinding political coordination can produce real economic effects before Congress enacts a statute or an agency promulgates a rule.
But that concession does not answer the harder question—whether those effects are beneficial. The issue is not whether a term sheet shapes expectations. It is how it shapes them, and whether it improves or distorts the market process through which information about AI safety, reliability, and value emerges. Skepticism is warranted. In a fast-moving industry defined by dispersed knowledge, entrepreneurial experimentation, and radical uncertainty, a politically generated focal point can do more than reduce uncertainty at the margin. It can create the wrong kind of certainty—and in the AI context, that may prove worse than having less of it.