An interview with Sriram Krishnan, who says “there will not be an FDA for AI” under Trump, blames the AI backlash on the industry's “doomer” messaging, and more
Sriram Krishnan tells the FT the president is against a centralised regulator as AI backlash grows
Context & Ripple Effects
Krishnan’s position extends a White House AI agenda already framed around opposing “woke” AI and competing with China. It also echoes an earlier Trump-era hands-off approach to AI regulation, while related coverage had anticipated that existing safety institutions could be dismantled or reshaped.
The comments arrive as prominent industry figures acknowledge more resistance to AI adoption and argue that catastrophic-risk messaging is losing public support. That makes the regulatory stance inseparable from a broader fight over how AI’s risks and benefits are presented.
First-order effects
- A centralised, FDA-style US AI regulator is not part of the administration’s stated approach, reducing the prospect of a single pre-deployment approval gate for AI developers.
- The White House is publicly shifting responsibility for the AI backlash toward industry messaging, putting AI companies under pressure to make a more practical case for deployment rather than foregrounding existential-risk narratives.
Second-order effects
- AI developers and their customers may face a more fragmented policy environment: absent a central regulator, sector-specific rules and institutional reshaping become more consequential than a unified federal safety regime.
- Companies competing for policy influence have an incentive to align AI deployment with the administration’s competitiveness agenda, while critics of rapid adoption may focus more heavily on concrete labor and public-service effects.
Third-order effects
- If this posture persists, US AI governance could develop around executive policy, sector-by-sector oversight, and geopolitical competition rather than a dedicated national safety regulator.
- The larger fault line will be whether public acceptance can be maintained through demonstrated economic and operational benefits as AI also shifts income from labor toward capital; the related coverage suggests that distributional effects may become harder to separate from safety debates.
The trend: US AI policy is increasingly being contested as a choice between centralized safety governance and a pro-deployment, competitiveness-led model that seeks to counter public backlash through economic utility.