SuperCitizen

AI regulation in the U.S. has been mostly through executive orders, voluntary commitments, and existing sectoral rules (FDA for medical AI, EEOC for hiring AI, NHTSA for autonomous vehicles). Major developments:

EO 14110 (2023): Required reporting on frontier-model training, safety testing, and Department of Commerce involvement; partially rescinded in 2025.
AI Safety Institute at NIST.
State laws: California's SB 1047 (vetoed), Colorado AI Act, NYC algorithmic-hiring law.
Sectoral rules: FDA AI/ML guidance, ECPA for biometrics.

Debates span: pre-deployment testing for frontier models, AI liability, copyright and training-data, government use, election AI (deepfakes), and AI talent / chip export rules.

Spectrum of framings

How adherents on each side of the conventional left / center / right spectrum frame this issue — written so each camp would recognize the framing as charitable.

left

Progressive views vary: AI-safety advocates favor strong frontier regulation; civil-liberties advocates focus on bias, surveillance, and worker impact.

center

Most centrists favor a federal framework with risk-tiered oversight and sectoral rules.

right

Conservative views split: some favor light-touch innovation-friendly rules; others worry about national-security and content concerns.

Perspectives

Each perspective is presented in terms its advocates would recognize, with the concerns they treat as paramount. None is endorsed.

Strong-regulation advocates
Frontier AI models pose catastrophic and systemic risks. Mandatory pre-deployment testing, capability evaluations, transparency requirements, and liability for foreseeable harms are needed.
- Frontier-model safety testing
- Catastrophic risk
- Algorithmic harm and bias
Innovation-friendly framework
AI is the next general-purpose technology. Heavy-handed regulation cedes leadership to China and entrenches large incumbents. Light-touch federal framework with sectoral application is the right balance.
- U.S. AI leadership
- Avoiding incumbent entrenchment
- Innovation pace
Sectoral / harm-specific advocates
AI is a tool with sector-specific risks. Apply existing rules — FDA, EEOC, NHTSA — and create new ones where gaps exist (election deepfakes, child safety) without imposing horizontal AI law.
- Sector-specific application
- Targeting specific harms
- Avoiding horizontal AI mandates

Voices on this issue13

Commonly-cited public figures who have taken a position on this issue. Grouped by their conventional left/center/right lean. Tap a voice to see their full position record.

left3

center4

right6

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