A political map of US AI policy

In February I mapped global AI governance: institutions, summits, the EU AI Act, industry self-regulation, and the 600:1 safety-to-capability spending gap. That map was about what exists on paper.

This one is about US domestic politics — who is fighting over AI, with what tools, at what level of government, and with how much money. The headline from February still holds: the United States has no comprehensive federal AI safety law, and the executive branch has been working to prevent state laws from filling the gap. But the four months since have been among the most consequential in American AI politics: policy is being written anyway, just not in Congress. California and New York passed the first state laws requiring frontier labs to publish safety frameworks, report critical incidents, and protect whistleblowers. Industry spent millions trying to kill them. When that failed at the state level, a super PAC spent $7 million trying to keep one of the bills’ authors out of Congress.

If you only read one thing before engaging with US AI policy — as a researcher, advocate, or voter — understand that the fight is not Democrats vs. Republicans. It is at least seven factions, often aligned on specific votes and opposed on others, fighting over three different regulatory templates at three levels of government. The question for 2026 is not “will the US regulate AI?” It is who gets to regulate it, at what level, and with what penalties.

The one-page mental map

                    PUBLIC (70–86% want regulation; AI not yet top-5 election issue)
                                        │
        ┌───────────────────────────────┼───────────────────────────────┐
        │                               │                               │
   STATE LAWS                    FEDERAL FIGHT                   2026 RACES
   (where policy is              (who overrides whom)            (where money is)
    actually passing)
        │                               │                               │
   ┌────┴────┐                    ┌─────┴─────┐                   ┌─────┴─────┐
   │Frontier │                    │ Trump EO  │                   │ Wiener    │
   │transparency│                 │ voluntary │                   │ CA-11     │
   │SB 53    │                    │ 30-day    │                   │ Bores ✗   │
   │RAISE    │                    │ review    │                   │ NY-12     │
   ├─────────┤                    ├───────────┤                   │ Rutinel   │
   │Consumer │                    │ GAAIA     │                   │ CO-8      │
   │/ labor  │                    │ mandatory │                   └───────────┘
   │CO SB205 │                    │ audits +  │
   │NY A768  │                    │ 3yr       │
   ├─────────┤                    │ preemption│
   │Infra    │                    └───────────┘
   │DC pause │
   │Sanders  │
   │S.4214   │
   └─────────┘
        │
   SEVEN FACTIONS (not two parties):
   1 Frontier transparency (Wiener, Bores, Encode, Anthropic on SB 53)
   2 Omnibus Dem accountability (Lasher, Jeffries, Warren — civil rights + labor + kids)
   3 Near-term consumer AI (Rutinel, Colorado algorithmic discrimination)
   4 Progressive infrastructure pause (Sanders, AOC, env/labor coalitions)
   5 Populist right anti-oligarch (Bannon, parts of MAGA)
   6 Accelerationist / industry (Sacks, Leading the Future, parts of GOP leadership)
   7 Bipartisan federal framework (Obernolte-Trahan GAAIA — transparency + preempt states)

The central tension: States are writing laws. Industry wants one weak federal standard to replace them. Progressives want a federal pause on infrastructure. Populists on left and right distrust Big Tech oligarchs but disagree on solutions. And 2026 congressional primaries are where these abstractions turn into seven-figure ad buys.

What Americans actually think

Before the factions: the electorate. 70–86% of Americans support AI regulation in general (KPMG global, Eurobarometer, US anti-AI populism polling). Specific policies poll even higher and bipartisan:

Policy	Support	Source
Ban deepfakes in political ads	84% (R 83%, D 86%)	PPC/UMD 2024
Government testing before AI deployment	81% (R 76%, D 88%)	PPC/UMD 2024
Mandatory deepfake labeling	83–91%	PPC/UMD, Carnegie
Six-month pause on large-scale AI development	69%	YouGov 2023

Democrats are somewhat more pro-regulation on testing and oversight. Republicans match or exceed Democrats on deepfake bans and child safety. This is not a culture-war issue in polling — it is a high-consensus, low-salience issue. AI rarely ranks in voters’ top five priorities; healthcare, the economy, and immigration consistently dominate.

The pattern that matters politically: people express concern in surveys but keep using AI daily (the “say vs. do” gap). That makes it hard to build a mass movement against AI itself — but easy to build coalitions around specific harms: deepfakes, chatbots harming kids, algorithmic discrimination, data center electricity bills.

Sanders’s data center moratorium went from “fringe” (December 2025) to 100+ local moratoria and 12 state proposals (March 2026, per his office) — not because voters ranked “AI” as issue #1, but because electricity prices and local land use are tangible.

Implication: Politicians will frame AI through jobs, kids, bills, and oligarchs — not through alignment theory or P(doom). The safety research community’s concepts (catastrophic risk, deceptive alignment, RSI) enter politics only when translated into those frames.

Layer 1: State legislatures — the laboratory

After California’s SB 1047 was vetoed by Newsom in September 2024, the state-level strategy shifted: transparency and accountability first, not training bans or compute caps. Get labs to document what they’re doing before asking legislatures to halt capability development.

Three templates emerged.

Template A: Frontier transparency (California + New York)

Two sister laws emerged.

California SB 53 (Transparency in Frontier AI Act) — authored by State Senator Scott Wiener, signed September 2025, in force January 2026. Anthropic publicly supported it.

It applies to large frontier developers — roughly, entities training models above 10²⁶ FLOPs with over $500 million in annual revenue. They must:

Publish a Frontier AI framework on their website: how they assess catastrophic risks, secure unreleased weights, use third-party evaluators, and update annually
Issue transparency reports before deploying new or substantially modified frontier models
Report critical safety incidents to California’s Office of Emergency Services (15 days standard, 24 hours for emergencies)
Maintain whistleblower protections and anonymous internal reporting channels

Penalties: up to ~$1 million per violation, enforced by the state Attorney General. It does not require pausing training, government pre-approval of releases, or compute caps.

New York RAISE Act (Responsible AI Safety and Education Act) — co-authored by Assemblymember Alex Bores and Senator Andrew Gounardes, passed the legislature June 2025 with bipartisan support (~84% NY voter support cited by sponsors), signed by Governor Kathy Hochul December 19, 2025 — but significantly weakened before signing. Effective January 1, 2027 after chapter amendments.

RAISE covers similar ground: large frontier developers ($100M+ training compute threshold) must write and publish safety and security protocols, conduct third-party risk assessments, protect model weights, report critical safety incidents within 72 hours, and maintain whistleblower protections. An Office of Responsible AI Safety and Education within NY’s Department of Financial Services gets oversight authority. AG civil penalties — originally up to $30 million, cut by Hochul toward California scale ($1 million).

	CA SB 53	NY RAISE
Author	Sen. Scott Wiener	Asm. Alex Bores + Sen. Andrew Gounardes
Signed	Sept 2025	Dec 2025 (weakened)
Effective	Jan 2026	Jan 2027
Incident reporting	15 days / 24h emergency	72 hours
Penalties	~$1M/violation	~$1M/violation (after Hochul cuts)
Industry stance	Anthropic endorsed	Industry fought; Trump EO targeted

Politico called RAISE “widely regarded as the furthest-reaching in the country.” Industry fought both bills. Encode (Sneha Revanur’s organization) helped pass both. These laws do not pause training or require government pre-approval. They make voluntary safety practices mandatory law — the same package the AI safety research community has advocated for years, now encoded in the two states where most frontier labs operate.

Template B: Consumer / algorithmic discrimination (Colorado + spreading)

Colorado SB 24-205 (2024) — first comprehensive state AI consumer protection law, requiring developers and deployers of “high-risk” AI systems to use reasonable care against algorithmic discrimination. Effective February 2026. Lead sponsor in the 2025 session expansion: Rep. Manny Rutinel.

This is the near-term, optimistic-general quadrant: AI affecting hiring, credit, housing, healthcare decisions today, not catastrophic risk tomorrow. Industry often prefers fighting this to fighting frontier transparency — but consumer groups and civil rights organizations prioritize it.

Illinois, NYC (Local Law 144 on hiring algorithm audits), and New York’s pending A768 (Bores) extend this lane.

Template C: Infrastructure pause (Sanders + states + local)

Separate from frontier model law: data center moratoria. Sanders’s S.4214 (March 2025, with AOC) would pause new/upgraded AI data centers federally until comprehensive AI legislation passes covering safety, worker protection, and community/environmental standards. New York’s A11560 (passed legislature June 2026, awaiting Hochul) imposes a one-year state moratorium on large data center permits with prevailing wage and ratepayer protection requirements.

This regulates the physical substrate of capability — compute, power, water — not model weights directly.

State preemption skirmishes

Governors matter. Newsom vetoed SB 1047 but signed SB 53. Hochul signed RAISE but weakened it and endorsed Bores’s primary opponent. Both signal: transparency yes, hard pause no, and we pick which Democrats get credit.

Layer 2: Federal politics — three competing visions

The vacuum (still)

Biden’s EO 14110 (October 2023) required safety reporting for large models and pushed NIST to develop standards. Trump revoked it on January 20, 2025, replacing it with an order focused on “removing barriers to American leadership.” NIST’s AI Safety Institute was renamed the Center for AI Standards and Innovation (CAISI), its budget stayed around $10 million, and its mandate narrowed.

Congress has introduced dozens of AI bills. None have passed as comprehensive federal law. The Cruz attempt to attach a 10-year moratorium on state AI enforcement to the 2025 budget bill was stripped 99–1 in July 2025 — a rare bipartisan rejection of broad preemption. But that doesn’t mean preemption is dead. It means the fight moved to narrower, more sophisticated drafts.

Vision 1: Voluntary federal review (Trump EO, June 2, 2026)

Frontier developers may choose up to 30 days pre-release government review. CISA/NSA/Treasury define covered models within 60 days. Cannot be used for mandatory licensing. NSA leads benchmark definition; CAISI advisory only. No mandatory incident reporting. No penalties for non-participation. Hands-off.

Vision 2: Mandatory federal framework + state preemption (GAAIA, June 4, 2026)

Reps. Jay Obernolte (R-CA) and Lori Trahan (D-MA) released the Great American Artificial Intelligence Act discussion draft — 269 pages, the most substantive bipartisan federal frontier proposal to date.

For large frontier developers: public safety frameworks, semi-annual third-party audits (CAISI-certified IVOs), mandatory critical incident reporting, penalties up to $100M/day, CAISI codified (~$100M/year FY27–29).

Plus: 3-year preemption — states cannot enact new laws “specifically regulating the development” of AI models. General laws (civil rights, labor, privacy) and post-deployment rules preserved. California training-data transparency (AB 2013) would be preempted. Frontier laws in CA, NY, IL “federalized” — replaced by the federal standard, not duplicated.

Encode, Wiener, and Public Knowledge oppose preemption. Industry often wants federal rules — if they override state laws already fought.

The fight is not “regulate vs. don’t.” It is:

Who sets benchmarks — public thresholds (GAAIA/SB 53) vs. classified NSA standards (Trump EO)
Mandatory vs. voluntary — incident reporting and audits required, or optional 30-day review
Whether states keep authority — or get frozen for three years while Congress negotiates

If GAAIA passes with preemption intact, SB 53’s development-stage obligations could be superseded. That is the scenario safety advocates are organizing against.

Vision 3: Infrastructure moratorium + comprehensive legislation (Sanders S.4214)

Federal pause on AI data center construction until Congress passes laws ensuring: (A) AI product safety before release, (B) wealth sharing / anti-displacement, (C) community/environmental standards. Export ban on AI compute infrastructure to countries without equivalent safeguards.

Almost certainly will not pass the 119th Congress. Value is agenda-setting and linking to 100+ local moratoria.

The preemption wars — and strange bedfellows

Critical distinction: two different “moratoriums” get conflated in media:

Term	Who pushes it	What it pauses
State-law preemption moratorium	Cruz / Trump / Sacks	States cannot enforce AI laws for ~10 years
Data center moratorium	Sanders / AOC	New data centers until federal comprehensive AI law

Sanders wants to slow infrastructure; he opposed Cruz’s state preemption (aligned with Bannon and Blackburn on that single vote). The Senate killed Cruz’s broad preemption 99–1 in July 2025 — one of the few issues where progressive state-law advocates, Republican governors (DeSantis: “denying the people the ability to channel these technologies via self-government”), and MAGA populists (Bannon) overlapped.

GAAIA’s narrower 3-year preemption is harder to kill because it comes wrapped in mandatory audits and bipartisan sponsors.

GOP is not monolithic

GOP faction	AI stance	Example
Accelerationist / tech-right	De-regulate, win China, federal preemption	Sacks, parts of Trump WH
Federalist / culture-war	Block broad preemption; keep state child safety, deepfake, musician protection	Blackburn (killed Cruz; pushes TRUMP AMERICA AI Act with KOSA/NO FAKES carve-outs), DeSantis
National-security hawk	Export controls, visibility into RSI/internal models, CAISI in testing	Banks (AI OVERWATCH Act, June 2026 letter on recursive self-improvement)
Bipartisan framework	One national standard	Obernolte GAAIA

Sen. Jim Banks (R-IN) is not a pause advocate — but his June 2026 letter to the Trump cabinet urged treating recursive self-improvement and unreleased internal models as national security issues, and pushed CAISI into testing (weakening NSA-only control). Same week, Anthropic published on collective slowdown; OpenAI released an RSI policy paper. The fight is over who sets standards and who sees models, not regulation vs. no regulation.

Layer 3: Democrats — three lanes, not one party

It is tempting to say Democrats are “more pro-AI regulation.” Elites in the party are more likely to sponsor AI bills. But Democrats are fighting each other over which template wins.

Lane 1: Frontier transparency

Wiener (SB 53), Bores (RAISE), Encode, Anthropic (endorsed SB 53). Frame: catastrophic risk, mandatory safety plans, incident reporting, whistleblowers. Federal goal: nationalize SB 53/RAISE.

Lane 2: Omnibus accountability

Lasher (won NY-12 primary over Bores), Jeffries (House Dem AI Commission), Warren, AG Tish James. Frame: AI civil rights, hiring/lending bias (A3779, A773), kids (SAFE for Kids, chatbot bill A10379), data centers, deepfakes — frontier safety as one piece, not the whole brand.

Lasher co-sponsored RAISE and attacked Bores for voting no on employment/lending bills. Hochul signed weakened RAISE and endorsed Lasher — establishment signal: regulate AI, but not only through the frontier-only CS-legislator lane.

Lane 3: Near-term consumer protection

Rutinel (Colorado SB 24-205 lead, running for CO-8). Frame: algorithmic discrimination, reasonable floor for businesses, protect workers and consumers now. Not x-risk primary.

Lane 4 (overlapping): Progressive pause

Sanders, AOC. Frame: oligarchs, jobs, electricity bills, democracy catching up. Cites Hinton and FLI pause letter but master frame is economic justice, not EA alignment. Leadership (Jeffries) sympathetic but does not co-sponsor moratorium.

Net: No unified “Democratic AI policy.” NY-12 was Lasher’s omnibus lane beating Bores’s frontier lane. CA-11 is Wiener’s frontier lane winning. CO-8 (primary June 30) is Rutinel’s consumer lane vs. Shannon Bird’s innovation-friendly moderation.

Layer 4: Populism — left, right, and misaligned alliances

Populist left (Sanders / AOC / env-labor)

Anti-oligarch master frame: “a handful of billionaire Big Tech oligarchs” deciding humanity’s future without democratic debate
Data center moratorium, wealth sharing, pre-release product review
200+ organizations (Food & Water Watch, nurses unions, etc.) backed federal moratorium letter

Populist right (Bannon / parts of MAGA)

Names Altman, Musk, Amodei, Hassabis, Sacks as not acting in US interests
Demands pre-deployment vetting; fears employment and deepfake/truth crises
Helped kill Cruz preemption 99–1 — not aligned with Sanders on infrastructure pause

	Shared	Not shared
Left + right populists	Distrust Big Tech; want vetting; anti-oligarch rhetoric; killed broad preemption	Sanders wants wealth redistribution; Bannon doesn’t. Sanders pauses data centers; Bannon doesn’t necessarily.
Populists + frontier transparency advocates	Want oversight before harm	Populists frame jobs/democracy; frontier advocates frame catastrophic risk and evals
Populists + industry	Nothing	Everything

Foreign Affairs, DNYUZ, and Tech Policy Press documented anti-AI populist backlash building across both parties in early 2026. It is real but fragmented — not yet a coherent third force, more a set of overlapping grievances industry lobbyists exploit when convenient.

Layer 5: Money — where AI politics becomes expensive

2026 is the first cycle where AI regulation is a seven-figure primary issue.

Race	Candidate	AI policy lane	Notable outside spend
NY-12 (Jun 23)	Alex Bores (lost ~35%) vs Micah Lasher (won ~39%)	Frontier vs omnibus	Leading the Future $7M+ anti-Bores; Larsen $3.5M pro-Bores
CA-11 (Jun 2)	Scott Wiener (won 41.3%)	Frontier (SB 53)	High spend; Wiener first in top-two primary
CO-8 (Jun 30)	Manny Rutinel vs Shannon Bird	Consumer vs innovation	$5.5M+ pro-Rutinel per Axios; Anthropic/Google/Meta/OpenAI employees $265K direct

Politico on Leading the Future’s strategy: “Beat up on Bores so badly that when the idea of regulating AI development comes up, other politicians run the other direction.”

Compare to global AI safety funding: ~$200–400M/year worldwide for safety and governance vs. $7M in one primary to stop one assemblyman. The political economy of frontier regulation is dominated by industry offense, not safety-community defense. Pro-regulation money exists (Larsen, Anthropic employees, Encode ecosystem) but concentrates on candidates who can win, not movement infrastructure.

NY-12 case study: Bores vs Lasher

Alex Bores is not an AI safety researcher. He is a NY State Assemblymember (District 73, Manhattan East Side) with a Georgia Tech MS in computer science and a Palantir past — facts his opponents used relentlessly in attack ads. He claims to be the only Democrat elected at any level of NY government with a CS degree.

He is relevant because he co-authored RAISE and ran for Congress on a platform to nationalize it — making him the test case for whether a state-level frontier safety legislator could survive industry PAC warfare and reach the House.

His framework

Bores uses a 3-axis taxonomy for AI legislation:

Outlook: pessimistic vs. optimistic about AI
Time scale: near-term vs. long-term
Scope: use-case-specific vs. general

Most state AI bills are pessimistic + near-term + specific (hiring bias, deepfakes, chatbots for kids). Bores spans all quadrants. RAISE is long-term frontier safety. His NY AI Consumer Protection Act (modeled on Colorado) is near-term algorithmic discrimination. Training data transparency (A6578, passed Assembly unanimously) is near-term general disclosure. Strict liability (A8833) is long-term economic incentive alignment — make developers pay for catastrophic harm regardless of care exercised.

This taxonomy explains something attack ads flatten: Bores voted no on several employment and lending AI bills (A3779, A773) while leading RAISE. His stated reasons: bills imposed costly assessments without changing standards, didn’t cover national banks that dominate the market, or froze state AI adoption for ten years. Lasher co-sponsored those bills and campaigned on Bores’s no votes as proof of inconsistency. Bores’s counter: targeted, implementable regulation beats performative guardrails — read the bill, fix the scope, or don’t pass it.

Both can be true. He is genuinely more selective about which regulations he supports. He is also the public face of frontier safety in a state that passed the country’s strongest transparency law. Those facts coexist uncomfortably.

The money war

NY-12 — the safely Democratic Manhattan seat Bores sought to succeed retiring Jerry Nadler — became the highest AI PAC spend of any 2026 primary.

Side	Actor	Spend (approx.)
Anti-regulation	Leading the Future super PAC (Palantir/OpenAI-aligned funders per press)	$6–7M+ attack ads
Pro-regulation	Chris Larsen (Ripple co-founder)	$3.5M
Pro-regulation	Various safety-aligned donors	~$4.6M total pro-Bores

The paradox: attack ads may have helped — they elevated Bores’s profile, fed an anti-oligarch narrative, and landed him in the New York Times, Vanity Fair, the Ezra Klein Show, and Time 100 AI 2025.

Only ~12% of his campaign contributions came from within NY-12 (February 2026). This was a national fight fought in a Manhattan primary.

Primary result

Eight candidates. Early vote June 13–21. Election day June 23.

Bores’s rival Micah Lasher — former Hochul policy director, co-sponsor of RAISE, champion of SAFE for Kids (social media algorithm restrictions for minors) — ran a broader tech accountability frame: labor, lending, data centers, civil rights, plus frontier safety. Hochul endorsed Lasher and weakened RAISE before signing it — signaling support for AI regulation, but not Bores’s specific lane.

Result: Lasher won ~39% to Bores’s ~35%, a ~4,000-vote margin. NBC/CBS/CNN called it election night. Schlossberg finished third at ~11%.

Leading the Future got its stated goal: Bores is not going to Congress. But 35% second place in an eight-way race, after $7M in attack spending, is not a repudiation of frontier regulation. Lasher co-sponsored RAISE. The industry blocked the author, not the policy.

What Bores still has

Bores remains Assemblymember for AD-73. RAISE is still law. He leads A9449 (chapter amendments aligning operative text with the Hochul compromise), A6578 (training data transparency, Assembly passed), and A10379 (unsafe AI chatbots for minors, passed legislature June 2026, awaiting Hochul signature).

His federal 43-point framework — nationalize RAISE, AI dividend, training data transparency, international safety standards — won’t be introduced by him in Congress. If Scott Wiener wins CA-11 in November, Wiener may become the sole frontier-law author in the House.

The parallel race: Wiener

California’s Scott Wiener won his June 2 primary with 41.3% in a crowded field — same policy lane, different outcome. He authored SB 53. He is expected to carry federal SB 53 nationalization if elected to CA-11 in November.

Two frontier transparency authors ran for Congress in 2026. One won the primary. One lost. The policy template survived both races.

Layer 6: Industry and safety-adjacent actors

Actor	Role in US AI politics
Anthropic	Endorsed SB 53; employees donate to Rutinel; RSP as corporate model; Dario Amodei 2026 shift toward FAA-style mandatory testing
OpenAI	Mixed; superalignment team dissolved 2024; RSI policy paper June 2026; Altman meets White House
Leading the Future	Super PAC; ~$7M anti-Bores; Palantir/OpenAI-aligned funders per press
Encode	Youth org; passed SB 53 and RAISE; opposes GAAIA preemption
Data Center Coalition	Opposes Sanders moratorium
CAIS / METR / GovAI	Research; inform policy but tiny budgets vs. industry lobbying

Industry self-regulation (Anthropic RSP, etc.) remains more detailed than most government policies — but competitive pressure and political spending are the actual governance mechanisms in the US, not RSP compliance alone.

How the layers interact — three scenarios for 2027

Scenario A: State lab wins → federal floor follows

SB 53 and RAISE enforce through 2026–27. Wiener (and possibly Rutinel on consumer provisions) reach Congress. GAAIA preemption stripped or expires. Federal law codifies state template with enforceable penalties. Encode/Wiener playbook: states first, then nationalize.

Scenario B: GAAIA preemption wins

3-year freeze on state development-stage rules. SB 53/RAISE development obligations federally superseded. Industry gets one weaker standard. Chilling effect on next state author confirmed post-Bores.

Scenario C: Populist infrastructure politics escalates

Data center moratoria spread; electricity prices become local election issue; Sanders frame goes mainstream without S.4214 passing. Frontier transparency and infrastructure pause decouple — different coalitions, different bills.

All three can partially coexist. The mistake is assuming one faction “wins” AI politics outright.

What this means for AI safety researchers

Your eval work connects to law. SB 53 and RAISE are now law (or becoming law). If you work at or evaluate frontier labs operating in California or New York, mandatory safety frameworks and incident reporting are not voluntary best practices — they are legal obligations. The definitions of “catastrophic risk” and “critical safety incident” in these bills are worth reading alongside METR/Apollo outputs.
Federal preemption is the highest-leverage political object — more than another eval benchmark. Cruz 99–1 proved broad preemption can die. GAAIA’s narrower version is the live threat. The state-lab strategy worked partially; the federal response is to federalize a version and preempt states for three years (GAAIA), or offer voluntary review with classified benchmarks (Trump EO).
Framing matters. Sanders enters politics through jobs and oligarchs; Bores through CS credentials and nuclear analogies; Wiener through Encode partnership; Lasher through kids and civil rights. Same underlying demand for oversight, four different voter interfaces.
Don’t map Dem=safe, GOP=unsafe. Blackburn saved state AI laws from Cruz. Obernolte wrote GAAIA. Banks pushes RSI visibility. Sacks pushes preemption.
Salience will lag consensus. 81% want pre-deployment testing; AI still isn’t top-five in voter priority. Mobilization requires local, tangible hooks — data center bills, wrongful denial of benefits, teen chatbot harm. NY-12 proved frontier AI regulation is now a national PAC issue; industry’s goal is chilling effect — make the next state legislator think twice before authoring a RAISE equivalent.

For practical entry points: how to participate in AI safety. Calling representatives to oppose broad federal preemption of state AI safety laws remains high-leverage even if you cannot vote.

Open questions (June 2026)

Does Hochul sign A10379 (unsafe AI chatbots for minors) and A11560 (data center moratorium)?
Does the Senate pass A6578 (training data transparency) in 2026?
Does CO-8 nominate Rutinel (June 30 primary)?
Does Wiener win CA-11 general (November)?
Does GAAIA preemption survive stakeholder feedback, or get stripped like Cruz’s moratorium?
Does Lasher in Congress nationalize any RAISE elements or only omnibus civil-rights frame?
If Wiener reaches Congress, does a frontier-transparency coalition (Wiener + Anthropic + Encode) beat an omnibus civil-rights frame (Lasher + labor + AG James)?
Does Bores’s loss chill other state frontier-safety authors — or does RAISE on the books matter more?
Does a trigger event (mass layoffs attributed to AI, election deepfake, data center rate hike) move AI into top-tier salience before 2028?

How this fits the other maps

Article	Scope
Global AI governance landscape	International institutions, EU/China/US vacuum, industry self-regulation, funding gap
This article	US domestic factions, state templates, federal preemption, 2026 races, NY-12 case study, populism, money
What happens before policy changes	Political science playbook: why concern ≠ law, proactive levers before a crisis

The US story in one sentence: policy is being written in state capitols, fought over in primaries, and threatened by federal preemption — while the public wants regulation but hasn’t yet made AI a top-tier election issue. The US still has no federal AI safety law, but for the first time it has state laws that frontier labs must comply with — and a political fight fierce enough to spend seven figures keeping one assemblyman out of Congress.