NY Assemblymember Alex Bores · 2026

Alex Bores — The AI Dividend

Bores AI Dividend

A federal policy proposal from the New York Assemblymember who authored the RAISE Act, now pitching a contingency-based direct payment program designed to activate automatically if AI meaningfully displaces American workers. The AI Dividend is explicitly framed as 'fire insurance' — not a prediction that mass unemployment will occur, but preparation in case it does. The proposal is notable for three novel funding mechanisms: a token tax on AI computation, federal equity warrants in frontier AI companies (out-of-the-money, exercisable only if companies multiply dramatically in value), and tax reform eliminating the accelerated depreciation subsidy for AI capital that currently makes automation cheaper than hiring. Revenue flows to three buckets: direct payments to Americans, workforce transition and education investment, and public AI safety/oversight infrastructure. Bores frames the timing urgency around a closing political window — demanding equity stakes in AI companies after they have already captured the value is far harder than structuring it now.

Key Provisions

Direct payments to Americans triggered by economic conditions — sustained labor force participation declines, wage compression, or AI-driven productivity gains without corresponding job growth
Token tax: a per-unit tax on AI computation (tokens) that scales automatically as AI adoption scales
Federal equity warrants in frontier AI firms — out-of-the-money, exercisable only if companies multiply dramatically, creating a windfall for the public precisely when displacement is worst
Tax reform eliminating accelerated depreciation for AI capital investment that displaces labor — fixing the current ~5% tax on robots vs. ~30% on hiring humans
Revenue allocated three ways: direct payments, workforce transition/education, and public AI safety and oversight infrastructure
Activation tied to clear economic triggers rather than political discretion, ensuring the program responds to real-world conditions

Regulatory Philosophy

Contingency-based economic insurance with automatic triggers. Bores explicitly avoids both the accelerationist claim that AI will only create jobs and the doomer claim that mass unemployment is certain. Instead, the framing is risk management: if there is even a meaningful probability of large-scale displacement, responsible governance requires preparation now while the political window is open and AI companies are still in early growth. The philosophy is closer to options pricing than traditional regulation — the equity warrants pay off precisely in the scenario where the dividend is most needed. Notable for treating the tax code as the primary policy lever: if AI substitutes for labor rather than complementing it, the current tax system is actively subsidizing job elimination.

Where the burden falls

FrontierPrimaryAppsPrimaryHyperscalersPrimaryChipsIndirect

Base assessed: Tokens consumed; AI capital depreciation; frontier enterprise value
Why it lands there: Three instruments, three different layers, which is why this proposal is hard to place and easy to misread as a single tax on AI. The token tax sounds like a tax on AI companies but is a tax on AI buyers, so its incidence is on the app layer and its enterprise customers. Eliminating accelerated depreciation for AI capital assesses whoever owns the machines, which is the hyperscalers. The equity warrants are the only instrument in this landscape aimed squarely and exclusively at the frontier layer.

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Strengths

Derived from the proposal’s own policy documents

+The equity warrant structure is genuinely novel — it creates automatic fiscal alignment where the government's windfall is largest exactly when displacement is worst, without diluting AI company shares unless they succeed enormously
+The token tax is the first concrete proposal to tax AI at the unit of computation rather than the corporate level, creating a funding mechanism that scales automatically with adoption without requiring new legislation each cycle
+Framing as 'insurance, not punishment' is politically deft — it sidesteps the innovation-vs-regulation frame that paralyzes most AI policy debates and makes the proposal legible to both business and labor audiences
+The closing-window timing argument is substantively correct: structuring equity participation in AI companies is orders of magnitude easier before they reach $10T valuations than after
+Bores has actual legislative credibility on AI — he authored the RAISE Act that passed in New York, giving this proposal a concrete track record to point to rather than being purely aspirational

Weaknesses

From the perspective of political opposition

−A state assemblymember's policy paper for a congressional race is not legislation — there are no bill numbers, no committee referrals, no CBO score, and no co-sponsors; this is a campaign document dressed up as policy
−The token tax is trivially evadable: AI companies would simply restructure computation to minimize taxable units, move inference offshore, or redefine what constitutes a 'token' — the analog of the carried-interest loophole for compute
−Federal equity warrants in private companies have no legal precedent and would face immediate Fifth Amendment takings challenges — the government cannot compel private equity participation without triggering constitutional litigation that would delay implementation by years
−Economic triggers sound precise but are politically manipulable in both directions — administrations hostile to the program can redefine thresholds to prevent activation, while sympathetic ones can cherry-pick metrics to trigger it prematurely
−The proposal is silent on how direct payments interact with existing safety net programs (SNAP, Medicaid, unemployment insurance, SSDI) — layering a new cash benefit on top of a patchwork system without addressing integration creates administrative chaos and potential benefit cliffs

Position on Analytical Frameworks

Enforcement Mechanism vs. Regulatory Scope

Prevention vs. Liability & Regulatory Authority

Innovation Priority vs. Worker Protection

Pre-deployment Obligations vs. Federal Preemption

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